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Social Network Analysis and Mining

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01-12-2015 | Original Article

Detecting sociosemantic communities by applying social network analysis in tweets

Authors: Rocío Abascal-Mena, Rose Lema, Florence Sèdes

Published in: Social Network Analysis and Mining | Issue 1/2015

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Abstract

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.

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Title: Detecting sociosemantic communities by applying social network analysis in tweets
Authors: Rocío Abascal-Mena
Rose Lema
Florence Sèdes
Publication date: 01-12-2015
Publisher: Springer Vienna
Published in: Social Network Analysis and Mining / Issue 1/2015
Print ISSN: 1869-5450
Electronic ISSN: 1869-5469
DOI: https://doi.org/10.1007/s13278-015-0280-2

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