Detecting sociosemantic communities by applying social network analysis in tweets

Rocio Abascal-Mena (1) , Rose Lema (1) , Florence Sèdes (2)

1 Universidad Autonoma Metropolitana, Unidad Cuajimalpa
2 IRIT-SIG - Systèmes d’Informations Généralisées

Virtual social networks have led to a new way of communication that is different from the oral one, where the restriction of time and space generates new linguistic practices. Twitter, a medium for political and social discussion, can be analyzed to understand new ways of communication and to explore sociosemiotics aspects that come with the use of the hashtags and their relationship with other elements. This paper presents a quantitative study of tweets, around a fixed hashtag, in relation with other contents that users bring to connection. By calculating the frequency of terms, a table of nodes and edges is created to visualize tweets like graphs. Our study applies social network analysis that, going beyond mere topology, reveals relevant sociosemantic communities providing insights for the comparison of social and political movements.

Mots clés: Information mining; Social Web; Social Network Analysis; Graph theory; Community detection; Sociosemantics; Twitter

Domaines: Théorie de l'information [cs.IT]; Recherche d'information [cs.IR]

Rocio Abascal-Mena, Rose Lema, Florence Sèdes. Detecting sociosemantic communities by applying social network analysis in tweets. Social Network Analysis and Mining, 2015, vol. 5 (n° 1), pp. 1-17. ⟨10.1007/s13278-015-0280-2⟩. ⟨hal-01283863⟩