ABSTRACT
Issue The COVID-19 pandemic and current recovery efforts have been complicated by a parallel infodemic. The infodemic has manifested itself in the rapid spread of questions, concerns and misinformation that can affect population attitudes and behavior harmful to health -promoting stigma and discrediting science, non-recommended treatments and cures, politicizing health programs and eroding trust in health workers and health systems. Description WHO's COVID-19 Pillar 2 (risk communication, community engagement and infodemic management) developed an integrated public health infodemic insights methodology for weekly analysis of social media, traditional media and other data sources to identify, categorize, and understand the key concerns and narratives expressed, and inform risk communication and response activities. Results The infodemic characterization, integrated analysis and insights generation consisted of a 3-step mixed-methods approach. First, data was collected from publicly available social and news media and categorized into categories of conversations by a COVID-19 public health taxonomy. Second, the dataset was analyzed and compared week-on-week to identify changes in narratives and conversation sentiment. Third, the digital infodemic intelligence was reviewed by a group of subject matter experts and triangulated with other data sources to derive infodemic insights and provide recommendations for action for the week. The methodology has been applied to inform COVID-19 response, COVID-19 vaccine demand promotion, and preparing for mass gatherings or mass immunization campaigns. Lessons The methodology for infodemic intelligence generation and integration has introduced evidence-based analytical practices for generation of infodemic insights and recommendations for action into the work of WHO. It must be further adapted for use by different health programmes and preparedness functions, and is described WHO Field Infodemiology Manual. Key messages • Health authorities can use infodemic insights to respond to people’s concerns, questions and information deficits in a timely and effective manner. • An evidence-based methodology has been developed and validated to generate infodemic insights and recommendations for action during an acute health event or emergency.
ABSTRACT
Background COVID-19 pandemic was accompanied by an Infodemic (overabundance of information, including misinformation and disinformation, both online and offline);in response to this Infodemic, WHO launched the EARS platform (Early AI-assisted Response with Social Listening), showing real-time information about how people are talking about COVID-19 online. This information is intended to serve health information professionals to understand narratives and needs of the general public, in order to inform policy or communications decisions. Methods Data is collected daily from online conversations in publicly available sources, including Twitter, online forums, and blogs in English, French, Spanish and Portuguese, for 20 pilot countries. Once the data is collected, it is processed and classified into 39 categories, according to a set of pandemic public health taxonomy. The classification is made based on semi-supervised machine learning. Results Top 5 categories across regions are Covid-19 vaccine, Transmission settings, Personal measures, Testing and Industry (industry refers to the impact of the pandemic on the economy). We find that conversations around Covid-19 vaccines usually rank in the second or third position in all regions and represent 9%-12% of the conversation. Conclusions The configuration and application of the EARS platform has enabled progress towards more scalable and sustainable social listening to inform Infodemic management and response, compared to previous methods which were more manual, required data scientists in the team, or had fewer analytics capabilities. Future work will focus on gradually adding more data sources which can expand coverage and representativity. Key messages Discuss social listening methods for greater accountability to affected populations. Formulate insights into how digital media and information technology can be better utilized for more rapidly responding to the evolving needs of communities.
ABSTRACT
This special theme issue of Big Data & Society presents leading-edge, interdisciplinary research that focuses on examining how health-related (mis-)information is circulating on social media. In particular, we are focusing on how computational and Big Data approaches can help to provide a better understanding of the ongoing COVID-19 infodemic (overexposure to both accurate and misleading information on a health topic) and to develop effective strategies to combat it. © The Author(s) 2021.