# Como Mensurar a Import\^ancia, Influ\^encia e a Relev\^ancia de Usu\'arios do Twitter? Uma an\'alise da intera\c{c}\~ao dos candidatos \`a presid\^encia do Brasil nas elei\c{c}\~oes de 2018

## TL;DR

This paper analyzes Twitter interactions of Brazilian 2018 presidential candidates using complex network metrics to quantify user influence and relevance, employing community detection algorithms to identify user groups.

## Contribution

It introduces a new metric for measuring user importance in Twitter networks and applies community detection to political candidate interactions.

## Key findings

- Identified influential users and their network positions.
- Detected distinct communities of users around candidates.
- Quantified influence and relevance of Twitter users in political discourse.

## Abstract

In the contemporary world, a significant number of people use social networking services for a variety of purposes, including, but not limited to, communicating, exchanging messages and searching for information. A popular social network in the political arena is Twitter, a microblogging service for posting messages of up to 280 characters, called "tweets," where influential politicians from various countries often use this medium to spread ideas and make public statements. In this work, an analysis was made of the connections of candidates for the presidency of the Republic of Brazil in the year 2018. Using the analysis of complex networks to measure influence and relevance, a metric was established able to quantify the importance of users in the network. As part of the analysis, a Memory Algorithm was used to detect communities, groups of strongly connected vertices (tweets) evidencing groupings of users.