LAUSR

Social research on public opinion has been affected by the recent deluge of new digital data on the Web, from blogs and forums to Facebook pages and Twitter accounts. This fresh type of information useful for mining opinions is emerging as an alternative to traditional techniques, such as opinion polls. Firstly, by building the state of the art of studies of political opinion based on Twitter data, this paper aims at identifying the relationship between the chosen data analysis method and the definition of political opinion implied in these studies. Secondly, it aims at investigating the feasibility of performing multiscale analysis in digital social research on political opinion by addressing the merits of several methodological techniques, from content-based to interaction-based methods, from statistical to semantic analysis, from supervised to unsupervised approaches. The end result of such an approach is to identify future trends in social science research on political opinion.