Suchergebnisse

Significance Online networks carry benefits and risks with high-stakes consequences during contentious political events: They can be tools for organization and awareness, or tools for disinformation and conflict. We combine social media and web-tracking data to measure differences on the visibility of news sources during two events that involved massive political mobilizations in two different countries and time periods. We contextualize the role of social media as an entry point to news, and we cast doubts on the impact that bot activity had on the coverage of those mobilizations. We show that verified, blue-badge accounts were significantly more visible and central. Our findings provide evidence to evaluate the role of social media in facilitating information campaigns and eroding traditional gatekeeping roles.

AbstractNowadays, scientific challenges usually require approaches that cross traditional boundaries between academic disciplines, driving many researchers towards interdisciplinarity. Despite its obvious importance, there is a lack of studies on how to quantify the influence of interdisciplinarity on the research impact, posing uncertainty in a proper evaluation for hiring and funding purposes. Here, we propose a method based on the analysis of bipartite interconnected multilayer networks of citations and disciplines, to assess scholars, institutions, and countries interdisciplinary importance. Using data about physics publications and US patents, we show that our method allows to reward, using a quantitative approach, scholars and institutions that have carried out interdisciplinary work and have had an impact in different scientific areas. The proposed method could be used by funding agencies, universities and scientific policy decision makers for hiring and funding purposes, and to complement existing methods to rank universities and countries.

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.

This deliverable aims to describe inDICEs' targeted methodologies of research and analysis, briefly describing the Methodological Toolbox as the set of targeted methodologies defined through an in-depth review of the current state of the art approaches, both in relation to the research questions and to the kind of available and acquired data and their structure. These are the main components of the Methodological Toolbox: inDICEs Theoretical Framework, Targeted strategies of data gathering and data analysis, Available datasets, Set of useful indicators. This set of methodologies is aimed at supplying inDICEs with new data in order to develop reports on CHI digitization status, to support the Self-assessment tool development, to populate the Observatory Platform and to offer insight in the understanding of the users' behaviour (in their use of different personas), as well as in the understanding of the social and economic impact of digitized culture as a basis for the design of evidence-based policies in the future context of the Digital Single Market (DSM). ; The research leading to these results has received funding from the European Union's Horizon 2020 Programme (H2020-DT-GOVERNANCE-13-2019) under grant agreement n° 870792.

This Deliverable aims to briefly describe the data collection processes, the datasets gathered and the preliminary data analysis on users' behavioural changes that were carried out by the WP1 working group. The inDICEs data collection processed and/or stored within the first 12 months of the project consists of: a) data analyzed as part of the inDICEs participatory platform, where results are made available through the Open Observatory b) data of relevance provided by third-parties such as Enumerate Nemo Eurostat State of the commons United Nations Conference on Trade and Developmen Digital Economy and Society Index EU open data portal c) online content gathered continuously, made accessible by means of the Visual Analytics Dashboard that covers: Online news and web sources Twitter posts Youtube videos Facebook pages d) FBK collected on-line datasets on cultural production, from the following sources: Wikipedia Tiktok Deviantart AllTheater IMDB and was gathered with the purpose to: a) monitor and analyze the state of cultural digitization via WLT analytical tools and through the Visual Analytical Dashboard, configured for culture-based web sources (news, websites, social networks, blogs, forums) and with domain-relevant keywords according to a series of pre-sets and new indicators [as described in Deliverable D1.1]. b) stimulate behavioural changes in the users of participatory platforms in order to favour production and access. To understand how this process of collective cultural production works, inDICEs chose Wikipedia as its first case study, in order to extract new useful indicators to fill the open Repository available for single researchers and institutes. ; This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 870792.

AbstractWe analyze social media activity during one of the largest protest mobilizations in US history to examine ideological asymmetries in the posting of news content. Using an unprecedented combination of four datasets (tracking offline protests, social media activity, web browsing, and the reliability of news sources), we show that there is no evidence of unreliable sources having any prominent visibility during the protest period, but we do identify asymmetries in the ideological slant of the sources shared on social media, with a clear bias towards right-leaning domains. These results support the "amplification of the right" thesis, which points to the structural conditions (social and technological) that lead to higher visibility of content with a partisan bent towards the right. Our findings provide evidence that right-leaning sources gain more visibility on social media and reveal that ideological asymmetries manifest themselves even in the context of movements with progressive goals.

Political and environmental factors—e.g., regional conflicts and global warming—increase large-scale migrations, posing extraordinary societal challenges to policymakers of destination countries. A common concern is that such a massive arrival of people—often from a country with a disrupted healthcare system—can increase the risk of vaccine-preventable disease outbreaks like measles. We analyze human flows of 3.5 million (M) Syrian refugees in Turkey inferred from massive mobile-phone data to verify this concern. We use multilayer modeling of interdependent social and epidemic dynamics to demonstrate that the risk of disease reemergence in Turkey, the main host country, can be dramatically reduced by 75 to 90% when the mixing of Turkish and Syrian populations is high. Our results suggest that maximizing the dispersal of refugees in the recipient population contributes to impede the spread of sustained measles epidemics, rather than favoring it. Targeted vaccination campaigns and policies enhancing social integration of refugees are the most effective strategies to reduce epidemic risks for all citizens.

Abstract
As the coronavirus disease 2019 spread globally, emerging variants such as B.1.1.529 quickly became dominant worldwide. Sustained community transmission favors the proliferation of mutated sub-lineages with pandemic potential, due to cross-national mobility flows, which are responsible for consecutive cases surge worldwide. We show that, in the early stages of an emerging variant, integrating data from national genomic surveillance and global human mobility with large-scale epidemic modeling allows to quantify its pandemic potential, providing quantifiable indicators for pro-active policy interventions. We validate our framework on worldwide spreading variants and gain insights about the pandemic potential of BA.5, BA.2.75, and other sub- and lineages. We combine the different sources of information in a simple estimate of the pandemic delay and show that only in combination, the pandemic potentials of the lineages are correctly assessed relative to each other. Compared to a country-level epidemic intelligence, our scalable integrated approach, that is pandemic intelligence, permits to enhance global preparedness to contrast the pandemic of respiratory pathogens such as SARS-CoV-2.

Background: An 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. Objective: A 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. Methods: A 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. Results: The 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. Conclusions: The 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. ; peer-reviewed