TY  - EJOU
AU  - Saraswathy, Kumari Sheeja 
AU  - Devi, Sobha Lalitha 

TI  - Enhancement of Sentiment Analysis Using Clause and Discourse Connectives
T2  - Computers, Materials \& Continua

PY  - 2021
VL  - 68
IS  - 2
SN  - 1546-2226

AB  - The sentiment of a text depends on the clausal structure of the sentence and the connectives’ discourse arguments. In this work, the clause boundary, discourse argument, and syntactic and semantic information of the sentence are used to assign the text’s sentiment. The clause boundaries identify the span of the text, and the discourse connectives identify the arguments. Since the lexicon-based analysis of traditional sentiment analysis gives the wrong sentiment of the sentence, a deeper-level semantic analysis is required for the correct analysis of sentiments. Hence, in this study, explicit connectives in Malayalam are considered to identify the discourse arguments. A supervised method, conditional random fields, is used to identify the clause boundary and discourse arguments. For the study, 1,000 sentiment sentences from  Malayalam documents were analyzed. Experimental results show that the discourse structure integration considerably improves sentiment analysis performance from the baseline system.
KW  - Natural language processing; artificial intelligence; sentiment analysis; computational linguistics; opinion mining; machine learning; information extraction; supervised learning

DO  - 10.32604/cmc.2021.015661