Papers reviewed and determined not to be word norm studies. Use the flag icon to report errors or suggest re-inclusion.
18265 papers
In this paper we present the principles of lexico-semantic annotation of Skadnica Treebank using Polish WordNet lexical units.We describe different means of annotation, depending on the structure of a sentence in Skadnica on the one hand and the availability of adequate lexical unit in PLWN on the other.Apart from "standard" annotation involving lexical units with the same lemma as the token under annotation, multi-word units, different verb lemmas including reflexive marker si as well as synonyms and hypernyms have also been involved.Some tokens have obtained tags explaining why they require no annotation.Additionally, we discuss the assessment of the annotation of whole sentences.
OBJECTIVE: To develop and evaluate an objective image-scoring system for crown-rump length (CRL) measurements and to determine how this compares with subjective assessment. METHODS: A total of 125 CRL ultrasound images were selected from the database of the International Fetal and Newborn Growth Consortium for the 21(st) Century study group. Two reviewers, who were blinded to the operators' and to each others' results, evaluated all images both subjectively and objectively. Subjective evaluation consisted of rating an image as acceptable or unacceptable, while objective evaluation was based on six criteria. Reviewer differences for both the subjective and objective evaluations were compared using percentage of agreement and adjusted kappa values. RESULTS: The distribution of individual scores and differences between subjective and objective evaluation for the two reviewers was similar. Overall agreement between the reviewers was higher for objective evaluation (95.2%; adjusted κ, 0.904), than for subjective evaluation (77.6%; adjusted κ, 0.552). There was a high level of agreement for horizontal position (κ = 0.951), magnification (κ = 0.919), visualization of crown and rump (κ = 0.806) and caliper placement (κ = 0.756), while agreement for mid-sagittal section (κ = 0.629) and neutral position (κ = 0.565) were moderate and poor, respectively. CONCLUSION: The proposed six-point scoring system for CRL image rating is more reproducible than is subjective evaluation and should be considered as a method of quality assessment and audit.
The accuracy of similarity measurement between sentences is critical to the performance of several applications such as text mining, question answering, and text summarization. This paper focuses on calculating semantic similarities between sentences and performing a comparative analysis among identified similarity measurement techniques. Comparison between three popular similarity measurements which are Jaccard, Cosine and Dice similarity measures has been conducted. The performance of each identified measurement was evaluated and recorded. In this paper, we use a large lexical database of English known as WordNet to calculate the word-to-word semantic similarity. The result of this research concludes that the Jaccard and Dice performs better in measuring the semantic similarity between sentences.
Behavioral habituation during repeated exposure to aversive stimuli is an adaptive process. However, the way in which changes in self-reported emotional experience are related to the neural mechanisms supporting habituation remains unclear. We probed these mechanisms by repeatedly presenting negative images to healthy adult participants and recording behavioral and neural responses using functional magnetic resonance imaging. We were particularly interested in investigating patterns of activity in insula, given its significant role in affective integration, and in amygdala, given its association with appraisal of aversive stimuli and its frequent coactivation with insula. We found significant habituation behaviorally along with decreases in amygdala, occipital cortex and ventral prefrontal cortex (PFC) activity with repeated presentation, whereas bilateral posterior insula, dorsolateral PFC and precuneus showed increased activation. Posterior insula activation during image presentation was correlated with greater negative affect ratings for novel presentations of negative images. Further, repeated negative image presentation was associated with increased functional connectivity between left posterior insula and amygdala, and increasing insula-amygdala functional connectivity was correlated with increasing behavioral habituation. These results suggest that habituation is subserved in part by insula-amygdala connectivity and involves a change in the activity of bottom-up affective networks.
We investigated the reappraisal and the time course of negative emotion regulation by performing event-related potential (ERP) recordings. We found that negative pictures elicited more positive P2 and late positivity potential (LPP) deflections than neutral pictures. This effect occurred between 150–2000 ms post-stimulus. Compared to the emotion maintaining condition, the emotion enhancing condition was associated with higher arousal ratings and displayed increased P2 and LPP amplitudes. The decrease condition was also associated with reduced picture-induced arousal; however, it led to increased P2 and LPP amplitudes. Furthermore, when compared with the maintain condition, both the enhancing and decrease conditions significantly enhanced LPP in the early stage (350–750 ms). Compared to previous studies using western subjects, the negative emotion LPP effects of the present study were shorter in duration and the decrease-emotion condition elicited larger LPPs.
Transition-based parsing is a widely used approach for dependency parsing that combines high efficiency with expressive feature models. Many different transition systems have been proposed, often formalized in slightly different frameworks. In this article, we show that a large number of the known systems for projective dependency parsing can be viewed as variants of the same stack-based system with a small set of elementary transitions that can be composed into complex transitions and restricted in different ways. We call these systems divisible transition systems and prove a number of theoretical results about their expressivity and complexity. In particular, we characterize an important subclass called efficient divisible transition systems that parse planar dependency graphs in linear time. We go on to show, first, how this system can be restricted to capture exactly the set of planar dependency trees and, secondly, how the system can be generalized to k-planar trees by making use of multiple stacks. Using the first known efficient test for k-planarity, we investigate the coverage of k-planar trees in available dependency treebanks and find a very good fit for 2-planar trees. We end with an experimental evaluation showing that our 2-planar parser gives significant improvements in parsing accuracy over the corresponding 1-planar and projective parsers for data sets with non-projective dependency trees and performs on a par with the widely used arc-eager pseudo-projective parser.
This paper proposes a discriminative forest reranking algorithm for dependency parsing that can be seen as a form of efficient stacked parsing. A dynamic programming shift-reduce parser produces a packed derivation forest which is then scored by a discriminative reranker, using the 1-best tree output by the shift-reduce parser as guide features in addition to third-order graph-based features. To improve efficiency and accuracy, this paper also proposes a novel shift-reduce parser that eliminates the spurious ambiguity of arc-standard transition systems. Testing on the English Penn Treebank data, forest reranking gave a state-of-the-art unlabeled dependency accuracy of 93.12.
Chinese word segmentation and part-ofspeech tagging (S&T) are fundamental steps for more advanced Chinese language processing tasks.Recently, it has attracted more and more research interests to exploit heterogeneous annotation corpora for Chinese S&T.In this paper, we propose a unified model for Chinese S&T with heterogeneous annotation corpora.We first automatically construct a loose and uncertain mapping between two representative heterogeneous corpora, Penn Chinese Treebank (CTB) and PKU's People's Daily (PPD).Then we regard the Chinese S&T with heterogeneous corpora as two "related" tasks and train our model on two heterogeneous corpora simultaneously.Experiments show that our method can boost the performances of both of the heterogeneous corpora by using the shared information, and achieves significant improvements over the state-of-the-art methods.
This paper investigates the impact of different morphological and lexical information on data-driven dependency parsing of Persian, a morphologically rich language.We explore two state-of-the-art parsers, namely MSTParser and MaltParser, on the recently released Persian dependency treebank and establish some baselines for dependency parsing performance.Three sets of issues are addressed in our experiments: effects of using gold and automatically derived features, finding the best features for the parser, and a suitable way to alleviate the data sparsity problem.The final accuracy is 87.91% and 88.37% labeled attachment scores for Malt-Parser and MSTParser, respectively.
Abstract Given that explicitly realist perspectives are currently quite unfashionable in applied linguistics, we very much welcome your thorough and careful discussion of the various forms they might take. We find the various categories you identify quite persuasive, and we find much to agree with in your characterisation of several of the positions you outline, particularly in the earlier part of the paper. However, we do take issue with aspects of your characterisation of both “social” and “linguistic systems” realism, and with some of the arguments you adduce particularly against the latter and in favour of your seventh way (“linguistic norm circles realism”). Our response, then, concentrates particularly on the challenges arising from these parts of your paper, and addresses: (1) the ways in which we may define language itself, for the purposes of this debate; (2) the distinction between social and linguistic norms; (3) the properties of language; (4) the role of empirical evidence; and (5) the methodological problems we find with the norm circle approach.
International audience
Self-regulatory trainings can be an effective complementary treatment for mental health disorders. We investigated the effects of a six-week-focused meditation training on emotion and attention regulation in undergraduates randomly allocated to a meditation, a relaxation, or a wait-list control group. Assessment comprised a discrimination task that investigates the relationship between attentional load and emotional processing and self-report measures. For emotion regulation, results showed greater reduction in emotional interference in the low attentional load condition in meditators, particularly compared to relaxation. Only meditators presented a significant association between amount of weekly practice and the reduction in emotion interference in the task and significantly reduced image ratings of negative valence and arousal, perceived anxiety and difficulty during the task, and state and trait-anxiety. For attention regulation, response bias during the task was analyzed through signal detection theory. After training, meditation and relaxation significantly reduced bias in the high attentional load condition. Importantly, there was a dose-response effect on general bias: the lowest in meditation, increasing linearly across relaxation and wait-list. Only meditators reduced omissions in a concentrated attention test. Focused meditation seems to be an effective training for emotion and attention regulation and an alternative for treatments in the mental health context.
denne artikel bygger på min forskning i sprogpolitik og sprogpraksis på arbejdspladser i den globaliserede service- og vidensøkonomi, hvor der i stigende grad udøves diverse former for sproglig normering1. i ar-tiklen vil jeg se nærmere på den sproglige normering der finder sted i callcentre og på universiteter, to arbejdspladser som her repræsenterer henholdsvis service- og vidensøkonomien. Selvom den sproglige nor-mering der udøves på callcentre, er mere omfattende og detaljeret end den der foregår på danmarks otte internationaliserede universiteter, er der også en del ligheder. Begge typer af sproglig normering finder fx sted som et forsøg på at løse en række modstridende behov der karakteriserer dagens globaliserede arbejdspladser. i callcentre handler det om behovet for at rationalisere og effektivisere uden at det går ud over kundeservicen, og på universiteterne handler det om at interna-tionalisere uden at det går ud over nationale behov. og i begge typer af institutioner fokuserer man på isproget/i frem for på de underliggende politiske, økonomiske, organisatoriske og pædagogiske faktorer som spændingerne i virkeligheden skyldes. Formålet med artiklen er at sam-menholde forskelle og ligheder mellem den sproglige normering der foregår i disse i øvrigt meget forskellige typer af institutioner for på den måde at opnå en dybere forståelse af begrebet sproglig normering: hvad den består i og hvorfor den finder sted
This study examines verb modes and tenses as well as the predicate structure in «Libro decimosexto» of Bartolomé Jiménez Patón’s Comentarios de erudición in an effort to demonstrate how the text straddles the line between Medieval and Golden Age norms. Jiménez Patón, thus, combines traits already considered archaic at the time, due perhaps to his solid training in grammar and his linguistic awareness, with those modern solutions which, towards the end of the 1500’s, were forging the new Spanish language (that of the «plain style», which he championed), one that was gradually being refined in order to take its place as the language of culture.
Given the enormity of the app market and the velocity with which new apps arrive, it is extremely challenging for apps to reach the intended audience, or any audience at all, in fact. An entire "app promotion" industry exists to help publishers achieve post-launch app success. This is done by understanding relationships between app success and a variety of app attributes (like category, price, etc.). In this paper, we study a dimension not addressed thus far - the timing of app launch. Specifically, we study a large data set to uncover relationships between app launch times and its subsequent commercial success, or lack thereof. A number of interesting findings are revealed in this study. Users are generally less price-sensitive around holiday seasons, especially around Christmas and New Year's, in stark contrast, they are extra price sensitive during weekends. Specifically, more expensive apps released on weekends tend to get a higher negative word-of-mouth (review valence) rating. In addition, our results indicate that apps released in the latter part of the week tend to fare better than do apps released earlier. Furthermore, Thursday is the optimal day to release an app when considering review sentiments. Finally, it does tend to get a higher number of reviews on weekends.
This paper tries to give answers for successful receptive multilingualism (RM) but also for its failure. It is mainly based on the results of two projects, one on inter-dialectal communication in the Baltic area during the era of the Hanseatic League and the other analyses inter-Scandinavian communication today. The main purpose of this survey is to outline the essential preconditions for successful RM, from a linguistic, social and environmental perspective. The historical project about communication in the Baltic focuses on long-term language contact based on common mutual trading interests whilst the contemporary project highlights the cultural factors (among others Pan-Scandinavism) as a common basis for using one's own mother tongue in transnational communication. Moreover, other relevant issues belonging to successful RM are touched upon, such as diglossia (i.e. the functional distribution of different languages/varieties in various settings), oral face-to-face communication, the absence of written norms and the non-existence of standardised forms, which result not only in a greater flexibility in communication but also support openness for divergent varieties. Disfavouring factors for RM are, however, taken into consideration as well, such as nationalism and the suppression of minorities (and thus indirectly multilingualism), the enforcement of strict linguistic norms by the society and finally the use of a lingua franca such as Latin in the Middle Ages or English today.
ABSTRACT The aim of this article is to carry out a structural-functional analysis of the formation of Old English adjectives by means of affixation. By analysing the rules and operations that produce the 3,356 adjectives which the lexical database of Old English Nerthus (www.nerthusproject.com) turns out as affixal derivatives, a total of fourteen derivational functions have been identified. Additionally, the analysis yields conclusions concerning the relationship between affixes and derivational functions, the patterns of recategorization present in adjective formation and recursive word-formation.
This paper has two main objectives. The first is to provide an overview of the CDT annotation design with special emphasis on the modeling of the interface between syntactic and morphological structure. Against this background, the second objective is to explain the basic fundamentals of how CDT is marked-up with semantic relations in accordance with the dependency principles governing the annotation on the other levels of CDT. Specifically, focus will be on how Generative Lexicon theory has been incorporated into the unitary theoretical dependency framework of CDT by developing an annotation scheme for lexical semantics which is able to account for the lexico-semantic structure of complex NPs.
There is a substantial body of recent evidence showing ergogenic effects of carbohydrate (CHO) mouth rinsing on endurance performance. However, there is a lack of research on the dose-effect and the aim of this study was to investigate the effect of two different concentrations (6% and 12% weight/volume, w/v) on 90 minute treadmill running performance. Seven active males took part in one familiarization trial and three experimental trials (90-minute self-paced performance trials). Solutions (placebo, 6% or 12% CHO-electrolyte solution, CHO-E) were rinsed in the mouth at the beginning, and at 15, 30 and 45 minutes during the run. The total distance covered was greater during the CHO-E trials (6%, 14.6 ± 1.7 km; 12%, 14.9 ± 1.6 km) compared to the placebo trial (13.9 ± 1.7 km, P < 0.05). There was no significant difference between the 6% and 12% trials (P > 0.05). There were no between trial differences (P > 0.05) in ratings of perceived exertion (RPE) and feeling or arousal ratings suggesting that the same subjective ratings were associated with higher speeds in the CHO-E trials. Enhanced performance in the CHO-E trials was due to higher speeds in the last 30 minutes even though rinses were not provided during the final 45 minutes, suggesting the effects persist for at least 20-45 minutes after rinsing. In conclusion, mouth rinsing with a CHO-E solution enhanced endurance running performance but there does not appear to be a dose-response effect with the higher concentration (12%) compared to a standard 6% solution.
This article presents a new approach of us-ing dependency treebanks in theoretical syn-tactic research: the view of dependency treebanks as combined networks. This al-lows the usage of advanced tools for net-work analysis that quite easily provide novel insight into the syntactic structure of lan-guage. As an example of this approach, we will show how the network approach can provide clear structural distinctions among the Chinese function words, which are very difficult to obtain directly from the original treebank. We hope to illustrate the enor-mous potential of the language network ap-
The perception of emotional cues from voice and face is essential for social interaction. However, this process is altered in various psychiatric conditions along with impaired social functioning. Emotion communication trainings have been demonstrated to improve social interaction in healthy individuals and to reduce emotional communication deficits in psychiatric patients. Here, we investigated the impact of a non-verbal emotion communication training (NECT) on cerebral activation and brain structure in a controlled and combined functional magnetic resonance imaging (fMRI) and voxel-based morphometry study. NECT-specific reductions in brain activity occurred in a distributed set of brain regions including face and voice processing regions as well as emotion processing- and motor-related regions presumably reflecting training-induced familiarization with the evaluation of face/voice stimuli. Training-induced changes in non-verbal emotion sensitivity at the behavioral level and the respective cerebral activation patterns were correlated in the face-selective cortical areas in the posterior superior temporal sulcus and fusiform gyrus for valence ratings and in the temporal pole, lateral prefrontal cortex and midbrain/thalamus for the response times. A NECT-induced increase in gray matter (GM) volume was observed in the fusiform face area. Thus, NECT induces both functional and structural plasticity in the face processing system as well as functional plasticity in the emotion perception and evaluation system. We propose that functional alterations are presumably related to changes in sensory tuning in the decoding of emotional expressions. Taken together, these findings highlight that the present experimental design may serve as a valuable tool to investigate the altered behavioral and neuronal processing of emotional cues in psychiatric disorders as well as the impact of therapeutic interventions on brain function and structure.
Moral decision-making is a key asset for humans' integration in social contexts, and the way we decide about moral issues seems to be strongly influenced by emotions. For example, individuals with deficits in emotional processing tend to deliver more utilitarian choices (accepting an emotionally aversive action in favor of communitarian well-being). However, little is known about the association between emotional experience and moral-related patterns of choice. We investigated whether subjective reactivity to emotional stimuli, in terms of valence, arousal, and dominance, is associated with moral decision-making in 95 healthy adults. They answered to a set of moral and non-moral dilemmas and assessed emotional experience in valence, arousal and dominance dimensions in response to neutral, pleasant, unpleasant non-moral, and unpleasant moral pictures. Results showed significant correlations between less unpleasantness to negative stimuli, more pleasantness to positive stimuli and higher proportion of utilitarian choices. We also found a positive association between higher arousal ratings to negative moral laden pictures and more utilitarian choices. Low dominance was associated with greater perceived difficulty over moral judgment. These behavioral results are in fitting with the proposed role of emotional experience in moral choice.
The linguistic annotation of noun-verb complex predicates (also termed as light verb constructions) is challenging as these predicates are highly productive in Hindi. For semantic role labelling, each argument of the noun-verb complex predicate must be given a role label. For complex predicates, frame files need to be created specifying the role labels for each noun-verb complex predicate. The creation of frame files is usually done manually, but we propose an automatic method to expedite this process. We use two resources for this method: Hindi PropBank frame files for simple verbs and the annotated Hindi Treebank. Our method perfectly predicts 65 % of the roles in 3015 unique noun-verb combinations, with an additional 22 % partial predictions, giving us 87 % useful predictions to build our annotation resource. 1
We present an idiographic approach to modeling dyadic interactions using differential equations. Using data representing daily affect ratings from romantic relationships, we examined several models conceptualizing different types of dyadic interactions. We fitted each model to each of the dyads and the resulting AICc values were used to classify the most likely configuration of interaction for each dyad. Additionally, the AICc from the different models were used in parameter averaging across models. Averaged parameters were used in models involving predictors of relationship dynamics, as indexed by these parameters, as well as models wherein the parameters predicted distal outcomes of the dyads such as relationship satisfaction and status. Results indicated that, within our sample, the most likely interaction style was that of independence, without evidence of emotional interrelations between the two individuals in the couple. Attachment-related avoidance and anxiety showed significant relations with model parameters, such that ideal levels of affect for males were negatively influenced by higher levels of avoidance from their partner while their own levels of anxiety had positive effects on their levels of dyadic coregulation. For females coregulation was negatively influenced by both time in the relationship and their partner's level of avoidance. Analysis involving distal outcomes showed modest influences from the individual's level of ideal affect.
ABSTRACT This paper takes issue with the lexicon of Old English and, more specifically, with the existence of closing suffixes in word-formation. Closing suffixes are defined as base suffixes that prevent further suffixation by word-forming suffixes (Aronoff & Furhop 2002: 455). This is tantamount to saying that this is a study in recursivity, or the formation of derivatives from derived bases, as in anti-establish-ment, which requires the attachment of the prefix anti- to the derived input establishment. The present analysis comprises all major lexical categories, that is, nouns, adjectives, verbs and adverbs and concentrates on suffixes because they represent the newest and the most productive process in Old English word-formation (Kastovsky 1992, 2006), as well as the set of morphemes that has survived into Present-day English without undergoing radical changes. Given this aim, the data retrieved from the lexical database of Old English Nerthus (www.nerthusproject.com) comprise 6,073 affixed (prefixed and suffixed) derivatives, including 3,008 nouns, 1,961 adjectives, 974 adverbs and 130 verbs. All of them have been analysed in order to isolate recursive formations.
This paper studies the performance of different parsers over a large Spanish treebank. The aim of this work is to assess the limitations of state-of-the-art parsers. We want to select the most appropriate parser for subcategorization Frame acquisition, and we focus our analysis on two aspects: the accuracy drop when parsing out-of-domain data, and the performance over specific labels relevant to our task.
In this study of serious verse drama (tragedies and history plays) by Shakespeare and his contemporaries of the late Elizabethan and early Jacobean periods, language is seen as a resource for achieving immediacy or distance, situating the play either in a contemporary socio-political framework or else in a national-historical past. The empirical basis for this claim lies in a study of archaic versus innovative syntactic constructions. It is shown that in the early 1590s Shakespeare and his contemporaries made very frequent use of verb-second in declaratives, and tended to avoiddo-support in interrogatives. In early Jacobean serious drama, however, "verb-second" had almost disappeared anddo-support rose to around 50% of interrogative contexts. Whereas in the earlier period an archaic effect was created by retaining Middle English constructions that ordinary usage had by now either abandoned, or was in the process of doing so, the language of Jacobean serious drama aligned itself on the respective ambient linguistic norms. It is argued that these syntactic preferences conveyed a stylistic effect suitable for representing distance and/or alterity, either with respect to the past or to a foreign context: both perspectives involved late Elizabethan national identity concerns. Conversely, the adoption of contemporary linguistic norms in Jacobean high drama achieved an effect of proximity, facilitating "here-and-now" allusiveness to contemporary themes, especially those of court intrigue and cynical acquisitive materialism.
It is well-known that emotionally salient events are remembered more vividly than mundane ones. Our recent research has demonstrated that such memory vividness (Mviv) is due in part to the subjective experience of emotional events as more perceptually vivid, an effect we call emotionally enhanced vividness (EEV). The present study built on previously reported research in which fMRI data were collected while participants rated relative levels of visual noise overlaid on emotionally salient and neutral images. Ratings of greater EEV were associated with greater activation in the amygdala and visual cortex. In the present study, we measured BOLD activation that predicted recognition Mviv for these same images 1 week later. Results showed that, after controlling for differences between scenes in low-level objective features, hippocampus activation uniquely predicted subsequent Mviv. In contrast, amygdala and visual cortex regions that were sensitive to EEV were also modulated by subsequent ratings of Mviv. These findings suggest shared neural substrates for the influence of emotional salience on perceptual and mnemonic vividness, with amygdala and visual cortex activation at encoding contributing to the experience of both perception and subsequent memory.
Abstract Jewish history in Kerala, the southernmost state in modern India, goes back to as early as the tenth century CE. In the mid-twentieth century, Kerala Jews migrated en masse to Israel, leaving behind but a handful of their community members and remnants of eight communities, synagogues, and cemeteries. The paper presents a preliminary attempt to describe and analyze the language—so far left undocumented and unexplored—still spoken by Kerala Jews in Israel, based on a language documentation project carried out in 2008 and 2009. In light of the data collected and studied so far, it is clear that the language in question fits nicely into the Jewish languages spectrum, while at the same time it fits perfectly into the linguistic mosaic of castolects in Kerala. Though the linguistic database described here reflects a language in its last stages, it affords salvaging the remnants of a once rich oral heritage and opens new channels for the study of the history, society, and culture of Kerala Jews.
This paper is concerned with the problem of heterogeneous dependency parsing. In this paper, we present a novel joint inference scheme, which is able to leverage the consensus information between heterogeneous treebanks in the parsing phase. Different from stacked learning methods (Nivre and McDonald, 2008; Martins et al., 2008), which process the dependency parsing in a pipelined way (e.g., a second level uses the first level outputs), in our method, multiple dependency parsing models are coordinated to exchange consensus information. We conduct experiments on Chinese Dependency Treebank (CDT) and Penn Chinese Treebank (CTB), experimental results show that joint inference can bring significant improvements to all state-of-the-art dependency parsers. 1
Padayachee examines developments in the culture and practice of corporate governance largely within the private sector in South Africa. His analysis reveals the dominance of powerful individuals, family trusts and groups sharing common social, cultural, and linguistic norms, bound together outside the boardrooms thorough old school, club, societal, political, church, sports and other such networks. A sound corporate governance culture based on transparency and disclosure hardly existed before and during the apartheid era. Since 1994 and as South Africa opened up to global economic circuits and institutional rules and practices, there has been a much stronger commitment, at least nominally, to compliance with developments in global corporate governance. The King codes of corporate governance (now into version 3) are the strongest indication of this. South African companies have over the last 18 years shifted from an initial state (a management controlled, 'social club' approach to corporate governance) towards an Anglo-American corporate governance model, practising what is widely referred to as 'shareholder wealth maximization'. But Padayachee argues that the practice of this approach remains uneven, as large family networks (both old and new) still exercise significant influences in boardrooms.
It was repeatedly demonstrated that a negative emotional context enhances memory for central details while impairing memory for peripheral information. This trade-off effect is assumed to result from attentional processes: a negative context seems to narrow attention to central information at the expense of more peripheral details, thus causing the differential effects in memory. However, this explanation has rarely been tested and previous findings were partly inconclusive. For the present experiment 13 negative and 13 neutral naturalistic, thematically driven picture stories were constructed to test the trade-off effect in an ecologically more valid setting as compared to previous studies. During an incidental encoding phase, eye movements were recorded as an index of overt attention. In a subsequent recognition phase, memory for central and peripheral details occurring in the picture stories was tested. Explicit affective ratings and autonomic responses validated the induction of emotion during encoding. Consistent with the emotional trade-off effect on memory, encoding context differentially affected recognition of central and peripheral details. However, contrary to the common assumption, the emotional trade-off effect on memory was not mediated by attentional processes. By contrast, results suggest that the relevance of attentional processing for later recognition memory depends on the centrality of information and the emotional context but not their interaction. Thus, central information was remembered well even when fixated very briefly whereas memory for peripheral information depended more on overt attention at encoding. Moreover, the influence of overt attention on memory for central and peripheral details seems to be much lower for an arousing as compared to a neutral context.
This paper analyzes the subjects/modules which presumably contribute to develop the communicative competence in Level C1 from the students of Primary Education Degree. So, taking as a starting point their course descriptions, we will check to what extend they reflect the communicative competence concept set by the CEFR and the teaching of linguistic norm.
We explored the influence of implicit motives and activity inhibition (AI) on subjectively experienced affect in response to the presentation of six different facial expressions of emotion (FEEs; anger, disgust, fear, happiness, sadness, and surprise) and neutral faces from the NimStim set of facial expressions (Tottenham et al., 2009). Implicit motives and AI were assessed using a Picture Story Exercise (PSE) (Schultheiss et al., 2009b). Ratings of subjectively experienced affect (arousal and valence) were assessed using Self-Assessment Manikins (SAM) (Bradley and Lang, 1994) in a sample of 84 participants. We found that people with either a strong implicit power or achievement motive experienced stronger arousal, while people with a strong affiliation motive experienced less arousal and less pleasurable affect across emotions. Additionally, we obtained significant power motive × AI interactions for arousal ratings in response to FEEs and neutral faces. Participants with a strong power motive and weak AI experienced stronger arousal after the presentation of neutral faces but no additional increase in arousal after the presentation of FEEs. Participants with a strong power motive and strong AI (inhibited power motive) did not feel aroused by neutral faces. However, their arousal increased in response to all FEEs with the exception of happy faces, for which their subjective arousal decreased. These differentiated reaction patterns of individuals with an inhibited power motive suggest that they engage in a more socially adaptive manner of responding to different FEEs. Our findings extend established links between implicit motives and affective processes found at the procedural level to declarative reactions to FEEs. Implications are discussed with respect to dual-process models of motivation and research in motive congruence.
A major computational burden, while performing document clustering, is the calculation of similarity measure between a pair of documents. Similarity measure is a function that assigns a real number between 0 and 1 to a pair of documents, depending upon the degree of similarity between them. A value of zero means that the documents are completely dissimilar whereas a value of one indicates that the documents are practically identical. Traditionally, vector-based models have been used for computing the document similarity. The vector-based models represent several features present in documents. These approaches to similarity measures, in general, cannot account for the semantics of the document. Documents written in human languages contain contexts and the words used to describe these contexts are generally semantically related. Motivated by this fact, many researchers have proposed seman-tic-based similarity measures by utilizing text annotation through external thesauruses like WordNet (a lexical database). In this paper, we define a semantic similarity measure based on documents represented in topic maps. Topic maps are rapidly becoming an industrial standard for knowledge representation with a focus for later search and extraction. The documents are transformed into a topic map based coded knowledge and the similarity between a pair of documents is represented as a correlation between the common patterns (sub-trees). The experimental studies on the text mining datasets reveal that this new similarity measure is more effective as compared to commonly used similarity measures in text clustering.
Tree substitution grammar (TSG) is a generalization of context-free grammar (CFG) that permits non-terminals to rewrite as fragments of arbitrary size, instead of just depth-one productions. We discuss connections between the TSG framework and the larger family of usage-based approaches to language, showing how TSG allows us to make some of the claims of these approaches sufficiently concrete for computational modeling. A fundamental difficulty in defining a TSG is to determine the set of fragments for the grammar, because the set of possible fragments is exponential in the size of the parse trees from which TSGs are typically learned. We describe a model-based approach that learns a TSG using Gibbs sampling with a non-parametric prior to control fragment size, yielding grammars that contain mostly small fragments but that include larger ones. as the data permits. We evaluate these grammars on two tasks (parsing accuracy and grammaticality classification), and find that these Bayesian TSGs achieve excellent performance on two tasks relative to a set of heuristically extracted TSGs spanning the spectrum of representations, from a standard depth-one context-free Treebank grammar to explicit approximations of the Data-Oriented Parsing model.
In a large scale study on 843 transcripts of Technology, Entertainment and Design (TED) talks, the authors address the relation between word usage and categorical affective ratings of lectures by a large group of internet users. Users rated the lectures by assigning one or more predefined tags which relate to the affective state evoked in the audience (e. g., ‘fascinating’, ‘funny’, ‘courageous’, ‘unconvincing’ or ‘long-winded’). By automatic classification experiments, they demonstrate the usefulness of linguistic features for predicting these subjective ratings. Extensive test runs are conducted to assess the influence of the classifier and feature selection, and individual linguistic features are evaluated with respect to their discriminative power. In the result, classification whether the frequency of a given tag is higher than on average can be performed most robustly for tags associated with positive valence, reaching up to 80.7% accuracy on unseen test data.
Today, more than ten years after the resolution of the language controversy on a state level, it is far from resolved in the scholarly or the public sphere, where representatives of the two countries continue to debate the question of how distinct Macedonian is from Bulgarian. This chapter explains why this question is so hotly debated and so politicized. It deals with the process of codification of the contemporary Macedonian linguistic norm and with the conflicts between Bulgarians and Macedonians about the definition both of the Slavic vernacular dialects in geographic Macedonia and of the Macedonian norm itself. The chapter argues that the codification of the contemporary Macedonian idiom cannot be understood without examining a larger international context. Finally, it shows how the codification of a separate Macedonian norm has shaped Bulgarian nationalist representations-especially in the field of linguistics. Keywords:Bulgarian; Macedonian linguistic norm; Slavic vernacular dialects
The aim of the article is to identify the exponent for the semantic prime TOUCH in Old English. Therefore, this research contributes to the frame of the Natural Semantic Metalanguage Research Programme (NSMRP) by applying it to the study of a historical language. Throughout such an application several descriptive and methodological questions arise. On the descriptive side, it is necessary to propose a cluster of semantic, morphological, textual and syntactic criteria that allow for the identification of the prime at stake, given that the nature of the object of study is not compatible with the translation into the native language generally adopted by the NSMRP. The analysis focuses on the category actions, events, movement and contact, and relies on data retrieved from the Historical Thesaurus of the Oxford English Dictionary, the Dictionary of Old English Corpus and the lexical database of Old English Nerthus. Although the cluster of criteria evinces a clear candidate for semantic prime it also raises the methodological issue of the distinction between the semantic prime and the hyperonym because some of the criteria used in the search for the former also play a role in the process of identification of the latter. The conclusion is reached that the verb hrīnan is the main exponent for the semantic prime TOUCH in Old English because it satisfies the criteria of meaning, word-formation, textual frequency and syntactic complementation.
Abstract. Recent research and development have created the necessary ingredients for a major push in web-scale language understanding: large repositories of structured knowledge (DBpedia, the Google knowledge graph, Freebase, YAGO) progress in language processing (parsing, information extraction, computational semantics), linguistic knowledge resources (Treebanks, WordNet, BabelNet, UWN) and new powerful techniques for machine learning. A major goal is the automatic aggregation of knowledge from textual data. A central component of this endeavor is relation extraction (RE). In this paper, we will outline a new approach to connecting repositories of world knowledge with linguistic knowledge (syntactic and lexical semantics) via web-scale relation extraction technologies.
Morphology is the study of internal structure of words and is an essential early step in many NLP applications such as parsing and machine translation. Researchers working in Hindi NLP have either used the widely popular paradigm based analyzer (PBA) or extensions of it. In this work, we undertook a comprehensive evaluation of PBA using the data from the Hindi Treebank (HTB) and presented a new morphological analyzer trained on the HTB. Our morphological analyzer has better coverage and accuracy when compared to the existing analyzers for Hindi. An oracle system that takes the best values from the PBA’s output achieves only 63.41% for lemma, gender, number, person and case. Our statistical analyzer has an accuracy of 84.16% for these morphological attributes when evaluated on the test section of the Hindi Treebank.
This paper describes our submission for SemEval2013 Task 2: Sentiment Analysis in Twitter. For the limited data condition we use a lexicon-based model. The model uses an affective lexicon automaticallygeneratedfrom a very large corpus of raw web data. Statistics are calculated over the word and bigram affective ratings and used as features of a Naive Bayes tree model. For the unconstrained data scenario we combine the lexicon-based model with a classifier built on maximum entropy language models and trained on a large external dataset. The two models are fused at the posterior level to produce a final output. The approach proved successful, reaching rankings of 9th and 4th in the twitter sentiment analysis constrained and unconstrained scenario respectively, despite using only lexical features.
We present a comparative study of transition-, graph- and PCFG-based models aimed at illuminating more precisely the likely contribution of CFGs in improving Chinese dependency parsing accuracy, especially by combining heterogeneous models. Inspired by the impact of a constituency grammar on dependency parsing, we propose several strategies to acquire pseudo CFGs only from dependency annotations. Compared to linguistic grammars learned from rich phrase-structure treebanks, well designed pseudo grammars achieve similar parsing accuracy and have equivalent contributions to parser ensemble. Moreover, pseudo grammars increase the diversity of base models; therefore, together with all other models, further improve system combination. Based on automatic POS tagging, our final model achieves a UAS of 87.23%, resulting in a significant improvement of the state of the art.
For years observational techniques along with other methods have sought to explore the relationships of couple interactional exchanges to marital quality and longevity. However, many of the previous methodological procedures used might be inadequate at capturing the influential micro-dimensional nuances of interpartner couple affective stability and reciprocity. This study explored the dyadic patterns in 23 married couples' continuous affect ratings during two communication episodes. Multilevel modeling was used to assess the structure in the stability of one's own affect and the influence of partner affect over 3-, 6-, and 9-second time lags. Implications regarding the use of nested models to explore patterns of actor and partner effects are discussed.
At present, discourse parsing is an important research topic. Rhetorical Structure Theory (RST) is one of the most popular approaches in this field. In general, discourse parsing includes three stages: discourse segmentation, discourse relations detection and building up rhetorical trees. Different strategies are used when developing discourse parsers. One of the strategies to detect discourse relations is based on symbolic rules that take into account linguistic clues, such as discourse markers. Nevertheless, some discourse markers are ambiguous, that is, they can indicate more than one discourse relation. This fact constitutes a problem when assigning discourse relations automatically. In this paper, a symbolic approach to detect and solve discourse markers ambiguity in Spanish is developed. First, we detect ambiguous discourse markers, using the training corpus of the RST Spanish Treebank. Second, we extract linguistic contexts for these markers. Third, we design linguistic rules to solve the ambiguity of discourse markers. Fourth, we evaluate the rules, using the test corpus of the RST Spanish Treebank. Our approach outperforms the baseline created following the methodology of the state of the art. Therefore, we consider that the results obtained in our experiments are representative and constitute the first step towards the disambiguation of discourse markers senses in Spanish. However, there is room for improvement and the main limitations of the approach are presented. In the future, the rules will be integrated in a discourse parser for Spanish, and several related applications will be developed (automatic summarization and information extraction, among others).