|
|
|
|
LEADER |
00000cam a2200000Mu 4500 |
001 |
EBOOKCENTRAL_ocn871779867 |
003 |
OCoLC |
005 |
20240329122006.0 |
006 |
m o d |
007 |
cr |n|---||||| |
008 |
140306s2014 gw o 000 0 eng d |
040 |
|
|
|a MHW
|b eng
|e pn
|c MHW
|d EBLCP
|d OCLCQ
|d YDXCP
|d OCLCQ
|d ZCU
|d MERUC
|d ICG
|d OCLCO
|d OCLCF
|d OCLCQ
|d DKC
|d OCLCO
|d AU@
|d OCLCQ
|d OCLCO
|d SGP
|d OCLCQ
|d OCLCO
|d OCLCL
|
019 |
|
|
|a 901623547
|
020 |
|
|
|a 9783954896455
|
020 |
|
|
|a 3954896451
|
020 |
|
|
|z 395489145X
|
020 |
|
|
|z 9783954891450
|
029 |
1 |
|
|a AU@
|b 000062532754
|
029 |
1 |
|
|a DEBBG
|b BV043607919
|
035 |
|
|
|a (OCoLC)871779867
|z (OCoLC)901623547
|
043 |
|
|
|a e-gx---
|
050 |
|
4 |
|a HG4026
|
082 |
0 |
4 |
|a 658.15
|
049 |
|
|
|a UAMI
|
100 |
1 |
|
|a Kohtes, Robert.
|
245 |
1 |
0 |
|a From Valence to Emotions.
|
260 |
|
|
|a Hamburg :
|b Diplomica Verlag,
|c 2014.
|
300 |
|
|
|a 1 online resource (79 pages)
|
336 |
|
|
|a text
|b txt
|2 rdacontent
|
337 |
|
|
|a computer
|b c
|2 rdamedia
|
338 |
|
|
|a online resource
|b cr
|2 rdacarrier
|
588 |
0 |
|
|a Print version record.
|
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.
|
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
|
590 |
|
|
|a ProQuest Ebook Central
|b Ebook Central Academic Complete
|
650 |
|
0 |
|a Corporations
|x Finance.
|
650 |
|
0 |
|a Financial statements
|z Germany.
|
650 |
|
7 |
|a Corporations
|x Finance
|2 fast
|
650 |
|
7 |
|a Financial statements
|2 fast
|
651 |
|
7 |
|a Germany
|2 fast
|1 https://id.oclc.org/worldcat/entity/E39PBJtCD3rcKcPDx6FHmjvrbd
|
776 |
0 |
8 |
|i Print version:
|z 9783954891450
|
856 |
4 |
0 |
|u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=1640330
|z Texto completo
|
938 |
|
|
|a ProQuest Ebook Central
|b EBLB
|n EBL1640330
|
938 |
|
|
|a YBP Library Services
|b YANK
|n 11684828
|
994 |
|
|
|a 92
|b IZTAP
|