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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 a...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Hamburg, Germany :
Anchor Academic Publishing,
2014.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Kohtes, Robert, |e author. | |
| 245 | 1 | 0 | |a From valence to emotions : |b how coarse versus fine-grained online sentiment can predict real-world outcomes / |c Robert Kohtes. |
| 264 | 1 | |a Hamburg, Germany : |b Anchor Academic Publishing, |c 2014. | |
| 264 | 4 | |c ©2014 | |
| 300 | |a 1 online resource (79 pages) : |b illustrations, tables | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 504 | |a Includes bibliographical references. | ||
| 588 | 0 | |a Online resource; title from PDF title page (ebrary, viewed April 16, 2014). | |
| 505 | 0 | |a 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 | |
| 505 | 8 | |a 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 | |
| 520 | |a 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. | ||
| 546 | |a English. | ||
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| 650 | 7 | |a BUSINESS & ECONOMICS |x Organizational Behavior. |2 bisacsh | |
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| 776 | 0 | 8 | |i Print version: |a Kohtes, Robert. |t From valence to emotions : how coarse versus fine-grained online sentiment can predict real-world outcomes. |d Hamburg, Germany : Anchor Academic Publishing, ©2014 |h x, 70 pages |z 9783954891450 |
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