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Cited by 554

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Understanding online firestorms: Negative word-of-mouth dynamics in social media networks

Pfeffer, J., Zorbach, T., Carley, K. M.·2014·Journal of Marketing Communications

Abstract

Social media are, on the one hand, a highly beneficial environment for word-of-mouth (WOM) propagation of new ideas and products, and this has increasingly made them a focus of marketing communications. On the other hand, companies and their brands as well as politicians, governmental institutions, and celebrities have increasingly been facing the impact of negative online WOM and complaint behavior. In reaction to any questionable statement or activity, social media users can create huge waves of outrage within just a few hours. These so-called online firestorms pose new challenges for marketing communications. In this article, we group observations from recent online firestorms, identify related social and economic science theories, and derive generalized factors that form the basis for the proliferation of these dynamics. Furthermore, we discuss the consequences of online firestorms for marketing communications, and offer courses of action for marketers to navigate through crises of negative online WOM.

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Metadata

Authors
Pfeffer, J., Zorbach, T., & Carley, K. M.
Venue
Journal of Marketing Communications
Published
2013-06-10
Volume
20
Issue
1-2
Pages
117-128
ISSN
  • 1352-7266 (ISSN-L)
  • 1466-4445
OpenAlex
W2148895878
Cited by
554
References
2
FWCI
62.85
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Understanding online firestorms: Negative word-of-mouth dynamics in social media networks. https://app.cochat.ai/papers/10.1080/13527266.2013.797778
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Pfeffer, J., Zorbach, T., & Carley, K. M. (2014). Understanding online firestorms: Negative word-of-mouth dynamics in social media networks. Journal of Marketing Communications. https://doi.org/10.1080/13527266.2013.797778

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.