About this Research Topic
Rumor is generally defined as information that has not been officially confirmed but is still transmitted through society. Research on rumors has been going on for decades, dating back to the World War II. Nowadays, the topic of rumor governance is becoming more and more important both in science and in practice, especially during the sudden crisis, such as natural disasters and major epidemics like COVID-19 pandemic. Rumor can be a major problem in social governance, as it often leads to the degradation or outright destruction of public security and social order. For example, on April 23, 2013, a rumor about two explosions injuring Barack Obama caused a serious crash in the US stock market. Thus, it is of great importance to better understand the characteristics of rumors and its formation and spreading mechanisms, and develop and implement effective strategies for discouraging its dissemination.
Since the rapid development of computer technology in recent years, social media platforms enable individuals to post their viewpoints on global events. A specific form in which users both access and share opinions and perceptions is showing a greater transition in social media platforms than perhaps at any previous point in history. However, they also pose some serious problems that should be addressed, for example, the transmission of rumors via the electronic media has become ubiquitous. Thus, social media should be viewed as a data source or modeling basis for rumor governance. In addition, there has been a significant increase in the adoption and use of social media by both the general public and particular subpopulations, such as government sectors, enterprises, and celebrities, which allow scholars to explore rumors under more realistic and complex situations.
Overall, the research field of social media data-based rumor governance is interdisciplinary by nature at the intersection of various disciplines, including but not limited to information science, social physics, mathematics, politics, psychology, communication, and sociology. This current Research Topic aims to cover all areas related to rumor governance using social media data and invites researchers from various disciplines to contribute.
Topics of interest include but are not limited to:
• theoretical, methodological, and ethical investigations on rumor governance
• differences in characteristics between different kinds of rumors on different social media platforms
• identify key factors influencing rumor formation and spreading, and accordingly propose decision making suggestions for rumor governance
• empirical studies focusing on reasons and mechanisms for the formation of rumors from the perspective of human behavior and social aggregation
• social media data-driven opinion dynamics model for rumor spreading and governance simulation
• using social media data for rumor detection and rumor source detection
• new data mining methods, such as machine learning, social network analysis, natural language processing, and knowledge graphs, for rumor governance.
Since the rapid development of computer technology in recent years, social media platforms enable individuals to post their viewpoints on global events. A specific form in which users both access and share opinions and perceptions is showing a greater transition in social media platforms than perhaps at any previous point in history. However, they also pose some serious problems that should be addressed, for example, the transmission of rumors via the electronic media has become ubiquitous. Thus, social media should be viewed as a data source or modeling basis for rumor governance. In addition, there has been a significant increase in the adoption and use of social media by both the general public and particular subpopulations, such as government sectors, enterprises, and celebrities, which allow scholars to explore rumors under more realistic and complex situations.
Overall, the research field of social media data-based rumor governance is interdisciplinary by nature at the intersection of various disciplines, including but not limited to information science, social physics, mathematics, politics, psychology, communication, and sociology. This current Research Topic aims to cover all areas related to rumor governance using social media data and invites researchers from various disciplines to contribute.
Topics of interest include but are not limited to:
• theoretical, methodological, and ethical investigations on rumor governance
• differences in characteristics between different kinds of rumors on different social media platforms
• identify key factors influencing rumor formation and spreading, and accordingly propose decision making suggestions for rumor governance
• empirical studies focusing on reasons and mechanisms for the formation of rumors from the perspective of human behavior and social aggregation
• social media data-driven opinion dynamics model for rumor spreading and governance simulation
• using social media data for rumor detection and rumor source detection
• new data mining methods, such as machine learning, social network analysis, natural language processing, and knowledge graphs, for rumor governance.
Keywords: Rumor Governance, Social Media Data, Big Data analysis, Opinion Dynamics, Data Mining, Deep Learning, Network Science
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