Association for Computing Machinery
Social media have been employed to assess public opinions on events, markets, and policies. Most current work focuses on either developing aggregated measures or opinion extraction methods like sentiment analysis. These approaches suffer from unpredictable turnover in the participants and the information they react to, making it difficult to distinguish meaningful shifts from those that follow from known information. The authors propose a novel approach to tame these sources of uncertainty through the introduction of \"Computational focus groups\" to track opinion shifts in social media streams.