Listening and comprehending the pulse of places: cultural analysis of emotions in Big Data and polarisation

It is hoped that city happiness can be detected through the use of Big Data. This raises the question of accuracy and precision in predicting city happiness with Big Data, owing to a number of technical challenges. This chapter uses Big Data from Twitter in the UK that we aggregate on an individual level and combine with geocoded data from Google Trends and culture-related data from Understanding Society. We perform principal component factor analysis on the individual level data from Understanding Society and aggregate it on a regional level to characterise the Cultural Entropy of the geocoded local context following the culture-based development (CBD) approach. This allows us to account for the presence of cultural bias in the Big Data quantification of city happiness. We triangulate the results using the Google Trends data. Thus, we offer a brief quantitative demonstration of the technical challenges and their potential CBD-resolutions suggested in our initial theoretical reflections.