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BackgroundAn infodemic is an overabundance of information—some accurate and some not—that occurs during an epidemic. In a similar manner to an epidemic, it spreads between humans via digital and physical information systems. It makes it hard for people to find trustworthy sources and reliable guidance when they need it. ObjectiveA World Health Organization (WHO) technical consultation on responding to the infodemic related to the coronavirus disease (COVID-19) pandemic was held, entirely online, to crowdsource suggested actions for a framework for infodemic management. MethodsA group of policy makers, public health professionals, researchers, students, and other concerned stakeholders was joined by representatives of the media, social media platforms, various private sector organizations, and civil society to suggest and discuss actions for all parts of society, and multiple related professional and scientific disciplines, methods, and technologies. A total of 594 ideas for actions were crowdsourced online during the discussions and consolidated into suggestions for an infodemic management framework. ResultsThe analysis team distilled the suggestions into a set of 50 proposed actions for a framework for managing infodemics in health emergencies. The consultation revealed six policy implications to consider. First, interventions and messages must be based on science and evidence, and must reach citizens and enable them to make informed decisions on how to protect themselves and their communities in a health emergency. Second, knowledge should be translated into actionable behavior-change messages, presented in ways that are understood by and accessible to all individuals in all parts of all societies. Third, governments should reach out to key communities to ensure their concerns and information needs are understood, tailoring advice and messages to address the audiences they represent. Fourth, to strengthen the analysis and amplification of information impact, strategic partnerships should be formed across all sectors, including but not limited to the social media and technology sectors, academia, and civil society. Fifth, health authorities should ensure that these actions are informed by reliable information that helps them understand the circulating narratives and changes in the flow of information, questions, and misinformation in communities. Sixth, following experiences to date in responding to the COVID-19 infodemic and the lessons from other disease outbreaks, infodemic management approaches should be further developed to support preparedness and response, and to inform risk mitigation, and be enhanced through data science and sociobehavioral and other research. ConclusionsThe first version of this framework proposes five action areas in which WHO Member States and actors within society can apply, according to their mandate, an infodemic management approach adapted to national contexts and practices. Responses to the COVID-19 pandemic and the related infodemic require swift, regular, systematic, and coordinated action from multiple sectors of society and government. It remains crucial that we promote trusted information and fight misinformation, thereby helping save lives.

In just a short period, social media have altered many aspects of our daily lives, from how we form and maintain social relationships to how we discover, access, and share information online. Now social media are also affecting how we teach and learn. In this paper, we discuss methods that can help researchers and educators evaluate and understand the observed and potential use of social media for teaching and learning through content and network analyses of social media texts and networks. This paper is based on a workshop given at the 2014 Learning Analytics and Knowledge conference, and presents an overview of the measures and potential of a multi-method approach for studying learning via social media. The theoretical discussion is augmented with study of the case of Twitter discussion from a cMOOC class.

The study uses 31 semi-structured interviews to explore users' motivations for adopting and using blockchain-based social media (BSM) platforms. The objective of the study is twofold—to collect empirical data on early adopters of BSM and to test the applicability of the Unified Theory of Acceptance and Use of Technology (UTAUT) model for explaining why some users are choosing BSM over mainstream social media (MSM) platforms. Manual content analysis of the interviews reveals that users are initially drawn to BSM due to social influence and financial incentives, but they continue to use it mainly because of the sense of community they experience. We also find that the steep learning curve, the absence of content moderation, as well as security and privacy concerns hinder the widespread adoption of these platforms. From the theoretical side, although the UTAUT model is generally suitable for examining why individuals use BSM, we suggest integrating two additional factors into the model: financial incentives and content moderation. [ABSTRACT FROM AUTHOR]

Learning on and through social media is becoming a cornerstone of lifelong learning, creating places not only for accessing information, but also for finding other self-motivated learners. Such is the case for Reddit, the online news sharing site that is also a forum for asking and answering questions. We studied learning practices found in 'Ask' subreddits AskScience, Ask_Politics, AskAcademia, and AskHistorians to develop a coding schema for informal learning. This paper describes the process of evaluating and defining a workable coding schema, one that started with attention to learning processes associated with discourse, exploratory talk, and conversational dialogue, and ended with including norms and practices on Reddit and the support of communities of inquiry. Our 'learning in the wild' coding schema contributes a content analysis schema for learning through social media, and an understanding of how knowledge, ideas, and resources are shared in open, online learning forums.

While there is a growing body of literature on information privacy suggesting different mechanisms of how people's privacy concerns might be impacting their attitudes and behaviour when using social media, recent questionable data use practices by social media platforms and third parties call for a renewed validation of existing information privacy models. The objective of this research is to re-examine the variables predicting why people disclose information on social media. Building on previous work, this paper puts forward a comprehensive Privacy Concerns and Social Media Use Model (PC-SMU) and evaluates it in a specific cultural and legal environment (social media users from a single county, Canada). The study delves into the privacy paradox and shows that the benefits of using social media are the main driver of self-disclosure, and that self-disclosing behaviours are nuanced by the users' information privacy protection strategies. We also find that higher levels of social media literacy, and concerns about organisational threats to a lesser extent, lead to higher levels of information privacy management, emphasizing the importance of educating users about how to use the different privacy and security features provided by social media platforms. [ABSTRACT FROM AUTHOR]