There exist distinctive words that are used to express same semantics and as a result of this it has become hard to quantify the exact matching of words. To deal with this issue, past investigations endeavored to ascertain a likeness between distinctive pair of words. Conventional methodologies for computing word similarity are based on repositories like WordNet. It is a manually created lexical database and it processes semantic connection between various words. However, WordNet is a universally useful asset but wide range of words are not present in it and furthermore there exist an issue of identifying the meaning of words. Implication of words are diverse in WordNet when we utilize it in a textual framework. There exists a need of the refined approach that can gauge words resemblance in light of their co-occurrence. In this examination, we proposed an approach that registers likeness in text particular words, with the assistance of literary substance of various posts on StackOverflow. Our proposed strategy figures out word similarities in text by ascertaining the weighted co-occurrence in view of Computing Term Cooccurrence (CTC) and SentiWordNet. The exploratory outcome demonstrates that our system proposed an arrangement of words that are identified with text data is exceptional. Moreover, when it was compared with WordNet-based strategy named as WordNetres, it results with better outcomes.