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Identifying Communities in Twitter from Hashtag Networks

Grant number: 22/00355-2
Support Opportunities:Scholarships in Brazil - Scientific Initiation
Start date: May 01, 2022
End date: October 31, 2022
Field of knowledge:Physical Sciences and Mathematics - Probability and Statistics - Applied Probability and Statistics
Principal Investigator:Jefferson Antonio Galves
Grantee:Eduardo Janotti Cavalcante
Host Institution: Instituto de Matemática e Estatística (IME). Universidade de São Paulo (USP). São Paulo , SP, Brazil
Associated research grant:13/07699-0 - Research, Innovation and Dissemination Center for Neuromathematics - NeuroMat, AP.CEPID

Abstract

This project aims to analyze the behavior of a community identification method when applied to real data. The studied method is based on a generalized stochastic block model and uses the degree of two distinct vertices of the graph to assess whether they do not belong to the same community. To evaluate the method, we will use data collected from the social network Twitter, more precisely information from posts that contains the hashtag #CPIdaCovid, and we will create a graph with the hashtags that appear concurrently with it. We are interested in the behavior of other hashtags, which we will be making comparisons with in order to verify if two distinct ones can be considered as belonging to the same community. As we will be using real data, some hashtag may have a much higher frequency in the sample than others, which may alter themethod's result. Therefore, we will test it with only the hashtags whose frequency in the sample belongs to a specified range that will be changed a few times for the purpose of verifying which one presents the best results. We hope that, later, we will be able to apply the results found here in other contexts and in different networks, both social and neurobiologies, and obtain satisfactory results regarding the identification ofcommunities.

News published in Agência FAPESP Newsletter about the scholarship:
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