Abstract
When a company experiences the proliferation of negative information on social media, typically as a result of an incident in the real world, the company must decide whether to react positively, such as by responding in a timely manner, disclosing the facts, or offering an apology or compensation, or by reacting negatively with a denial or threat of legal actions. Before responding, the company should consider the potential impacts due to the different reactions of stakeholders. A company's ideal choice of strategy during a social media storm depends on the costs of that strategy for the company and the likelihood that netizens will publicly condemn the company on social media. In this study, we employ a model based on evolutionary game theory to investigate crisis communication on social media. The results show that the company's choice of response strategy influences the evolution of the strategy pursued by Internet users. In the base model, we consider three possible actions for netizens on social media in reaction to an incident: ignoring the incident, noticing the incident but staying silent, and condemning the company and transmitting negative information. Subsequently, we extend the base model to consider complex network structures and defensive behavior. We also studied real-world cases of social media crisis communication and conducted numeric simulations with different parameters in order to determine the evolutionary equilibrium in different situations, which may inform the crisis response strategy selected by companies.
Original language | English |
---|---|
Article number | 103371 |
Number of pages | 20 |
Journal | Information and Management |
Volume | 58 |
Issue number | 6 |
DOIs | |
Publication status | Published - Sept 2021 |
Fields of science
- 102 Computer Sciences
- 102010 Database systems
- 102015 Information systems
- 102016 IT security
- 102025 Distributed systems
- 102027 Web engineering
- 102028 Knowledge engineering
- 102030 Semantic technologies
- 102033 Data mining
- 102035 Data science
- 502050 Business informatics
- 503008 E-learning
JKU Focus areas
- Digital Transformation