Detecting Group Beliefs Related to 2018's Brazilian Elections in Tweets A Combined Study on Modeling Topics and Sentiment Analysis

TL;DR

This paper analyzes Twitter discussions during the 2018 Brazilian elections to understand how group beliefs are reinforced through topic modeling and sentiment analysis, revealing passionate engagement aligned with shared political opinions.

Contribution

It combines topic modeling and sentiment analysis on Twitter data to study political discourse and belief reinforcement during a major election.

Findings

Passionate discourses are prevalent in digital political discussions.

Group beliefs are reinforced through similar opinions expressed in tweets.

Social media engagement correlates with shared political sentiments.

Abstract

2018's Brazilian presidential elections highlighted the influence of alternative media and social networks, such as Twitter. In this work, we perform an analysis covering politically motivated discourses related to the second round in Brazilian elections. In order to verify whether similar discourses reinforce group engagement to personal beliefs, we collected a set of tweets related to political hashtags at that moment. To this end, we have used a combination of topic modeling approach with opinion mining techniques to analyze the motivated political discourses. Using SentiLex-PT, a Portuguese sentiment lexicon, we extracted from the dataset the top 5 most frequent group of words related to opinions. Applying a bag-of-words model, the cosine similarity calculation was performed between each opinion and the observed groups. This study allowed us to observe an exacerbated use of passionate discourses in the digital political scenario as a form of appreciation and engagement to the groups which convey similar beliefs.