Big Social data to analyse the #metoo movement.

Abstract

On Twitter the 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 homophily around these forms of socialization. In this paper we analyze in a longitudinal way the feminist #metoo movement on Twitter during the 2018-2019. 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, netnography and content analysis have been used to optimize the combination of the most common contents, giving rise to conversation patterns around certain force ideas. The results achieved show a significant pattern of polarization in the way of interacting that may be the seed of radicalization. The key lies in the way we congregate in networks around those with whom we share our perspectives and opinions about the world. This tendency provokes a biased and monolithic vision of reality. In order to counteract social workers must raise the level of self-awareness and intervene to increase tolerance for diversity.