Investigations on sentiment mining are mostly ensued in the English language. Due to the characteristics of the Indian languages tools and techniques used for sentiment mining in the English langua...

This chapter presented an analysis of the application of lexicon-based political sentiment analysis in social media. The aim is to identify the most frequently used lexicons in political sentiment analysis, their results, similarities, and differences. For this, the authors conducted a systematic literature review based on PRISMA methodology. Afinn, NRC, and SenticNet lexicons are tested and combined for data analysis from the 2020 U.S. presidential campaign. Findings show that political sentiment analysis is a new field studied for only 10 years. Political sentiment analysis could generate benefits in understanding problems such as political polarization, discourse analysis, politician influence, candidate profiling, and improving government-citizen interaction, among other problems in the public sphere, enhanced by the combination of lexicons and multimodal analysis. The authors conclude that polarity was one of the critical dimensions identified for finding variations in the behavior and polarity of sentiments. Limitations and future work also are presented. 

Political Sentiment Mining: A New Age Intelligence Tool for Business Strategy Formulation

Review on the Application of Lexicon-Based Political Sentiment Analysis in Social Media

This chapter addresses the question whether opinion-mining techniques can successfully be used to automatically retrieve political viewpoints from parliamentary proceedings. Two specific preprocessing tasks were identified and systematically evaluated: automatically determining subjectivity in the publications and automatically determining the semantic orientation of the subjective parts. A corpus of recent parliamentary proceedings was collected and a gold standard annotation was created on both subjectivity and orientation. Following this, a number of models based on subjectivity lexicons and machine-learning algorithms were evaluated. Machine-learning algorithms perform best, but methods based on subjectivity lexicons also provide promising results. Based on these results we can conclude that opinion-mining techniques applied to political data score just as well as the state of the art in other more traditional domains of opinion mining like product reviews and blogs.

Political Sentiment Mining: A New Age Intelligence Tool for Business Strategy Formulation

Citations

Review on the Application of Lexicon-Based Political Sentiment Analysis in Social Media

References

Sentiment Analysis in Parliamentary Proceedings

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