Unveiling What Is Written in the Stars: Analyzing Explicit, Implicit, and Discourse Patterns of Sentiment in Social Media
| Autor: | Stephan Ludwig, Ko de Ruyter, Francisco Villarroel Ordenes, Martin Wetzels, Dhruv Grewal |
|---|---|
| Přispěvatelé: | RS: GSBE MSCM, Marketing & Supply Chain Management |
| Rok vydání: | 2017 |
| Předmět: |
HD
Economics and Econometrics Process (engineering) social media media_common.quotation_subject Big data text mining speech act theory consumer sentiment speech act theory text mining online reviews sales ranks social media Text mining Arts and Humanities (miscellaneous) 0502 economics and business Social media Product (category theory) online reviews Business and International Management media_common Marketing business.industry 05 social sciences Sentiment analysis Advertising Consumer Sentiment Sentiment Analysis Speech Act Theory Text Mining Customer Reviews Sales Ranks Social Media Marketing Analytics consumer sentiment Anthropology Service (economics) 050211 marketing Consumer confidence index Psychology business sales ranks 050203 business & management Cognitive psychology |
| Zdroj: | Ordenes, F V, Ludwig, S, Ruyter, K D, Grewal, D & Wetzels, M 2017, ' Unveiling What is Written in The Stars : Analyzing Explicit, Implicit, and Discourse Patterns of Sentiment in Social Media ', JOURNAL OF CONSUMER RESEARCH, vol. 43, no. 6, pp. 875–894 . https://doi.org/10.1093/jcr/ucw070 Journal of Consumer Research, 43(6), 875-894. Oxford University Press |
| ISSN: | 1537-5277 0093-5301 |
| DOI: | 10.1093/jcr/ucw070 |
| Popis: | Deciphering consumers’ sentiment expressions from big data (e.g., online reviews) has become a managerial priority to monitor product and service evaluations. However, sentiment analysis, the process of automatically distilling sentiment from text, provides little insight regarding the language granularities beyond the use of positive and negative words. Drawing on speech act theory, this study provides a fine-grained analysis of the implicit and explicit language used by consumers to express sentiment in text. An empirical text-mining study using more than 45,000 consumer reviews demonstrates the differential impacts of activation levels (e.g., tentative language), implicit sentiment expressions (e.g., commissive language), and discourse patterns (e.g., incoherence) on overall consumer sentiment (i.e., star ratings). In two follow-up studies, we demonstrate that these speech act features also influence the readers’ behavior and are generalizable to other social media contexts, such as Twitter and Facebook. We contribute to research on consumer sentiment analysis by offering a more nuanced understanding of consumer sentiments and their implications. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|