MAIA, K. M.; http://lattes.cnpq.br/1289134692632682; MAIA, Kyev Moura.
Resumo:
The concepts of democracy and political representation have been constantly changing. Today, the most impressive change comes from the world wide web. The internet has provided a number of unimaginable possibilities 30 years ago, and among these contributions are social networks. The latest electoral processes around the world have shown some prominence in social networks before, during and after polling day. Twitter is one of the main tools used in the political arena for the move up and promotion of electoral support, so the question is: how has Twitter been used as a new means of fostering political representation in the digital age? The research assumes as main hypothesis that greater use of this tool enables the candidate for an elective office, better electoral performance, and change the profile of use between periods, post and pre-election. To this end, we sought to understand and explain the impact of Twitter on the process of competition in Brazil, how presidential candidates used this tool and what impact it had on the votes of federal deputies elected in 2018. The investigation followed the path of the hypotheticaldeductive method and allowed two approaches to data treatment: qualitative for the profile of use of candidates for presidency of the republic in 2018 through the tool Twittonomy and MAXQDA; and quantitative, performing a series of statistical tests with primary Twitter data from federal deputies elected in 2018 and their respective parties, and secondary data provided by the TSE. The main results point out that Twitter, as well as other social networks, incorporate and initiate a new aspect of the
concept of political representation; presidential candidates seek to use the tool more
intensely during the election period and seek to anoint support, share links and
publicize their future radio and TV appearances. Statistical tests showed that there is
a positive impact of using Twitter on deputies' roll-call votes, with the following
variables: party followers, candidate tweets and campaign spending having a greater
impact on the Artificial Neural Network model.