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fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Languages: English
Types: Article
Subjects: HD
Purpose\ud – Drawing on the theoretical domain of speech act theory (SAT) and a discussion of its suitability for setting the agenda for social media research, this study aims to explore a range of research directions that are both relevant and conceptually robust, to stimulate the advancement of knowledge and understanding of online verbatim data.\ud \ud Design/methodology/approach\ud – Examining previously published cross-disciplinary research, the study identifies how recent conceptual and empirical advances in SAT may further guide the development of text analytics in a social media context.\ud \ud Findings\ud – Decoding content and function word use in customers’ social media communication can enhance the efficiency of determining potential impacts of customer reviews, sentiment strength, the quality of contributions in social media, customers’ socialization perceptions in online communities and deceptive messages.\ud \ud Originality/value\ud – Considering the variety of managerial demand, increasing and diverging social media formats, expanding archives, rapid development of software tools and fast-paced market changes, this study provides an urgently needed, theory-driven, coherent research agenda to guide the conceptual development of text analytics in a social media context.
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    • ANDERSON, E. T. & SIMESTER, D. I. 2014. Reviews Without a Purchase: Low Ratings, Loyal Customers, and Deception. Journal of Marketing Research, 51, 249-269.
    • ASHER, N. & LASCARIDES, A. 2001. Indirect speech acts. Synthese, 128, 183-228.
    • AUSTIN, J. L. 1962. How to do things with words: The William James Lectures delivered at Harvard University in 1955, Oxford: Clarendon Press.
    • BAGOZZI 2007. Antecedents and Consequences of Online Social Interactions. Media Psychology, 9, 77-144.
    • BALAHUR, A., HERMIDA, J. M. & MONTOYO, A. Detecting implicit expressions of sentiment in text based on commonsense knowledge. Proceedings of the 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis, 2011. Association for Computational Linguistics, 53-60.
    • BAUMEISTER, R. F., VOHS, K. D., DEWALL, C. N. & ZHANG, L. 2007. How Emotion Shapes Behavior:Feedback, Anticipation, and Reflection, Rather Than Direct Causation. Personality & Social Psychology Review, 11, 167-203.
    • BHARADWAJ, A., EL SAWY, O. A., PAVLOU, P. A. & VENKATRAMAN, N. 2013. Digital business strategy: toward a next generation of insights. MIS Quarterly, 37, 471-482.
    • BIRD, H., FRANKLIN, S. & HOWARD, D. 2002. 'Little words'--not really: Function and content words in normal and aphasic speech. Journal of Neurolinguistics, 15, 209- 237.
    • BONNET, D. & NANDAN, P. 2011. Transform to the Power of Digital- Digital Transformation as a Driver of Corporate Performance. Capgemini Consulting Report.
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