The growing number of user-generated content that can be found online has led to a huge amount
of data that can be used for scientific research. This book investigates the prediction of
certain human-related events using valences and emotions expressed in user-generated content
with regard to past and current research. First the theoretical framework of user-generated
content and sentiment detection- and classification methods is explained before empirical
literature is categorized into three specific prediction subjects. This is followed by a
comprehensive analysis including a comparison of prediction methods consistency and
limitations with respect to each of the three predictive sources.
