Social media and decision making: a data science lifecycle for opinion mining of public reactions to the 2020 International Booker Prize in Twitter

The emergence of social media platforms has altered patterns of interaction between individuals and decision-makers. To explore the impact of such changes, this study conducts an opinion mining of public reactions in Twitter to the 2020 International Booker Prize shortlist. Over 13,000 tweets were collected and analysed to examine whether public's emotions and responses to a list of nominees are akin to or influence the judges' decisions about the winning novelist. A data science lifecycle for sentiment analysis and topic modelling is proposed to classify tweet sentiments and identify the dominant topics in relation to the six shortlisted literary works both before and after the announcement of the winner. The findings show a marked discrepancy between readers' preference and the judges' decision as the prize was granted to one of the least heeded nominees. This difference reinforces the suspicion that the literary prizes are filtered through judges' personal views. The proposed digital model in this study can assist critics, book club judges, literary prize-givers, and publishing industries in better decision making.