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Analyzing the relationship between differentiated online sentiment and company-specific stock prices

  • PRACTITIONERS AND RESEARCHERS ALIKE INCREASINGLY USE SOCIAL MEDIA MESSAGES AS AN ADDITIONAL SOURCE OF INFORMATION WHEN DEALING WITH STOCKS. BASED ON EMOTION THEORY AND AN ESTABLISHED SENTIMENT LEXICON, WE DEVELOP AND APPLY AN OPEN SOURCE DICTIONARY FOR THE ANALYSIS OF SEVEN DIFFERENT EMOTIONS IN 5.5 MILLION TWITTER MESSAGES ON 33 S&P 100 COMPANIES. WE FIND VARYING EXPLANATORY POWER OF DIFFERENT EMOTIONS (ESP. HAPPINESS, AND DEPRESSION) FOR COMPANY-SPECIFIC STOCK PRICE MOVEMENTS OVER A PERIOD OF THREE MONTHS.

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Metadaten
Author:Marten Risius, Fabian Akolk, Roman Beck
URN:urn:nbn:de:hebis:30:3-579817
ISSN:1866-1238
Parent Title (English):EFL quarterly : an E-Finance Lab publication
Publisher:E-Finance Lab e.V.
Place of publication:Frankfurt am Main
Document Type:Article
Language:English
Year of Completion:2015
Year of first Publication:2015
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2021/01/28
Volume:2015
Issue:3
Page Number:3
First Page:6
Last Page:8
HeBIS-PPN:477254357
Institutes:Angeschlossene und kooperierende Institutionen / E-Finance Lab e.V.
Dewey Decimal Classification:3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft
Sammlungen:Universitätspublikationen
Licence (German):License LogoDeutsches Urheberrecht