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Comparing analysis of social media content with traditional survey methods of predicting opening night box-office revenues for motion pictures
For many years, consumers’ self-reported behavioural intentions have been successfully measured through traditional surveying tools. Purchase intention is very often used for predicting likely levels of demand for new products. More recently, use of social media content has gained popularity as a viable alternative for gauging consumers’ intention to buy. For example, Twitter has been used by many researchers for predicting box-office returns for movies with promising results. This paper investigates how traditional surveying tools compare with the use of social media. Specifically, surveys regarding intention to see a movie were administered during the same period as tweets about the movie were collected. Traditional behavioural intention measures were compared with various measures of tweeting activity to gauge how well each correlates with movie opening night box-office receipts. The results show that the two methods are very comparable.
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Hossien L. Najafi is Professor of Computer Science at University of Wisconsin River Falls. His research interests include machine learning, neural networks, fuzzy logic and their application to real-world problems. His research has been published in the International Journal of Intelligent Computing and Cybernetics, Journal of Applied Intelligence and Journal of the Academy of Finance.
Darryl W. Miller is Professor of Marketing at the University of Wisconsin River Falls. His research interests include branding, marketing communications, services and international marketing. His studies have been published in the Journal of Marketing Communications, Journal of Brand Management and Journal of Financial Services Marketing.