The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Twitter power: Tweets as electronic word of mouth
Abstract
In this paper we report research results investigating microblogging as a form of electronic word‐of‐mouth for sharing consumer opinions concerning brands. We analyzed more than 150,000 microblog postings containing branding comments, sentiments, and opinions. We investigated the overall structure of these microblog postings, the types of expressions, and the movement in positive or negative sentiment. We compared automated methods of classifying sentiment in these microblogs with manual coding. Using a case study approach, we analyzed the range, frequency, timing, and content of tweets in a corporate account. Our research findings show that 19% of microblogs contain mention of a brand. Of the branding microblogs, nearly 20% contained some expression of brand sentiments. Of these, more than 50% were positive and 33% were critical of the company or product. Our comparison of automated and manual coding showed no significant differences between the two approaches. In analyzing microblogs for structure and composition, the linguistic structure of tweets approximate the linguistic patterns of natural language expressions. We find that microblogging is an online tool for customer word of mouth communications and discuss the implications for corporations using microblogging as part of their overall marketing strategy.
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Cites
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“Additionally, altruistic behavior of sharing expertise with others has also been shown to motivate positive WOM (Fehr & Falk, 2002; Richins, 1984).”
Background
Cited by
De Veirman, M., Cauberghe, V., & Hudders, L. (2017) · International Journal of Advertising · doi:10.1080/02650487.2017.1348035 · Cited by 2,548
Predicting the future with social media
Asur, S., & Huberman, B. A. (2010) · 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology · doi:10.1109/wi-iat.2010.63 · Cited by 2,081
How Does Brand-related User-generated Content Differ across YouTube, Facebook, and Twitter?
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Social big data: recent achievements and new challenges
Bello-Orgaz, G., Jung, J. J., & Camacho, D. (2016) · Information Fusion · doi:10.1016/j.inffus.2015.08.005 · Cited by 846
“[94] Twitter as eWOM advertising mechanism Sentiment analysis”
MethodAffective News and Networked Publics: The Rhythms of News Storytelling on #Egypt
Papacharissi, Z., & de Fatima Oliveira, M. (2012) · Journal of Communication · doi:10.1111/j.1460-2466.2012.01630.x · Cited by 803
Metadata
- Authors
- Jansen, B. J., Zhang, M., Sobel, K., & Chowdury, A.
- Venue
- Journal of the American Society for Information Science and Technology
- Publisher
- Wiley
- Published
- 2009-07-06
- Volume
- 60
- Issue
- 11
- Pages
- 2169-2188
- ISSN
- 1532-2882 (ISSN-L)
- 1532-2890
- OpenAlex
- W4255173720
- Cited by
- 1,642
- References
- 5
- FWCI
- 180.18
- Type
- journal article
- Language
- en
- Open access
- closed
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- Jansen, B. J., Zhang, M., Sobel, K., & Chowdury, A. (2009). Twitter power: Tweets as electronic word of mouth. Journal of the American Society for Information Science and Technology. https://doi.org/10.1002/asi.21149
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