Uma abordagem de apuração do capital social bourdieusiano acumulado em perfis da rede Twitter

Abstract

We present in this work an approach to computing the Bourdieusian Social Capital (BSC) contained in profiles within the Twitter Network. The research methodology was defined as Design Science Research Methodology (DSRM). The main artifacts developed are a systematic process and a mobile tool based on that process. Supported by the theory of sociologist Pierre Bourdieu, data related to network sociability practices, i. e., data related to an execution of actions such as Like, Comment and Share, is identified and captured. The system of symbolic exchanges and mutual recognition discussed by Bourdieu is represented and automatically extracted from this data in the form of generalized sequential patterns. In this format, the social interactions captured from each profile are represented as sequences of actions. The frequency of occurrence of each sequence is computed and, from them, the effective mobilization capacity of each profile. Finally, the BSC volume is computed using the effective mobilization capacity, the number of social interactions captured and the number of active and inactive followers of each profile.The results obtained from the quantitative and qualitative analysis of institutional and noninstitutional profiles are in line with the Bourdieu theory. Institutional profiles are from federal professional education institutions. The non-institutional profiles are from precandidates for the presidency of Brazil. These results allow us to observe 1) the feedback movement between online Social Capital (from the digital world) and offline Social Capital (from the physical world), as well as 2) the composition of the BSC from the polarity of sentiment contained in the tweets.