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From Valence to Emotions
How Coarse versus Fine-Grained Online Sentiment Can Predict Real-World Outcomes
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The thesis explores the potential of user-generated content for predicting human-related events by analyzing the emotions and valences expressed within it. It provides a theoretical framework for sentiment detection and classification methods, categorizing empirical literature into three prediction subjects. A comprehensive analysis reveals significant differences in prediction accuracies based on data sources and methods, highlighting that fine-grained sentiments enhance prediction accuracy. The study also addresses the scarcity of empirical data on fine-grained sentiment approaches for evaluation.
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From Valence to Emotions, Robert Kohtes
- Language
- Released
- 2013
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- (Paperback)
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- Title
- From Valence to Emotions
- Subtitle
- How Coarse versus Fine-Grained Online Sentiment Can Predict Real-World Outcomes
- Language
- English
- Authors
- Robert Kohtes
- Publisher
- GRIN Verlag
- Released
- 2013
- Format
- Paperback
- Pages
- 88
- ISBN13
- 9783656443261
- Category
- Business and Economics
- Description
- The thesis explores the potential of user-generated content for predicting human-related events by analyzing the emotions and valences expressed within it. It provides a theoretical framework for sentiment detection and classification methods, categorizing empirical literature into three prediction subjects. A comprehensive analysis reveals significant differences in prediction accuracies based on data sources and methods, highlighting that fine-grained sentiments enhance prediction accuracy. The study also addresses the scarcity of empirical data on fine-grained sentiment approaches for evaluation.