From valence to emotions : how coarse versus fine-grained online sentiment can predict real-world outcomes / Robert Kohtes.
- Hamburg, Germany : Anchor Academic Publishing, 2014.
1 online resource (79 p.)
- Corporations -- Finance.
Financial statements -- Germany.
- Electronic books.
- 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
- From Valence to Emotions; Abstract; Table of Contents; List of Abbreviations; List of Figures; List of Tables; 1 Introduction; 2 Structure of Book; 3 The Need of Automated Prediction Using Online Sentiments; 4 What are the Different Prediction and Sentiment Detection Approaches and Techniques based on User-Generated-Content?; 4.1 User Generated Content and its Technical Background; 4.2 Online Word-of-Mouth; 4.3 Sentiment Classification; 5 How Consistent are Prediction Results Based on Online Sentiments?; 5.1 Predictive Power of Online Sentiments; 5.1.1 Stock Markets; 5.1.2 Sales Volume
5.1.3 Box Office Revenues6 Do Fine-Grained Sentiments Generate New Insights and Better Prediction Results Than Coarse Sentiments?; 7 Conclusion; 8 Managerial Implications; Bibliography
- Description based upon print version of record.
Includes bibliographical references.
Description based on online resource; title from PDF title page (ebrary, viewed April 16, 2014).
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