A Hybrid Approach to Generating Adjective Polarity Lexicon and its Application to Turkish Sentiment Analysis

Rahim Dehkharghani, Faculty of Engineering, University of Bonab, Bonab, Iran
2018 International Journal of Modern Education and Computer Science  
Many approaches to sentiment analysis benefit from polarity lexicons. Existing methods proposed for building such lexicons can be grouped into two categories: (1) Lexicon based approaches which use lexicons such as dictionaries and WordNet, and (2) Corpus based approaches which use a large corpus to extract semantic relations among words. Adjectives play an important role in polarity lexicons because they are better polarity estimators compared to other parts of speech. Among natural languages,
more » ... Turkish, similar to other non-English languages suffers from the shortage of polarity resources. In this work, a hybrid approach is proposed for building adjective polarity lexicon, which is experimented on Turkish combines both lexicon based and corpus based methods. The obtained classification accuracies in classifying adjectives as positive, negative, or neutral, range from 71% to 91%. Morphological analysers perform a word-level analysis and provide the root word but parsers provide more information such as the dependency parse tree of a sentence and the POS tag of words according to their context in the sentence.
doi:10.5815/ijmecs.2018.11.02 fatcat:iertseqkhvhkzfo4ogbsh6lqjy