Empirical study of sentiment analysis tools and techniques on societal topics

作者:Loitongbam Gyanendro Singh, Sanasam Ranbir Singh

摘要

A surge in public opinions mining against various societal topics using publicly available off-the-shelf sentiment analysis tools is evident in recent times. Since sentiment analysis is a domain-dependent problem, and the majority of the tools are built for customer reviews, the suitability of using such existing off-the-the-shelf tools for a societal topic is subject to investigation. None of the existing studies has thoroughly investigated on societal issues. This paper systematically evaluates the performance of 10 popularly used off-the-shelf tools and 17 state-of-the-art machine learning techniques and investigates their strengths and weaknesses using various societal and non-societal topics.

论文关键词:Sentiment analysis, Societal topics, Publicly available sentiment analysis tools, Machine learning techniques

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论文官网地址:https://doi.org/10.1007/s10844-020-00616-7