A Study on Herd Behavior Using Sentiment Analysis in Online Social Network

TL;DR

This paper explores how sentiment analysis of social media data can predict herd behavior and election outcomes, demonstrating the potential of opinion mining in social and political contexts.

Contribution

It evaluates sentiment analysis techniques on social media data to link public opinion with herd behavior and election predictions, offering insights into social dynamics.

Findings

Sentiment analysis can effectively predict election results.

Herd behavior correlates with sentiment and clustering in social networks.

Social media opinions influence large-scale public reactions.

Abstract

Social media platforms are thriving nowadays, so a huge volume of data is produced. As it includes brief and clear statements, millions of people post their thoughts on microblogging sites every day. This paper represents and analyze the capacity of diverse strategies to volumetric, delicate, and social networks to predict critical opinions from online social networking sites. In the exploration of certain searching for relevant, the thoughts of people play a crucial role. Social media becomes a good outlet since the last decades to share the opinions globally. Sentiment analysis as well as opinion mining is a tool that is used to extract the opinions or thoughts of the common public. An occurrence in one place, be it economic, political, or social, may trigger large-scale chain public reaction across many other sites in an increasingly interconnected world. This study demonstrates the evaluation of sentiment analysis techniques using social media contents and creating the association between subjectivity with herd behavior and clustering coefficient as well as tries to predict the election result (2021 election in West Bengal). This is an implementation of sentiment analysis targeted at estimating the results of an upcoming election by assessing the public's opinion across social media. This paper also has a short discussion section on the usefulness of the idea in other fields.