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Difficulties in the regulation of emotion are hypothesized to play a key role in the development and maintenance of posttraumatic stress disorder (PTSD). The current study used functional magnetic resonance imaging (fMRI) to assess neural activity during task preparation and image presentation during different emotion regulation strategies, cognitive reappraisal and expressive suppression, in PTSD. Patients with combat-related PTSD (n = 18) and combat-exposed controls (n = 27) were instructed to feel, reappraise or suppress their emotional response prior to viewing combat-related images during fMRI, while also providing arousal ratings. In the reappraise condition, patients showed lower medial prefrontal neural activity during task preparation and higher prefrontal neural activity during image presentation, compared with controls. No difference in neural activity was observed between the groups during the feel or suppress conditions, although patients rated images as more arousing than controls across all three conditions. By distinguishing between preparation and active regulation, and between reappraisal and suppression, the current findings reveal greater complexity regarding the dynamics of emotion regulation in PTSD and have implications for our understanding of the etiology and treatment of PTSD.
This paper tests the new-dialect formation model of Peter Trudgill (1986 et seq) by examining several phonological features of Tibetan as spoken in the diaspora community of Kathmandu, Nepal. Established by an influx of migrants from many dialect regions beginning in 1959, this presents a unique opportunity to study koinéization, new dialect formation, in progress. Trudgill’s model predicts that a new dialect should largely emerge in the second generation born in the new region, exhibiting both simplification, the failure of marked variants to transmit across generations, and focusing, the selection of particular variants as a new norm for the community's new variety.Data from seventy-three sociolinguistic interviews was coded for phonological and lexical variables known to differ across Tibetan-speaking regions, and NeighborNets were constructed in SplitsTree. Results indicate that regionally marked variables were not transmitted into the first or second generation of Diaspora-raised speakers, but Diaspora speakers exhibited a high degree of variation comparable to that of speakers from the numerically- and socially-dominant U-Tsang region. That younger speakers have not yet converged on a single new variety suggests a role for additional factors to affect the rate of koinéization.
Let me begin by thanking the Association for Computational Linguistics and its Executive Committee for conferring on me the great honor of their Lifetime Achievement Award for 2018, which of course I share with all the wonderful students and colleagues that have made many essential contributions to this work over many years.At the heart of the work that I have been pursuing over my research lifetime so far, whether in parsing and sentence processing, spoken language understanding, semantics, or even in musical understanding by machine, there lies a theory of natural language grammar that brings parsing, compositional semantics, statistical modeling, and logical inference into the closest possible relation. This theory of grammar is combinatory, in the sense that its operations are type-dependent and restricted to strictly string-adjacent phonologically or graphologically-realized inputs, and categorial, in the sense that those operands pair a syntactic type with a type-transparent semantic representation or logical form.I'd like to use this opportunity to briefly address three questions that revolve around the theory of grammar, both combinatory and otherwise. The first question concerns the way that Combinatory Categorial Grammar (CCG) was developed with a number of colleagues, over a number of stages and in slightly different forms. The second is an essentially evolutionary question of why natural language grammar should take a combinatory form. The third question is that of what the future holds for CCG and other structural theories of grammar in computational linguistics and NLP in the age of deep learning.I have called this talk "The Lost Combinator" in homage to the Victorian era poem "The Lost Chord," in the hope of suggesting that the theoretical development of CCG has always been empirical, rather than axiomatic, in search of the simplest explanation of the facts of language, rather than for confirmation of linguistic received opinion, however intuitively salient.In the late 1960s (when I was a psychology undergraduate at the University of Sussex under Stuart Sutherland, and then started as a graduate student in artificial intelligence at Edinburgh under Christopher Longuet-Higgins), a broad community of theoretical linguists, psychologists, and computational linguists saw themselves as all working on the same problem, under the definition provided by the "transformational" theory of grammar proposed by Chomsky (1957, 1965), using theories of psycholinguistic processing, language acquisition, and language evolution proposed by Lashley (1951), Miller, Galanter, and Pribram (1960), Miller (1967), and Lenneberg (1967), theories of natural language semantics proposed by Carnap (1956), Montague (1970), and Lewis (1970), and computational models of parsing such as those proposed by Thorne, Bratley, and Dewar (1968) and Woods (1970). (I myself was so convinced that this program would succeed that I believed it was time to apply the same methods to other cognitive faculties, taking as my research project for Ph.D. their application to the interpretation of music by machine, following the lead of Max Clowes [1971] in machine vision.)Almost immediately, this consensus fell apart. First, Chomsky himself was among the first (1965) to recognize that transformational rules, though descriptively revealing, were so expressive as to have little explanatory force, and required many apparently arbitrary constraints (Ross 1967). Second, psychologists realized that psycholinguistic measures of processing difficulty of sentences bore almost no relation to their transformational derivational complexity (Marslen-Wilson 1973; Fodor, Bever, and Garrett 1974). Finally, computational linguists attempting to implement transformational grammars as parsers realized that they were spending all their time implementing even more constraints on rules, in order to limit search arising from overgeneration (Friedman 1971; Gross 1978). (Meanwhile, I realized that the problem had not in fact been solved, and returned to natural language processing, thanks to a postdoc at Sussex with Philip Johnson-Laird.)This disillusion wasn't just a case of internal academic squabbling. There were also a couple of influential reports commissioned by the U.S. and UK governments that ended funding for machine translation (MT) and artificial intelligence (AI) (Pierce et al. 1966; Lighthill 1973). As a result of the second of these reports, which determined that AI was never going to work, PhDs in artificial intelligence like my classmate Geoff Hinton and myself spent ten years or so after graduation in psychology departments (in my case, at the Universities of Sussex and Warwick), until yet another report said AI was working after all and that Britain and the U.S. were falling behind Japan in this vital area. As a result, I could get hired again in computer science, first briefly back at Edinburgh, and then at the University of Pennsylvania (I learned a lesson from this odyssey that I have tried to remember whenever I have been appointed to a committee to report on anything, which is that while reports very rarely do any good, they can very easily do a great deal of harm.)Meanwhile, as a result of these conflicts, the scientific study of language fragmented. The linguists swiftly abjured any responsibility for their grammars ("Competence") bearing any relation to processing ("Performance"). Because the psychologists could hardly abandon Performance, they in turn became agnostic about grammar, retreating to context-free surface grammar (which they tended to refer to as "parsing strategies"), or a touchingly optimistic belief in its emergence from neural models. Meanwhile, the computational linguists (whose machines were growing exponentially in size and speed from the 16K byte core of the machine that supported the whole group when I started my graduate studies, on to levels that would soon permit parsing the entire contents of the then embrionic Web) similarly found that very little of what the linguists and psychologists cared about was usable at scale, and that none of it significantly improved overall performance over very much simpler context-free or even finite-state methods that the linguists had shown to be incomplete. The reason of course was Zipf's law, which means that the events with respect to which the low-level methods are incomplete are off in the long tail.It also became apparent to a few computationalists working on speech, MT, and information retrieval that the real problem was not grammar but ambiguity and its resolution by world-knowledge, and that the solution lay in probabilistic models (Bar-Hillel 1960/1964; Spärck Jones 1964/1986; Wilks 1975; Jelinek and Lafferty 1991) (although it was not immediately apparent how to combine statistical models with grammar-based systems without making obviously false independence assumptions).Nevertheless, as any red-blooded psychologist had always insisted, the divorce between competence and performance that everyone else had accepted did not make any sense. The grammar and the processor had to have evolved in lock-step, as a package deal, for what could be the evolutionary selective advantage of a grammar that you cannot process, or a parser without a grammar?It seemed equally obvious that surface syntax and the underlying semantic or conceptual representation must also be closely related, since the only reasonable basis for child language acquisition that has ever been on offer is that the child attaches language-specific grammar to a universal conceptual relation or "language of mind" (Miller 1967; Bowerman 1973; Wexler and Culicover 1980). It seemed to follow that radically new theories of grammar were needed.Theoretical linguists agree that the central problem for the theory of grammar is discontinuity or non-adjacent dependency between predicates and their arguments:Chomsky described discontinuity in terms of movement, which was known to be formally very unconstrained. By contrast, the ATN parser used in the LUNAR project (Woods, Kaplan, and Nash-Webber 1972) reduced all discontinuity to local operations on registers (Thorne, Bratley, and Dewar 1968; Bobrow and Fraser 1969; Woods 1970).In particular, unbounded wh-dependencies like the above were handled by: (a) putting a pointer into a * or HOLD register as soon as the "which" was encountered without regard to where it would end up; and (b) retrieving the pointer from HOLD when the verb needing an object "had" was encountered without regard to where it had started out. (It also included an ingenious mechanism for coordination called SYSCONJ, which one finds even now being reinvented on an almost yearly basis—cf. Woods [2010].) A * register was also used for wh-constructions within a systemic grammar framework by Winograd (1972, pages 52–53) in his inspiring conversational program SHRDLU.However, it was unclear how to generalize the HOLD register to handle the multiple long-range dependencies, including crossing dependencies, that are found in many other languages. In particular, if the HOLD register were assumed to be a stack, then the ATN becomes a two-stack machine (since we are already implicitly using one stack as a PDA to parse the context-free core grammar).On the computational side at least, the reaction to this impass took two distinct forms. Both reactions took the form of trying to reduce the two major operators of the transformation theory, substitution of immediate constituents, or what is nowadays called "Merge," and "Move," or displacement of non-immediate constituents, to one. On the one hand, Lexical Functional Grammar (Bresnan and Kaplan 1982) and Head-driven Phrase Structure Grammar (Pollard and Sag 1994) followed Kay (1979) in making unification the basis of movement and merger. Because unification can pass information across unbounded structures, this can be thought of as reducing Merge to Move.On the other hand, Generalized Phrase Structure Grammar (Gazdar 1981), Tree Adjoining Grammar (TAG; Joshi and Levy 1982), and Combinatory Categorial Grammar (CCG, Ades and Steedman, 1982) sought to reduce Move to various forms of local merger. In particular, the latter authors suggested that the same stack could be used to capture both long-range dependency and recursion in CCG.1Natural language grammar exhibits discontinuity because semantically language is an applicative system. Applicative systems (such as programming languages) support the twin notions of: (a) Application of a function/concept to an argument/entity; and (b) Abstraction, or the definition of a new function/concept in terms of existing ones.Language is in that sense inherently computational. It seems to follow that linguistics is (or should be) inherently computational as well. (Of course, it does not follow that computationalists have nothing to learn from linguistics.)There are two ways of modeling abstraction in applicative systems: Taking abstraction itself as a primitive operation (λ-calculus, LISP):(2)a.fatherEsau⇒Isaacb.grandfather=λx.father(fatherx)c.grandfatherEsau⇒Abrahamor Defining abstraction in terms of a collection of operators on strictly adjacent terms aka Combinators, such as function composition (Combinatory Calculus, MIRANDA).(3)b′.grandfather=BfatherfatherThe latter does the work of the λ-calculus without using any variables.Despite the resemblance of the "traces" (or copies) and "operators" (or complementizer positions) of the transformational theory to the λ-operators and variables of applicative systems of the first kind, natural language actually seems to be a system of the second, combinatory kind. The evidence stems from the fact that natural language deals with all sorts of fragments that linguists do not normally think of as semantically typable constituents, without the use of any phonologically realized equivalent of variables, such as pronouns:(4)a.Give[Anna books]?and[Manny records]?b.(Mother to child): There's adoggie![Youlike]?#the doggie.c.Food that you must[washVP/NP[before eating](VP∖VP)/NP]?.d.ik denk dat ik1Henk2Cecilia3[zag1leren2zingen3]?These fragments are diagnostic of a Combinatory Calculus based on Bn, T, and the "duplicator" Sn, plus application (Steedman 1987; Szabolcsi 1989; Steedman and Baldridge 2011).2CCG lexicalizes all bounded dependencies, such as passive, raising, control, exceptional case-marking, and so forth, via lexical logical form. All syntactic rules are Combinatory—that is, binary operators over contiguous phonologically realized categories and their logical forms. These rules are restricted by a Combinatory Projection Principle, which in essence says they cannot override the decisions already taken in the language-specific lexicon, but must be consistent with and project unchanged the directionality specified there. All such language-specific information is specified in the lexicon: The combinatory rules like composition are free and universal. All arguments, such as subjects and objects, are lexically type-raised to be functions over the predicate, as if they were morphologically cased as in Latin, exchanging the roles of predicate and argument.All long-range dependencies are established by contiguous reduction of a wh-element, such as (N∖N)/(S/NP), with an adjacent non-standard constituent with category S/NP, formed by rules of function composition.The combinatory rules synchronize composition of the syntactic types shown here with corresponding composition of logical forms (suppressed in the derivations above), to yield the logical forms shown as λ-terms for the resulting nouns N.To capture the construction in Example (4c), whose syntactic derivation we pass over here, we also need rules based on the duplicator S:(7)a."wash X before eating X″b.VP/NP:λx.before(eatx)(washx)≡S(Bbeforeeat)washTo capture constructions like Example (4d) (whose syntactic derivation is similarly suppressed), we also need rules based on second-order composition B2:(8)a."Y saw X teach W to sing.″b.((S∖NP)∖NP)∖NP:λwλxλy.help(teach(singw)wx)xy≡B2sees(Bteachsing)CCG thus reduces the operator move of transformational theory to applications of purely adjacent operators—that is, to recursive combinatory merge.Interestingly, the latest "minimalist" form of the transformational theory has also proposed that Move should be relabeled as an "internal" form of standard or "external" Merge (Chomsky 2001/2004, page 110), though without providing any formal basis for the reduction other than identifying internal Merge as "a grammatical transformation." (If anything deserved the soubriquet "the lost combinator," it would be this notional unitary combination of application and abstraction in a single perfect operator, linking or merging all types, as in the epigraph to this article.)B2 rules allow us to "grow" categories of arbitrarily high valency, such as ((S∖NPy)∖NPx)∖NPw. As we saw earlier, in some Germanic languages like Dutch, Swiss German, and West-Flemish, serial verbs are linearized using such rules to require crossing discontinuous dependencies. Thus, B2 rules give CCG slightly greater than context-free power.Nevertheless, CCG is still not as expressive as movement. In particular, we can only capture permutations that are what is called "separable," where separability is related to the idea of obtaining the permutations by rebracketing and rotating sister nodes (Steedman 2018).For example, for the categories of the form A|B, B|C, C|D, and D, it is obvious by inspection that we cannot recognize the following permutations:(9)i.*B|CDA|BC|Dii.*C|DA|BDB|CThis generalizatiion appears likely to be true cross-linguistically for the components of this form for the NP "These five young boys":(10)i.*Five boys these youngii.*Young these boys fiveTwenty-one of the 22 separable permutations of "These five young boys" are attested (Cinque 2005; Nchare 2012). The two forbidden orders are among the unattested three.3The probability of this happening by chance is the probability of the is the of the number of ways of two of three unattested by the is, about one in a (If the order that unattested so were to be this chance would to about one in number of separable permutations much more in than the number of all example, for around of the permutations are There are obvious for the problem of in machine translation and neural semantic parsing, to which we I to and at first as a still under least, that was what Joshi and then as a of where much of the development of CCG was out. students in a of and Joshi 1987; and that the of Ades and Steedman was by that both CCG and were equivalent to Grammar (Gazdar a new of the by the and of languages by these fell within the of what Joshi called which proposed as a for what could as a theory of natural that they are and and some limit on crossing dependencies. the is much much than the including the multiple free languages and even the languages of so it seems to and CCG as with to the its CCG was assumed to be as a grammar for parsing, because of the derivational ambiguity by and the combinatory rules, these also under and as any grammar with the same as CCG the same of in the parser it is there in the In this is just another in the of derivational ambiguity that all natural language and can be handled by the same statistical models as other particular, the dependency models by and are and Steedman and CCG is also to parsing with which can be using and long and Steedman and is now used in those that for between semantic and syntactic processing, such as machine translation and and machine and parsing and Steedman 1987; and et al. et al. et al. and semantic parser and 2005; et al. et al. of my work with the same has returned to their application in musical and and Steedman and shown that CCG grammars of the same and parsing models of the same statistical are required there as It is only in the of their compositional semantics that music and language very than on this of work in like to by two more The first is an evolutionary should natural language be a combinatory in the first The second is a question about the future development of CCG and other grammar-based theories to be to NLP in the age of deep and recursive neural take these questions in order in the two language like a combinatory applicative system because T, and evolved in to support of before there was any language (Steedman like need and are for of need to to make can form the that you need to before is to that they allow and some other can with like B2 are to make with arbitrary of including and including other whose is yet to be to be to do the the and problem, using like to in order to that are of to of and so such as of and can apply to a and much work that the and other have to be there in the already for the to be to with was to that from the even if had the problem of can be as the problem of search for a of in a or of possible such search has the same recursive as parser example, there are both and for the The latter a more in evolutionary as a mechanism that is to both semantic interpretation and parsing, rather than the evolution of like the the for linguistic as as the operators for competence grammar, the two to as what was to above as an evolutionary hope to have convinced you that CCG grammars are both and as as semantic parsers that are to parse the like other CCG parsers are by the of parsing models based on only a of no how we using and the constructions they are dependencies and so as we have and off in the long As a parsers are to on performance overall by using models et al. says more about the of grammars and parsers than about the of deep in the of semantic parser for arbitrary such as and Steedman I would that CCG and other grammar-based parsers have already been by of deep neural and and the question of whether models for applications in are because we have to the universal semantic that allow the child to CCG for natural languages and that we to be using both in semantic parser and in Because the language is any of linguistic logical like the universal language of it be more with and to semantic parsers for by deep neural force, rather than by CCG semantic parser is it possible that the problem of parsing could be by neural by stack et al. et al. actually learn as has been seems likely that semantic parsers and neural machine translation to have difficulty with long-range because the evidence for their is so example, both and as a case, verb categories or a complementizer I is actually by which says that if you are an language with like and then you not in be to in languages like or languages like and German, you be to both subjects and objects, or at the time of a translation system no of learned these syntactic from a we get an sentence whose to translation means is the that the us the a is the that the us to the if we with we (which back into the a is the that the us holds the a we with using a the translation again an that is is the that they said had the is the they said they the contrast, CCG parsers do rather on and Steedman Steedman, and which is a construction that to be rather determined by the parsing methods are similarly when with long-range even when the sentence is in this think that the the and that it is et think that the the and it is in at least, these constructions could be learned by grammar-based semantic parser from using the methods of et al. and et al. make it likely that there be a need for in like where long-range dependencies like deep and are here to The future in parsing for such lies with systems using neural for and grammars for problem in NLP the fact that natural language understanding inference as as semantics, and we have no idea of the representation question is the almost it many it is almost equally to the information in a form that is not immediately with the form of the example, sentences like the following a different a rather than a an an a a and at a representation language that is we are using CCG parsers to the for between in order to consistent of between over of the same types, using over then an it and it under such as et al. of in the then that can be to a single relation and Steedman can be across from multiple languages and Steedman can then the semantics for relation with the and the entire using this now both and semantic an with the as and the as questions the in this we parse questions into the same semantics which is now the language of the the we use the and the and the following anything that in the then the the of anything is in the in the this to work, we need to be nodes in their in both and then be to like in of a semantic in the language of the need to learn between semantic and the language of the this project is the the function of a of the semantic in semantic like those of and and Steedman and while the form a similarly of the of Carnap and Fodor, Fodor, and Garrett semantic are essentially but with the advantage that they can be with logical operators such as and for the of semantic underlying natural language semantics in to another different to semantics that to use reduced of to using operations such as and and in of compositional It is an question whether can be with to of a and et al. It is likely that some of be here to the of the of the long like and work in do they work in In particular, can they learn all the syntactic in the long like and crossing in a way that support semantic they are not actually but are a finite-state or a then by on as for natural language processing, we are in of of the computational linguistic project of also providing computational of language and if we that like is a real and that learn their first language by of the sentences of their language the of the universal language of we still the of what that universal semantic language not get an to that question we can above using and and such as as for the language of to use machine for what it is such variables and their for use in a natural language work was supported in by a Award and a a University of Edinburgh and my and the and all my and students over many
Sequence-to-sequence constituency parsing casts the tree structured prediction problem as a general sequential problem by top-down tree linearization,and thus it is very easy to train in parallel with distributed facilities. Despite its success, it relies on a probabilistic attention mechanism for a general purpose, which can not guarantee the selected context to be informative in the specific parsing scenario. Previous work introduced a deterministic attention to select the informative context for sequence-to-sequence parsing, but it is based on the bottom-up linearization even if it was observed that top-down linearization is better than bottom-up linearization for standard sequence-to-sequence constituency parsing. In this paper, we thereby extend the deterministic attention to directly conduct on the top-down tree linearization. Intensive experiments show that our parser delivers substantial improvements over the bottom-up linearization in accuracy, and it achieves 92.3 Fscore on the Penn English Treebank section 23 and 85.4 Fscore on the Penn Chinese Treebank test dataset, without reranking or semi-supervised training.
The cognitive nature of Ukrainian nickname constructionThis article is devoted to the study of the cognitive nature of the informal anthroponym creation mechanisms in the everyday communication of Ukrainian speakers. The article traces the role of the associative factors, nominational motives, and cultural, historical and social circumstances that play a direct role in the emergence of informal naming. The article also examines the wide variations in unofficial anthroponyms in spoken Ukrainian, their uniqueness, and their temporal and local character. On one hand, nicknames are not codified. They are prone to variation and susceptible to temporality. On the other hand, they are regulated by certain lexical and word-building norms, as well as custom. It is observed that nicknames reveal both a direct and an indirect (metaphorical) nomination. The article emphasises the cognitive nature of informal names, which is based on a direct or metaphorical resemblance to well-known public figures from the past or present: politicians, actors, artists, musicians, athletes, artists, writers, television characters, etc. Occupations and professions are also analysed as sources of semantic associations which give rise to informal names. It has been revealed that there is a large number of teacher nicknames based on internal associative connections, in which sarcasm is especially expressive. The article also examines the cognitive-axiological mechanisms of nicknames, the emergence of which is associated with an unusual event or a special situation in the life of the named individual. Poznawcza natura tworzenia przezwisk w języku ukraińskimNiniejszy artykuł poświęcony jest badaniu poznawczej natury mechanizmów tworzenia potocznych antroponimów w codziennej komunikacji Ukraińców. Autorzy przedstawiają rolę czynników asocjacyjnych, przyczyny nominacji, uwarunkowania kulturalno-historyczne i społeczne, które bezpośrednio wpływają na pojawienie się potocznego nazewnictwa. Autorzy wskazują również na szeroką różnorodność nieoficjalnych antroponimów w ukraińskim języku mówionym, ich szczególny koloryt, charakter okolicznościowy i lokalny. Z jednej strony przezwiska nie są skodyfikowane, nie podlegają zmianom, nie są podatne na upływ czasu, z drugiej strony są regulowane przez pewne normy leksykalne i słowotwórcze, prawo zwyczajowe. Należy zauważyć, że przezwiska wykazują zarówno bezpośrednią, jak i pośrednią (metaforyczną) nominację. Autorzy podkreślają poznawczą naturę nieoficjalnych nazw, które powstały w oparciu o bezpośrednie lub metaforyczne podobieństwo do innych znanych osób w życiu publicznym kiedyś i obecnie: polityków, aktorów, artystów, muzyków, sportowców, artystów, pisarzy, bohaterów telewizyjnych itp. Przeanalizowano również korzenie i związki semantyczne w nieoficjalnym nazewnictwie, motywowane zajęciem lub profesją ludzi. Stwierdzono, że istnieje duża liczba przydomków nauczycieli, które pojawiły się poprzez wewnętrzną asocjację, w której delikatna natura i sarkazm są szczególnie wyraziste. Zwrócono również uwagę na poznawczo-aksjologiczne mechanizmy pseudonimów, których pojawienie się wiąże się z nietypowym zdarzeniem lub szczególnym przypadkiem w życiu osoby go noszącej.
There is a sizable literature on the causes and effects of candidate positioning in elections. An implication of this research is that candidates present clear issue positions to the electorate and citizens then make voting decisions based on this information. However, if candidates are ambiguous in the positions they take, this may impair voters’ decision-making and prompt voters to punish them for inconsistency. Although there is a growing literature on the effects of candidate and party ambiguity, consensus on the implications of ambiguity for candidates and voters is yet to be achieved. Using data from the 2010 House elections, we find that candidate ambiguity undermines voters’ ability to vote consistent with the spatial logic just as Downs speculated. We also find, in contrast to Downs, that voters punish rather than reward candidate ambiguity. We suggest that a possible mechanism is in voters’ valence ratings of candidates.
We propose a novel neural network model for joint part-of-speech (POS) tagging and dependency parsing. Our model extends the well-known BIST graph-based dependency parser (Kiperwasser and Goldberg, 2016) by incorporating a BiLSTM-based tagging component to produce automatically predicted POS tags for the parser. On the benchmark English Penn treebank, our model obtains strong UAS and LAS scores at 94.51% and 92.87%, respectively, producing 1.5+% absolute improvements to the BIST graph-based parser, and also obtaining a state-of-the-art POS tagging accuracy at 97.97%. Furthermore, experimental results on parsing 61 "big" Universal Dependencies treebanks from raw texts show that our model outperforms the baseline UDPipe (Straka and Strakov, 2017) with 0.8% higher average POS tagging score and 3.6% higher average LAS score. In addition, with our model, we also obtain state-of-the-art downstream task scores for biomedical event extraction and opinion analysis applications.
The purpose of this article is to highlight problems with a range of semantic psycholinguistic variables (concreteness, imageability, individual modality norms, and emotional valence) and to provide a way of avoiding these problems. Focusing on concreteness, I show that for a large class of words in the Brysbaert, Warriner, and Kuperman (Behavior Research Methods 46: 904–911, 2013) concreteness norms, the mean concreteness values do not reflect the judgments that actual participants made. This problem applies to nearly every word in the middle of the concreteness scale. Using list memory experiments as a case study, I show that many of the “abstract” stimuli in concreteness experiments are not unequivocally abstract. Instead, they are simply those words about which participants tend to disagree. I report three replications of list memory experiments in which the contrast between concrete and abstract stimuli was maximized, so that the mean concreteness values were accurate reflections of participants’ judgments. The first two experiments did not produce a concreteness effect. After I introduced an additional control, the third experiment did produce a concreteness effect. The article closes with a discussion of the implications of these results, as well as a consideration of variables other than concreteness. The sensorimotor experience variables (imageability and individual modality norms) show the same distribution as concreteness. The distribution of emotional valence scores is healthier, but variability in ratings takes on a special significance for this measure because of how the scale is constructed. I recommend that researchers using these variables keep the standard deviations of the ratings of their stimuli as low as possible.
Predictive language processing is often studied by measuring eye movements as participants look at objects on a computer screen while they listen to spoken sentences. This variant of the visual-world paradigm has revealed that information encountered by a listener at a spoken verb can give rise to anticipatory eye movements to a target object, which is taken to indicate that people predict upcoming words. The ecological validity of such findings remains questionable, however, because these computer experiments used two-dimensional stimuli that were mere abstractions of real-world objects. Here we present a visual-world paradigm study in a three-dimensional (3-D) immersive virtual reality environment. Despite significant changes in the stimulus materials and the different mode of stimulus presentation, language-mediated anticipatory eye movements were still observed. These findings thus indicate that people do predict upcoming words during language comprehension in a more naturalistic setting where natural depth cues are preserved. Moreover, the results confirm the feasibility of using eyetracking in rich and multimodal 3-D virtual environments.
Frequency distribution of words, syntax and semantics in many languages abides by certain laws. However, because of the shortage of discourse corpora, few studies have examined whether the frequency of discourse relations follows some distributional patterns. Although there is some research based on the Rhetorical Structure Theory discourse treebank (RST-DT), each of these studies is limited to a single language. Otherwise to the RST-DT, the Penn Discourse Treebank (PDTB), adopting another annotation system, has had an enormous influence on the study of discourse structure and discourse annotation. Discourse corpora in other languages, such as Chinese, Hindi, Turkish, Czech and Arabic have been annotated following PDTB style. With the data from these discourse treebanks, we find that the rank-frequency of discourse relations follow the same pattern and that these languages share significant similarities in using semantic relations to organize the discourse. It is evidenced in our research that humans assume the relationship between two consecutive sentences is a causal connection or expansion link for fewer connectives used, but the relation of contrast is the most marked by connectives. This research will be of significance for understanding the homogeneity of discourse structure across languages.
This work investigates legal concepts and their expression in Portuguese, concentrating on the “Order of Attorneys of Brazil” Bar exam. Using a corpus formed by a collection of multiple-choice questions, three norms related to the Ethics part of the OAB exam, language resources (Princeton WordNet and OpenWordNet-PT) and tools (AntConc and Freeling), we began to investigate the concepts and words missing from our repertory of concepts and words in Portuguese, the knowledge base OpenWordNet-PT. We add these concepts and words to OpenWordNet-PT and hence obtain a representation of these texts that is mostly “contained” in the lexical knowledge base.
The dorsolateral prefrontal cortex (DLPFC) plays a key role in the modulation of affective processing. However, its specific role in the regulation of neurocognitive processes underlying the interplay of affective perception and visual awareness has remained largely unclear. Using a mixed factorial design, this study investigated effects of inhibitory continuous theta-burst stimulation (cTBS) of the right DLPFC (rDLPFC) compared to an Active Control condition on behavioral (N=48) and electroencephalographic (N=38) correlates of affective processing in healthy Chinese participants. Event-related potentials (ERPs) in response to passively viewed subliminal and supraliminal negative and neutral natural scenes were recorded before and after cTBS application. We applied minimum-norm approaches to estimate the corresponding neuronal sources. On a behavioral level, we found evidence for reduced emotional interference by, and less negative and arousing ratings of negative supraliminal stimuli following rDLPFC inhibition. We found no evidence for stimulation effects on self-reported mood or the behavioral discrimination of subliminal stimuli. On a neurophysiological level, rDLPFC inhibition relatively enhanced occipito-parietal brain activity for both subliminal and supraliminal negative compared to neutral images (112-268ms; 320-380ms). The early onset and localization of these effects suggests that rDLPFC inhibition boosts automatic processes of ‘emotional attention’ independently of visual awareness. Further, our study reveals the first available evidence for a differential influence of rDLPFC inhibition on subliminal versus supraliminal neural emotion processing. Explicitly, our findings indicate that rDLPFC inhibition selectively enhances rather late (292-360ms) activity in response to supraliminal negative images. We tentatively suggest that this differential frontal activity likely reflects enhanced awareness-dependent down-regulation of negative scene processing eventually leading to facilitated disengagement from and less negative and arousing evaluations of negative supraliminal stimuli.
Automatic syntactic parsing for question constructions is a challenging task due to the paucity of training examples in most treebanks. The near absence of question constructions is due to the dominance of the news domain in treebanking efforts. In this paper, we compare two synthetic low-cost question treebank creation methods with a conventional manual high-cost annotation method in the context of three domains (news questions, political talk shows, and chatbots) for Modern Standard Arabic, a language with relatively low resources and rich morphology. Our results show that synthetic methods can be effective at significantly reducing parsing errors for a target domain without having to invest large resources on manual annotation; and the combination of manual and synthetic methods is our best domain-independent performer.
propos des nologismes lis la mode et de leur circulation en franais et en tchque Rsum La mondialisation, qui acclre les contacts entre les langues, facilite normment la circulation des expressions nologiques dans des langues non apparentes. Un des domaines touchs par des apparitions particulirement nombreuses des expressions nologiques est celui de la mode et du style. De nouveaux mots, tels que hipster, preppy, girly, se propagent rapidement dans la culture anglo-amricaine et envahissent aussi les langues qui sont en contact avec cette culture. Le franais et le tchque ne font pas exception. tant donn que ce champ lexical n'a pas t exploit de manire comparative, nous avons dcid de dcrire certains mots lis au style dans ces deux langues. Sur un corpus fond sur nos propres connaissances du thme et sur un lexique trouv dans la presse, nous essayons de dcrire la prsence des lexmes choisis dans les deux langues et de comparer leur existence dans les diffrents types de documents, leur diffusion ainsi que leur nature et leur place dans les deux langues tudies, le franais et le tchque.
There has been a vast development of personal informatics devices combining sleep monitoring with alarm systems, in order to find an optimal time to awaken a sleeping person in a pleasant way. Most of these systems implement auditory feedback, which is not always pleasant and may disturb other sleepers. We present an adaptive alarm system that detects sleeping cycles and triggers alarm signal during shallow sleep, to minimize sleep inertia. Since tactile sensation is associated with positive valence, vibrotactile stimulation is investigated as a silent alarm to enhance pleasant awakening. Three modulation techniques to render the tactile stimuli for pleasant awakening are considered, namely simultaneous, continuous, and successive stimulation. Two experimental studied are conducted. Experiment 1 studied exogenous attention towards tactile stimulation in a multimodal scenario (involving visual and haptic interactions) with fully awake individuals. Results from the attention task and the subjective valence rating suggest that the vibrotactile stimulation should be based on the continuous modulation, since this not only is very perceivable but also associated with positive attention. Experiment 2 evaluated the user experience with tactile stimulation patterns during sleep. Results confirmed the findings of experiment 1. Continuous modulation was rated highest for pleasant yet arousing sleep-awake transition.
We present PAWS, a multi-lingual parallel treebank with coreference annotation. It consists of English texts from the Wall Street Journal translated into Czech, Russian and Polish. In addition, the texts are syntactically parsed and word-aligned. PAWS is based on PCEDT 2.0 and continues the tradition of multilingual treebanks with coreference annotation. The paper focuses on the coreference annotation in PAWS and its language-specific differences. PAWS offers linguistic material that can be further leveraged in cross-lingual studies, especially on coreference.
In this paper we describe the extensions we made to an existing treebank query application (GrETEL). These extensions address user needs expressed by multiple linguistic researchers and include (1) facilities for uploading one’s own data and metadata in GrETEL; (2) conversion and cleaning modules for uploading data in the CHAT format; (3) new facilities for analysing the results of the treebank queries in terms of data, metadata and combinations of them. These extensions have been made available in a new version (Version 4) of GrETEL.
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In this paper, we describe the annotation and development of Telugu treebank following the Universal Dependencies framework. We manually annotated 1328 sentences from a Telugu grammar textbook and the treebank is freely available from Universal Dependencies version 2.1.1 In this paper, we discuss some language specific annotation issues and decisions; and report preliminary experiments with POS tagging and dependency parsing. To the best of our knowledge, this is the first freely accessible and open dependency treebank for Telugu.
We introduce the syntactic scaffold, an approach to incorporating syntactic information into semantic tasks. Syntactic scaffolds avoid expensive syntactic processing at runtime, only making use of a treebank during training, through a multitask objective. We improve over strong baselines on PropBank semantics, frame semantics, and coreference resolution, achieving competitive performance on all three tasks. them he After encouraging them, told goodbye and left for STIMULATE _EMOTION
Larysa Kolibaba PhD in Philology, Senior Research Scientist of the Department of Grammar and Scientific Terminology, Institute of the Ukrainian Language of National Academy of Sciences of Ukraine 4 Hrushevskyi St., Kyiv 01001, Ukraine Е-mail: kolibaba.lm@meta.ua Heading: Researches Language: Ukrainian Abstract: In this article the problem of fixing of morphological forms of nouns in the Ukrainian dictionaries of different time and its […]
Implicit discourse relation recognition is a challenging task as the relation prediction without explicit connectives in discourse parsing needs understanding of text spans and cannot be easily derived from surface features from the input sentence pairs. Thus, properly representing the text is very crucial to this task. In this paper, we propose a model augmented with different grained text representations, including character, subword, word, sentence, and sentence pair levels. The proposed deeper model is evaluated on the benchmark treebank and achieves state-of-the-art accuracy with greater than 48% in 11-way and F1 score greater than 50% in 4-way classifications for the first time according to our best knowledge.
This paper describes our system (HIT-SCIR) submitted to the CoNLL 2018 shared task on Multilingual Parsing from Raw Text to Universal Dependencies. We base our submission on Stanford's winning system for the CoNLL 2017 shared task and make two effective extensions: 1) incorporating deep contextualized word embeddings into both the part of speech tagger and parser; 2) ensembling parsers trained with different initialization. We also explore different ways of concatenating treebanks for further improvements. Experimental results on the development data show the effectiveness of our methods. In the final evaluation, our system was ranked first according to LAS (75.84%) and outperformed the other systems by a large margin.
We present a progress report of the Turkish Treebank concentrating on various aspects of its design and implementation. In addition to a review of the corpus compilation process and the design of the annotation scheme, we describe the details of various pre-processing stages and the computer-assisted annotation process.
In the modern world it can be easy to encounter advertising slogans that are supposed to grab the attention of a potential recipient as well as affect their imagination and sensitivity. This communication tends to convince the client that buying the advertised product would make them feel exceptional. This article focuses on linguistic gimmicks that are used by marketing experts in order to convince the client to a certain product. The analysis in based on the cosmetics sector. The lexical database consists of websites, television commercials and Internet advertisements.
Aims: Eating disorders are typically associated with high self-criticism of one’s body, and there are hints that patients also stigmatize other people for their weight more than healthy people do. In this study, we use questionnaire data as well as two desktop computer tasks to investigate (1) whether people with eating disorders assign negative attributes to increasing weight and (2) whether weight-related stigmatization is stronger than in healthy controls. Methods: 30 eating disorder patients and 30 healthy controls are assessed. To measure evaluation of the own body, we use a set of established questionnaires (EDE-Q, BIQ-20, EDI-2). Weight bias is assessed with the Fat Phobia Scale and with two computer tasks. In task 1, we present computer generated bodies of varying body mass index (BMI; kg/m²) and ask for ratings how much a set of adjectives apply to this body. Also, we collect valence ratings for the adjectives. In task 2, participants freely model bodies to fit the same adjectives, and we afterwards compute the bodies’ BMI. Results: We assessed 10 patients with anorexia nervosa, 5 patients with bulimia nervosa and 10 patients with binge eating disorder. Pilot analyses with seven patients suggested significant correlations between BMI and attribution of adjectives. Heavier bodies were evaluated as fatter and more pear shaped, but also as more clumsy, lazy and less goal-oriented. In task 2, the adjusted body weight was significantly correlated with valence of the adjective. Conclusions: Preliminary data show that our tasks are appropriate to capture weight stigma. More detailed analyses will be presented at the conference. A multi-center assessment is planned to enable comparisons between different diagnoses.
This paper investigates the relation of syntax and communicative functions. We contrasted Dependency Grammar (DG) that sees syntax as autonomous and independent of its possible communicative uses with Construction Grammar (CxG) that maintains that the building blocks of language are stored form-meaning pairings, including phrasal patterns which may be associated with particular communicative or discourse functions. We constructed two treebanks of Hebrew, of parental speech and of young children's speech, parsing the sentences for DG and coding them for the communicative function of the utterances. The communicative-syntactic system is modeled as a bipartite network of verb-direct object (VO) combinations and of communicative functions (CF). DG predicts that VO-CF matching be scale-free, whereas CxG predicts that the matching is one-to-one. Next, we analyzed the degree of assortativity of the VO-CF bipartite network. We calculated a Pearson's correlation coefficient between the degrees of all pairs of connected nodes, predicting a positive assortativity on CxG and a negative one, on DG. The results do not support the concept of holistic constructions fusing syntactic structures and communicative functions. Instead, the communicative-syntactic system is a complex system with sub-systems mapping onto one another.
Emotional imagery is a common induction technique used in the laboratory and also employed in various exposure therapy treatments across the anxiety spectrum (e.g., specific and social phobias). Despite its clinical uses, there is a surprising dearth of literature regarding the basic central neural processes underlying emotional imagery, though other peripheral physiological processes have been investigated extensively using heart rate, skin conductance, and startle-blink responses. One imagery study that used a central nervous system psychophysiological measure -event specific brainwave or the event-related potential (ERP) technique- suggests the late positive potential (LPP) of the ERP is larger for unpleasant versus neutral stimuli, implying this ERP may index emotional engagement during imagery. This effect is consistent with the visual perception literature of emotion; however, the visual perception literature also indicates that the LPP is larger for pleasant stimuli versus neutral stimuli and positively correlated with subjective emotional arousal ratings. Using script-driven emotional imagery, we will extend research on the LPP to establish whether 1) the LPP is larger for both pleasant and unpleasant scripts relative to neutral ones and 2) this LPP effect is positively correlated with emotional arousal ratings. Fifty-five participants will make subjective ratings of the scripts and then imagine the scripts while electroencephalographic data are, recorded. Upon demonstrating the LPP is larger for emotional (both pleasant and unpleasant) scripts than neutral ones, this study will lay the foundation for future work aimed at determining whether LPP effects are hyper- or hypo-active for socially anxious participants.
The paper tackles the question of what the dynamics of wordplay mean for Early Modern language philosophy and what function wordplay fulfills at a time when linguistic norms and cultural values of a particular language are being sought. In Part 1, the current definition of wordplay suggested in In Part 2, we give a brief sketch of the main features of Early Modern linguistic thought with a particular focus on the concepts of play and wordplay. As one of the language theorists of 17th century Germany, Georg Philipp Harsdrffer (1607-1658) is widely known for the sophisticated integration of these concepts into his "linguistic" oeuvre, and this will determine the main focus of the current article. Two of Harsdrffer's works will be the center of attention: the Frauenzimmer Gesprchspiele (FZG), published 1643-1649 in Nuremberg, an eight-volume series of dialogues about social, poetic and scientific matters, which incorporates much of Harsdrffer's thoughts on language and one of the best-sellers of the 17th century, and the Delitiae Mathematicae et Physicae (DMP), a three-volume scientific work, to which Harsdrffer added the last two of the three volumes (1651( -1653, Nuremberg), Nuremberg). Based on the study of various subtypes of wordplay with letters in Part 3, we shall argue that in the context of baroque linguistic ideas wordplay should be defined in a broader sense. It is deeply rooted in a particular view of language peculiar to European baroque culture that provided a conceptual background not only for language "theories", poetry, education and standards of knowledge but also for the role and functions of wordplay. As Harsdrffer found his inspiration in and was strongly influenced by similar ideas of other scientists, particularly in Italy and France, the results of the analysis of the German baroque sources allow for more general assumptions that are not restricted to one language only.
Despite all the impressive advances of recurrent neural networks, sequential data is still in need of better modelling. Truncated backpropagation through time (TBPTT), the learning algorithm most widely used in practice, suffers from the truncation bias, which drastically limits its ability to learn long-term dependencies.The Real-Time Recurrent Learning algorithm (RTRL) addresses this issue, but its high computational requirements make it infeasible in practice. The Unbiased Online Recurrent Optimization algorithm (UORO) approximates RTRL with a smaller runtime and memory cost, but with the disadvantage of obtaining noisy gradients that also limit its practical applicability. In this paper we propose the Kronecker Factored RTRL (KF-RTRL) algorithm that uses a Kronecker product decomposition to approximate the gradients for a large class of RNNs. We show that KF-RTRL is an unbiased and memory efficient online learning algorithm. Our theoretical analysis shows that, under reasonable assumptions, the noise introduced by our algorithm is not only stable over time but also asymptotically much smaller than the one of the UORO algorithm. We also confirm these theoretical results experimentally. Further, we show empirically that the KF-RTRL algorithm captures long-term dependencies and almost matches the performance of TBPTT on real world tasks by training Recurrent Highway Networks on a synthetic string memorization task and on the Penn TreeBank task, respectively. These results indicate that RTRL based approaches might be a promising future alternative to TBPTT.
Many of the leading approaches in language modeling introduce novel, complex and specialized architectures. We take existing state-of-the-art word level language models based on LSTMs and QRNNs and extend them to both larger vocabularies as well as character-level granularity. When properly tuned, LSTMs and QRNNs achieve state-of-the-art results on character-level (Penn Treebank, enwik8) and word-level (WikiText-103) datasets, respectively. Results are obtained in only 12 hours (WikiText-103) to 2 days (enwik8) using a single modern GPU.
Ambivalence is a common experience that permeates a broad range of research. Unfortunately, quantifying ambivalence has proven a daunting task, with researchers limited to studying vacillating ambivalence, VA (i.e., temporal oscillations between favor/disfavor evaluations of an attitude object). Here, we demonstrate the use of the density matrix to measure both VA and what we term “simultaneous ambivalence” (SA): ambivalence that manifests itself as “in the moment” concurrent favor/disfavor evaluations. In a methodological study we gave participants the option of either single-responding or double-responding to questionnaire items regarding a controversial topic (i.e., affirmative action). Since standard statistical procedures provide no means for analyzing double responses, such data are routinely treated as “bad.” As demonstrated here, the density matrix provides an unambiguous and relatively easy means of accounting for double responses, which is our indicator of SA. Our data are well explained by a mixture model, with participants divided into two nearly equal groups of SA and non-SA participants, and provide evidence that the general phenomenon of SA transcends differences of gender and ethnicity. Further, the density matrix data are consistent with viewing SA and VA as distinct ambivalence constructs.
Up to now, the potential of eye tracking in science as well as in everyday life has not been fully realized because of the high acquisition cost of trackers. Recently, manufacturers have introduced low-cost devices, preparing the way for wider use of this underutilized technology. As soon as scientists show independently of the manufacturers that low-cost devices are accurate enough for application and research, the real advent of eye trackers will have arrived. To facilitate this development, we propose a simple approach for comparing two eye trackers by adopting a method that psychologists have been practicing in diagnostics for decades: correlating constructs to show reliability and validity. In a laboratory study, we ran the newer, low-cost EyeTribe eye tracker and an established SensoMotoric Instruments eye tracker at the same time, positioning one above the other. This design allowed us to directly correlate the eye-tracking metrics of the two devices over time. The experiment was embedded in a research project on memory where 26 participants viewed pictures or words and had to make cognitive judgments afterwards. The outputs of both trackers, that is, the pupil size and point of regard, were highly correlated, as estimated in a mixed effects model. Furthermore, calibration quality explained a substantial amount of individual differences for gaze, but not pupil size. Since data quality is not compromised, we conclude that low-cost eye trackers, in many cases, may be reliable alternatives to established devices.
Crowdsourcing services, such as MTurk, have opened a large pool of participants to researchers. Unfortunately, it can be difficult to confidently acquire a sample that matches a given demographic, psychographic, or behavioral dimension. This problem exists because little information is known about individual participants and because some participants are motivated to misrepresent their identity with the goal of financial reward. Despite the fact that online workers do not typically display a greater than average level of dishonesty, when researchers overtly request that only a certain population take part in an online study, a nontrivial portion misrepresent their identity. In this study, a proposed system is tested that researchers can use to quickly, fairly, and easily screen participants on any dimension. In contrast to an overt request, the reported system results in significantly fewer (near zero) instances of participant misrepresentation. Tests for misrepresentations were conducted by using a large database of past participant records (~45,000 unique workers). This research presents and tests an important tool for the increasingly prevalent practice of online data collection.
This paper focuses on a novel methodology of subjective speech quality measurement and repeatability of its results between laboratory conditions and simulated environmental conditions. A single set of speech samples was distorted by various background noises and low bit-rate coding techniques. This study aimed to compare results of subjective speech quality tests with and without a parallel task deploying the ITU-T P.835 methodology. Afterward, tests results performed with and without a parallel task were compared using Pearson correlation, CI95, and numbers of opposite pair-wise comparisons. The tests show differences in results in the case of a parallel task. [ABSTRACT FROM AUTHOR], Copyright of PLoS ONE is the property of Public Library of Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may)
Introduction: Natural resource management uses expert judgement to estimate facts that inform important decisions. Unfortunately, expert judgement is often derived by informal and largely untested protocols, despite evidence that the quality of judgements can be improved with structured approaches. We attribute the lack of uptake of structured protocols to the dearth of illustrative examples that demonstrate how they can be applied within pressing time and resource constraints, while also improving judgements. Aims and methods: In this paper, we demonstrate how the IDEA protocol for structured expert elicitation may be deployed to overcome operational challenges while improving the quality of judgements. The protocol was applied to the estimation of 14 future abiotic and biotic events on the Great Barrier Reef, Australia. Seventy-six participants with varying levels of expertise related to the Great Barrier Reef were recruited and allocated randomly to eight groups. Each participant)
Sylvia Plath was a very famous American poet, novelist, and short-story writer. Plath became the fi rst poet to win a Pulitzer Prize. Her works are also valuable for their ability to reach contemporary reader, because of its concern with the real problems of contemporary dominant culture. In this age of gender confl icts, broken families, and economic inequities, Plath’s forthright language speaks loudly about the anger of being both betrayed and powerless. Plath’s life and works have been constructed in such a way as to perpetuate specifi c fi ctions about her marriage, mental illness, and “autobiographical” writing, and although this may in part be due to a mythologizing tendency among critics and biographers, it can be demonstrated how Plath fi ctionalizes herself in her writing style. Sylvia Plath was a uniquely troubled individual, whose originality of vision refl ected by her often dark, brooding works. Plath expressed her personal view on a variety of recurring themes, including the obstacles faced by a woman poet, infl uences that shape the self, the allure of death, and several others. The main theme of the writer’s work is the theme of the male suppression of the female identity, forced to obey the patriarchal laws and norms in order to avoid the expulsion from the “paradise” of the male tradition. Plath speaks very clearly a language we can understand. In the novel “The Bell Jar” Sylvia Plath described in detail all the physical and psychological suffering of the main character. The article is devoted to the study of the lexical fi lling of the concept of STRIDING in the individual author’s style.
Over the past century, personality theory and research has successfully identified core sets of characteristics that consistently describe and explain fundamental differences in the way people think, feel and behave. Such characteristics were derived through theory, dictionary analyses, and survey research using explicit self-reports. The availability of social media data spanning millions of users now makes it possible to automatically derive characteristics from behavioral data—language use—at large scale. Taking advantage of linguistic information available through Facebook, we study the process of inferring a new set of potential human traits based on unprompted language use. We subject these new traits to a comprehensive set of evaluations and compare them with a popular five factor model of personality. We find that our language-based trait construct is often more generalizable in that it often predicts non-questionnaire-based outcomes better than questionnaire-based traits (e.g)
Scholarly studies and common accounts of national politics enjoy pointing out the resilience of ideological divides among populations. Building on the image of political cleavages and geographic polarization, the regionalization of politics has become a truism across Northern democracies. Left unquestioned, this geography plays a central role in shaping electoral and referendum campaigns. In Europe and North America, observers identify recurring patterns dividing local populations during national votes. While much research describes those patterns in relation to ethnicity, religious affiliation, historic legacy and party affiliation, current approaches in political research lack the capacity to measure their evolution over time or other vote subsets. This article introduces “Dyadic Agreement Modeling” (DyAM), a transdisciplinary method to assess the evolution of geographic cleavages in vote outcomes by implementing a metric of agreement/disagreement through Network Analysis. Unlike ex)
The Newest Vital Sign (NVS) is a simple, quick and accurate screening test for health literacy (HL). It has been validated for different languages but, to date, not for the Croatian language. The aim of this study was to develop a linguistically validated Croatian version of the NVS and to use it at a later stage in a pilot study of health literacy assessment of hospital patients in Croatia. A full linguistic validation procedure was applied, including forward and backward translation, expert panel review, cognitive interview with 10 respondents from general population, and full involvement in the procedure of one of the screening test developers, the lead author of the NVS-UK version. HL testing on 100 hospital patients (55% women, median age 63.5 years) revealed 58% of patients had less than adequate HL level (scores less than 4), and mean NVS total score was 3.34. A positive significant association was observed between HL and educational level (p = 0.002). A high percentage of pati)
Introduction: Oral Anticoagulation therapy (OAC) is highly effective in the management of thromboembolic disorders. An adequate level of knowledge is important for self-management and optimizing clinical outcomes. The Anticoagulation Knowledge Tool (AKT) was developed to assess OAC knowledge and caters for both patients prescribed direct oral anticoagulants or vitamin K antagonist (VKA). However, evidence regarding its psychometric proprieties, validity and reliability are unavailable in non-English speaking settings. For this reason, the aim of this study is to provide further evidence of validity for AKT and also developing an Italian AKT version (I-AKT) supported by evidence of validity and reliability. Methods: A multiphase study was conducted which included the following: cultural and linguistic validity; i.e. content validity; construct validity; reliability assessment. The Construct validity was performed using the contrasted group approach using three groups comprised of hea)
Background: In practical research, it was found that most people made health-related decisions not based on numerical data but on perceptions. Examples include the perceptions and their corresponding linguistic values of health risks such as, smoking, syringe sharing, eating energy-dense food, drinking sugar-sweetened beverages etc. For the sake of understanding the mechanisms that affect the implementations of health-related interventions, we employ fuzzy variables to quantify linguistic variable in healthcare modeling where we employ an integrated system dynamics and agent-based model. Methodology: In a nonlinear causal-driven simulation environment driven by feedback loops, we mathematically demonstrate how interventions at an aggregate level affect the dynamics of linguistic variables that are captured by fuzzy agents and how interactions among fuzzy agents, at the same time, affect the formation of different clusters(groups) that are targeted by specific interventions. Results:)
Prestige and dominance are thought to be two evolutionarily distinct routes to gaining status and influence in human social hierarchies. Prestige is attained by having specialist knowledge or skills that others wish to learn, whereas dominant individuals use threat or fear to gain influence over others. Previous studies with groups of unacquainted students have found prestige and dominance to be two independent avenues of gaining influence within groups. We tested whether this result extends to naturally-occurring social groups. We ran an experiment with 30 groups of 5 people from Cornwall, UK (n=150). Participants answered general knowledge questions individually and as a group, and subsequently nominated a team representative to answer bonus questions to win money on behalf of the team. Participants then rated all other team-mates anonymously on scales of prestige, dominance, likeability and influence on the task. Using a model comparison approach with Bayesian multi-level models, we found that prestige and dominance ratings were predicted by influence ratings on the task, replicating previous studies. However, prestige and dominance ratings did not predict who was nominated as group representative. Instead, participants nominated team members with the highest individual quiz scores, despite this information being unavailable to them. Interestingly, team members who were initially rated as being high status in the group, such as a team captain or group administrator, had higher ratings of both dominance and prestige than other group members. In contrast, those who were initially rated as someone from whom group members would like to learn had higher prestige ratings, but not higher dominance ratings, supporting the claim that prestige reflects social learning opportunities. Our results suggest that prestige and dominance hierarchies do become established in naturally occurring human social groups, but that these hierarchies may be more domain-specific and less flexible than we anticipated.
Word sense disambiguation (WSD) is the process of identifying an appropriate sense for an ambiguous word. With the complexity of human languages in which a single word could yield different meanings, WSD has been utilized by several domains of interests such as search engines and machine translations. The literature shows a vast number of techniques used for the process of WSD. Recently, researchers have focused on the use of meta-heuristic approaches to identify the best solutions that reflect the best sense. However, the application of meta-heuristic approaches remains limited and thus requires the efficient exploration and exploitation of the problem space. Hence, the current study aims to propose a hybrid meta-heuristic method that consists of particle swarm optimization (PSO) and simulated annealing to find the global best meaning of a given text. Different semantic measures have been utilized in this model as objective functions for the proposed hybrid PSO. These measures consis)
Annotation corpus for discourse relations benefits NLP tasks such as machine translation and question answering. In this paper, we present SciDTB, a domainspecific discourse treebank annotated on scientific articles. Different from widelyused RST-DT and PDTB, SciDTB uses dependency trees to represent discourse structure, which is flexible and simplified to some extent but do not sacrifice structural integrity. We discuss the labeling framework, annotation workflow and some statistics about SciDTB. Furthermore, our treebank is made as a benchmark for evaluating discourse dependency parsers, on which we provide several baselines as fundamental work.
Comprehending natural language quantifiers (like many, all, or some) involves linguistic and numerical abilities. However, the extent to which both factors play a role is controversial. In order to determine the specific contributions of linguistic and number skills in quantifier comprehension, we examined two groups of participants that differ in their language abilities while their number skills appear to be similar: Participants with Down syndrome (DS) and participants with Williams syndrome (WS). Compared to rather poor linguistic skills of individuals with DS, individuals with WS display relatively advanced language abilities. Participants with WS also outperformed participants with DS in a quantifier comprehension task while number knowledge did not differ between the two groups. When compared to typically developing (TD) children of the same mental age, participants with WS displayed similar levels regarding quantifier abilities, but participants with DS performed worse than th)
Understanding the determinants of syntactic choice in sentence production is a salient topic in psycholinguistics. Existing evidence suggests that syntactic choice results from an interplay between linguistic and non-linguistic factors, and a speaker’s attention to the elements of a described event represents one such factor. Whereas multimodal accounts of attention suggest a role for different modalities in this process, existing studies examining attention effects in syntactic choice are primarily based on visual cueing paradigms. Hence, it remains unclear whether attentional effects on syntactic choice are limited to the visual modality or are indeed more general. This issue is addressed by the current study. Native English participants viewed and described line drawings of simple transitive events while their attention was directed to the location of the agent or the patient of the depicted event by means of either an auditory (monaural beep) or a motor (unilateral key press) late)
Most language users agree that some words sound harsh (e.g. grotesque) whereas others sound soft and pleasing (e.g. lagoon). While this prominent feature of human language has always been creatively deployed in art and poetry, it is still largely unknown whether the sound of a word in itself makes any contribution to the word’s meaning as perceived and interpreted by the listener. In a large-scale lexicon analysis, we focused on the affective substrates of words’ meaning (i.e. affective meaning) and words’ sound (i.e. affective sound); both being measured on a two-dimensional space of valence (ranging from pleasant to unpleasant) and arousal (ranging from calm to excited). We tested the hypothesis that the sound of a word possesses affective iconic characteristics that can implicitly influence listeners when evaluating the affective meaning of that word. The results show that a significant portion of the variance in affective meaning ratings of printed words depends on a number of spe)