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Type: Dissertação de Mestrado
Title: Characterizing Interconnections and Linguistic Patterns in Twitter
Authors: Johnnatan Messias Peixoto Afonso
First Advisor: Fabricio Benevenuto de Souza
First Referee: Fabricio Murai Ferreira
Second Referee: Wagner Meira Junior
Third Referee: Maria da Graça Campos Pimentel
Abstract: Social media is considered a democratic space in which people connect and interact with each other regardless of their gender, race, or any other demographic aspect. Despite numerous efforts that explore demographic aspects in social media, it is still unclear whether social media perpetuates old inequalities from the offline world. In this dissertation, we attempt to identify gender and race of Twitter users located in U.S. using advanced image processing algorithms from Face++. We investigate how different demographic groups (i.e. male/female, asian/black/white) connect with each other and differentiate between them regarding linguistic styles and also their interests. We quantify to what extent one group follow and interact with each other and the extent to which these connections and interactions reflect in inequalities in Twitter. We also extract linguistic features from 6 categories (affective attributes, cognitive attributes, lexical density and awareness, temporal references, social and personal concerns, and interpersonal focus) in order to identify the similarities and differences in the messages they share in Twitter. Furthermore, we extract the absolute ranking difference of top phrases between demographic groups. As a dimension of diversity, we also use the topics of interest that we retrieve from each user. Our analysis shows that users identified as white and male tend to attain higher positions in Twitter, in terms of the number of followers and number of times in other user's lists. There are clear differences in the way of writing across different demographic groups in both gender and race domains as well as in the topic of interest. We hope our effort can stimulate the development of new theories of demographic information in the online space. Therefore, we developed and deployed the Who Makes Trends? Web-based service available at
Subject: Computação
Redes sociais on-line
Tipologia (Linguistica)
Dados Demograficos;
language: Inglês
Publisher: Universidade Federal de Minas Gerais
Publisher Initials: UFMG
Rights: Acesso Aberto
Issue Date: 9-Jun-2017
Appears in Collections:Dissertações de Mestrado

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