355 research outputs found

    Pathways to Online Hate: Behavioural, Technical, Economic, Legal, Political & Ethical Analysis.

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    The Alfred Landecker Foundation seeks to create a safer digital space for all. The work of the Foundation helps to develop research, convene stakeholders to share valuable insights, and support entities that combat online harms, specifically online hate, extremism, and disinformation. Overall, the Foundation seeks to reduce hate and harm tangibly and measurably in the digital space by using its resources in the most impactful way. It also aims to assist in building an ecosystem that can prevent, minimise, and mitigate online harms while at the same time preserving open societies and healthy democracies. A non-exhaustive literature review was undertaken to explore the main facets of harm and hate speech in the evolving online landscape and to analyse behavioural, technical, economic, legal, political and ethical drivers; key findings are detailed in this report

    Social media mental health analysis framework through applied computational approaches

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    Studies have shown that mental illness burdens not only public health and productivity but also established market economies throughout the world. However, mental disorders are difficult to diagnose and monitor through traditional methods, which heavily rely on interviews, questionnaires and surveys, resulting in high under-diagnosis and under-treatment rates. The increasing use of online social media, such as Facebook and Twitter, is now a common part of people’s everyday life. The continuous and real-time user-generated content often reflects feelings, opinions, social status and behaviours of individuals, creating an unprecedented wealth of person-specific information. With advances in data science, social media has already been increasingly employed in population health monitoring and more recently mental health applications to understand mental disorders as well as to develop online screening and intervention tools. However, existing research efforts are still in their infancy, primarily aimed at highlighting the potential of employing social media in mental health research. The majority of work is developed on ad hoc datasets and lacks a systematic research pipeline. [Continues.]</div

    The IHI Rochester Report 2022 on Healthcare Informatics Research: Resuming After the CoViD-19

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    In 2020, the CoViD-19 pandemic spread worldwide in an unexpected way and suddenly modified many life issues, including social habits, social relationships, teaching modalities, and more. Such changes were also observable in many different healthcare and medical contexts. Moreover, the CoViD-19 pandemic acted as a stress test for many research endeavors, and revealed some limitations, especially in contexts where research results had an immediate impact on the social and healthcare habits of millions of people. As a result, the research community is called to perform a deep analysis of the steps already taken, and to re-think steps for the near and far future to capitalize on the lessons learned due to the pandemic. In this direction, on June 09th-11th, 2022, a group of twelve healthcare informatics researchers met in Rochester, MN, USA. This meeting was initiated by the Institute for Healthcare Informatics-IHI, and hosted by the Mayo Clinic. The goal of the meeting was to discuss and propose a research agenda for biomedical and health informatics for the next decade, in light of the changes and the lessons learned from the CoViD-19 pandemic. This article reports the main topics discussed and the conclusions reached. The intended readers of this paper, besides the biomedical and health informatics research community, are all those stakeholders in academia, industry, and government, who could benefit from the new research findings in biomedical and health informatics research. Indeed, research directions and social and policy implications are the main focus of the research agenda we propose, according to three levels: the care of individuals, the healthcare system view, and the population view

    Investigating the role of social media and smart device applications in understanding human-environment relationships in urban green spaces

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    Urban green spaces are integral components of urban landscapes and the cultural ecosystem services afforded to human populations by these green spaces are of particular relevance to human and societal well-being. Urban green spaces provide opportunities for human interaction, physical activity and recreation, stress alleviation and mental restoration, economic opportunity, cultural activities and interactions with nature. To understand how these benefits are received by human populations it is vital to understand when and how individuals interact with urban green spaces. The rapid development and uptake of technologies such as smart phones, social networks and apps provides new opportunity to investigate the human interactions occurring in urban green spaces. Using the city of Birmingham as a case study, this thesis aims (i) to demonstratedemonstrate the utility of data obtained from smart device enabled platforms (social networks and apps) in understanding socio-ecological interactions in urban areas and (ii) to evaluateevaluate the utility of these data sources for researchers and policy makers. The successful identification of a range of socio-ecological interaction suggest these data sources provide a viable method if investigating such interactions; however, there remain a number of limitations to consider to ensure they are employed appropriately in research contexts

    Representing Crowd Knowledge: Guidelines for Conceptual Modeling of User-generated Content

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    Organizations’ increasing reliance on externally produced information, such as online user-generated content (UGC) and crowdsourcing, challenges common assumptions about conceptual modeling in information systems (IS) development. We demonstrate UGC’s societal importance, analyze its distinguishing characteristics, identify specific conceptual modeling challenges in this setting, evaluate traditional and recently proposed approaches to modeling UGC, propose a set of conceptual modeling guidelines for developing IS that harness structured UGC, and demonstrate how to implement and evaluate the proposed guidelines using a case of development of a real crowdsourcing (citizen science) IS. We conclude by considering implications for conceptual modeling research and practice
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