Two papers from the ThinkBIG project have been accepted for presentation at workshops at the International Conference on Data Mining taking place in Barcelona, Spain from the 12th – 15th December 2016.
The first paper, Seasonal Fluctuations in Collective Mood Revealed by Wikipedia Searches and Twitter Posts will be presented at the Sentiment Elicitation from Natural Text for Information Retrieval and Extraction workshop (SENTIRE) by Fabon Dzogang. In this paper, we investigate seasonal fluctuations in mood and mental health by analyzing the access logs of Wikipedia pages and the content of Twitter in the UK over a period of four years. By using standard methods of Natural Language Processing, we extract daily indicators of negative affect, anxiety, anger and sadness from Twitter and compare this with the overall daily traffic to Wikipedia pages about mental health disorders.
The second paper, Change-point Analysis of the Public Mood in UK Twitter during the Brexit Referendum will be presented at the Data Mining in Politics workshop (DMiP) by Thomas Lansdall-Welfare. In this paper, we study the changes in public mood within the contents of Twitter in the UK, in the days before and after the Brexit referendum. We measure the levels of anxiety, anger, sadness, negative affect and positive affect in various geographic regions of the UK, at hourly intervals. We analyse these affect time series’ by looking for change-points common to all five components, locating points of simultaneous change in the multivariate series using the fast group LARS algorithm, an algorithm originally developed for bioinformatics applications.