Detecting Group Beliefs Related to 2018's Brazilian Elections in Tweets A Combined Study on Modeling Topics and Sentiment Analysis
This work addresses the problem of understanding group dynamics and belief reinforcement in social media for researchers and policymakers, but it is incremental as it applies existing methods to a specific dataset.
The study analyzed politically motivated tweets from the 2018 Brazilian presidential elections to see if similar discourses reinforce group engagement to personal beliefs, finding an exacerbated use of passionate discourses as a form of appreciation and engagement among groups with similar beliefs.
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.