Corpus-Based Techniques for Sentiment Lexicon Generation: A Review-

Title Corpus-Based Techniques for Sentiment Lexicon Generation: A Review-
Publication TypeJournal Article
Year of Publication2019
AuthorsDarwich, M, Noah, SAzman Mohd, Omar, N, Osman, NAida
JournalJournal of Digital Information Management
Volume17
Issue5
Start Page296
Pagination296-305
Date Published10/2019
Type of ArticleResearch
Abstract

State-of-the-art sentiment analysis systems rely on a sentiment lexicon, which is the most essential feature that drives their performance. This resource is indispensable for, and greatly contributes to, sentiment analysis tasks. This is evident in the emergence of a large volume of research devoted to the development of automated sentiment lexicon generation algorithms. The task of tagging subjective words with a semantic orientation comprises two core approaches: dictionarybased and corpus-based. The former involves making use of an online dictionary to tag words, while the latter relies on co-occurrence statistics or syntactic patterns embedded in text corpora. The end result is a linguistic resource comprising a priori information about words, across the semantic dimension of sentiment. This paper provides a survey on the most prominent research works that utilize corpus-based techniques for sentiment lexicon generation. We also conduct a comparative analysis on the performance of state-of-the-art algorithms proposed for this task, and shed light on the current progress and challenges in this area.

URLhttp://dline.info/fpaper/jdim/v17i5/jdimv17i5_4.pdf
DOI10.6025/jdim/2019/17/5/296-305
Refereed DesignationRefereed

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