The emergence of social media data and sentiment analysis in election prediction

被引:0
作者
Priyavrat Chauhan
Nonita Sharma
Geeta Sikka
机构
[1] Dr B R Ambedkar National Institute of Technology,Department of Computer Science and Engineering
来源
Journal of Ambient Intelligence and Humanized Computing | 2021年 / 12卷
关键词
Sentiment analysis; Opinion mining; Election prediction; Social media; Twitter;
D O I
暂无
中图分类号
学科分类号
摘要
This work presents and assesses the power of various volumetric, sentiment, and social network approaches to predict crucial decisions from online social media platforms. The views of individuals play a vital role in the discovery of some critical decisions. Social media has become a well-known platform for voicing the feelings of the general population around the globe for almost decades. Sentiment analysis or opinion mining is a method that is used to mine the general population’s views or feelings. In this respect, the forecasting of election results is an application of sentiment analysis aimed at predicting the outcomes of an ongoing election by gauging the mood of the public through social media. This survey paper outlines the evaluation of sentiment analysis techniques and tries to edify the contribution of the researchers to predict election results through social media content. This paper also gives a review of studies that tried to infer the political stance of online users using social media platforms such as Facebook and Twitter. Besides, this paper highlights the research challenges associated with predicting election results and open issues related to sentiment analysis. Further, this paper also suggests some future directions in respective election prediction using social media content.
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页码:2601 / 2627
页数:26
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