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Analyzing the relationship between differentiated online sentiment and company-specific stock prices
(2015)
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.
SOCIAL MEDIA PLATFORMS PRESENT UNIQUE POSSIBILITIES FOR COMPANIES TO INTERACT WITH THEIR CUSTOMERS AND TAKE UP A KEY ROLE IN BUILDING RELATIONSHIPS. HOWEVER, LITTLE IS KNOWN CONCERNING THE FINANCIAL RETURN ON INVESTMENT FROM SOCIAL MEDIA ENGAGEMENT AND SPECIFIC STRATEGIES TO LEVERAGE IT. THE ANALYSIS OF OVER 1.5 MILLION TWEETS REVOLVING AROUND TEN CAR MANUFACTURERS SUGGESTS THAT COMPANIES CAN INCREASE THEIR SALES VOLUME THROUGH GREATER RELATIONSHIP INVESTMENT AND BY ADOPTING A SOCIAL MEDIA STRATEGY THAT PROMOTES THE USERS’ RELATIONSHIP SATISFACTION.
