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024 7 $a10.1007/978-3-658-09508-6
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035   $a(DE-He213)978-3-658-09508-6
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100   $a20150421d2015      u|             0
101 0 $aeng
135   $aur|n|---|||||
181   $ctxt
182   $cc
183   $acr
200 14$aThe Value of Social Media for Predicting Stock Returns$b[electronic resource] $ePreconditions, Instruments and Performance Analysis /$fby Michael Nofer
205   $a1st ed. 2015.
210  1$aWiesbaden :$cSpringer Fachmedien Wiesbaden :$cImprint: Springer Vieweg,$d2015.
215   $a1 online resource (140 p.)
225 0 $aResearch
300   $aDescription based upon print version of record.
311   $a3-658-09507-5 
320   $aIncludes bibliographical references.
327   $aIntroduction -- Market Anomalies on Two-Sided Auction Platforms -- Are Crowds on the Internet Wiser than Experts? ? The Case of a Stock Prediction Community -- Using Twitter to Predict the Stock Market: Where is the Mood Effect? -- The Economic Impact of Privacy Violations and Security Breaches ? A Laboratory Experiment -- Literature.
330   $aMichael Nofer examines whether and to what extent Social Media can be used to predict stock returns. Market-relevant information is available on various platforms on the Internet, which largely consist of user generated content. For instance, emotions can be extracted in order to identify the investors' risk appetite and in turn the willingness to invest in stocks. Discussion forums also provide an opportunity to identify opinions on certain companies. Taking Social Media platforms as examples, the author examines the forecasting quality of user generated content on the Internet. Contents Market Anomalies on Two-Sided Auction Platforms Are Crowds on the Internet Wiser than Experts? ? The Case of a Stock Prediction Community Using Twitter to Predict the Stock Market: Where is the Mood Effect? The Economic Impact of Privacy Violations and Security Breaches ? A Laboratory Experiment Target Groups Scientists and students in the field of IT, finance and business Private investors, institutional investors About the Author Michael Nofer wrote his dissertation at the Chair of Information Systems | Electronic Markets at TU Darmstadt, Germany.  .
606   $aData mining
606   $aMacroeconomics
606   $aInformation technology
606   $aBusiness?Data processing
606   $aData Mining and Knowledge Discovery$3https://scigraph.springernature.com/ontologies/product-market-codes/I18030
606   $aMacroeconomics/Monetary Economics//Financial Economics$3https://scigraph.springernature.com/ontologies/product-market-codes/W32000
606   $aIT in Business$3https://scigraph.springernature.com/ontologies/product-market-codes/522000
615  0$aData mining.
615  0$aMacroeconomics.
615  0$aInformation technology.
615  0$aBusiness?Data processing.
615 14$aData Mining and Knowledge Discovery.
615 24$aMacroeconomics/Monetary Economics//Financial Economics.
615 24$aIT in Business.
676   $a004
676   $a006.312
676   $a332
676   $a650
700   $aNofer$b Michael$4aut$4http://id.loc.gov/vocabulary/relators/aut$01059431
906   $aBOOK
912   $a9910299246703321
996   $aThe Value of Social Media for Predicting Stock Returns$92505854
997   $aUNINA