Polarization in social movements on Twitter

Abstract

Online social networks have become a parallel universe of socialization from which interactive dynamics are generated until recently unknown. From this framework of online communication, different social movements have reached a greater boom and spread. On Twitter these social movements have as a characteristic feature a hashtag (#) that allows cross-cutting the conversation. Although it has become an instrument that makes it possible to agglutinate the conversation in a massive way, we are also emerging voices that warn of the growing manipulation around these forms of socialization. Social workers must pay attention and investigate these means of digital activism in order to understand and avoid these possible manipulations.

In this communication we analyze in a longitudinal way different social movements on Twitter. To this end, social movements that have emerged during the last year about phenomena related to the empowerment of women (#metoo, #yositecreo, etc ...), cooperation against natural disasters (#mallorca) and social demands (# pensions). To identify leaderships, detect communities and measure social distances, social network analysis has been used as well as certain algorithms. For the analysis of the conversations, language analysis techniques have been used to optimize the combination of the most common words, giving rise to conversation patterns around certain force ideas.