From Valence to Emotions: How Coarse versus Fine-Grained Online Sentiment can predict Real-World Outcomes

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.

Dipl. Kfm. Robert Kohtes, born in 1983, studied Business Administration at the University of Cologne in Germany and at the Asian Institute of Management Manila on the Philippines. During his studies, he specialized in Marketing and Corporate Finance. Curr