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

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.

Keywords::

• online word-of-mouth
• complaint behavior
• social media networks
• opinion diffusion
• online firestorms

Acknowledgements

We thank Allan J. Kimmel and Philip J. Kitchen as well as two anonymous referees for their valuable comments to this article and their constructive suggestions. This work is part of the research in the Center for Computational Analysis of Social and Organizational systems (CASOS) on dynamic network analysis and is supported in part by the Office of Naval Research (ONR), United States Navy (ONR MURI N000140811186 and ONR MMV N00014060104), and in part by the Air Force Office of Sponsored Research (FA9550-05-1-0388). The views and conclusions contained in this article are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Office of Naval Research, the Air Force Office of Sponsored Research or the U.S. Government.

Additional information

Notes on contributors

J. Pfeffer

Jürgen Pfeffer is an assistant research professor at the School of Computer Science at Carnegie Mellon University, Pittsburgh, USA. His research focuses on dynamic analysis of large-scale real-world networks. Pfeffer develops new algorithms to model and calibrate interpersonal communication networks in order to better describe and predict diffusion processes. He also works on the optimization of network measures for large networks. Furthermore, Pfeffer's research projects deal with the analysis of emerging conflicts, e.g., in Northern African countries or the Middle East. His main interest in these projects is to detect and analyze change.

T. Zorbach

Thomas Zorbach is the founder and CEO of vm-people GmbH, a company based in Berlin, Germany, that specializes in the fields of Viral Marketing, Transmedia Storytelling, and Social Media Management. As well as being a practitioner himself, Zorbach has consulted with companies such as Microsoft, eBay, Fischer, Roland Berger, and Carlsen Publishing House and also contributes to academic research. His thesis, published at the University of Arts in Berlin, is entitled ‘Viral Communication – Aspects of Epidemic Spread on the Internet’ (2001). Zorbach also lectures in International Marketing at the Karlshochschule International University in Karlsruhe.

K. M. Carley

Kathleen M. Carley is a professor at the School of Computer Science, Carnegie Mellon University (Pittsburgh, USA), and director of the Center for Computational Analysis of Social and Organizational Systems (CASOS). Carley's research combines cognitive science, social networks, and computer science to address complex social and organizational problems. Her specific research areas are dynamic network analysis, computational social and organization theory, adaptation and evolution, text mining, and the impact of telecommunication technologies and policies on communication, information diffusion, and disease contagion and response within and among groups, particularly in disaster or crisis situations.