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Mental health in LGBTQ+ community is often challenged by stigma, prejudice, and discrimination. The "social distancing" public health measures during COVID-19 epidemic have exacerbated the trend. During the pandemic, many took to social media as an outlet for sharing their feelings and in search of connection. Social media may help alleviate loneliness—an increasingly prevalent condition associated with both physical and mental health issues. In this study, we examine 147,736 Twitter posts mentioning loneliness by users who self-identify as part of the LGBTQ+ community, posted before and during the COVID-19 lockdowns. We find that, compared to the year before COVID-19, these users posted 67% more loneliness self-disclosures during the first year of COVID-19. Examining the emotional content of these tweets, we find frequent references to depression, dysphoria, and suicidal ideation. During COVID-19, the users mentioned more "pain" and "numbness" in association with the lack of social and physical contact. However, many found Twitter to be a safe space to express these feelings. The replies to these disclosures were rare: only about 29% received one. Using a large dataset of self-disclosures, we reveal quantitatively and qualitatively the disclosure around loneliness by LGBTQ+ users at an unprecedented time of social isolation. [ABSTRACT FROM AUTHOR]

This study explores the effect of unprecedented mass isolation during COVID-19 lockdowns through the lens of self-disclosure of loneliness on Twitter. Using a dataset of 30 million public tweets, we use machine learning to identify tweets that contain self-disclosure of loneliness. We find that thousands more people turned to Twitter to express their loneliness during the lockdowns; however, this effect normalized within a month, demonstrating the "ordinization" effect on a collective level. Furthermore, lockdown brought a marked shift in the weekly timings of posting and a change in the accompanying emotions, which were more positive and other-focused. Finally, based on a qualitative analysis, we propose an updated typology of loneliness that captures the possibilities offered by the affordances of social media. Our findings illustrate the profound effect lockdowns had on the societal psychological state and emphasize the importance of mental health resources during extreme and isolating events. [ABSTRACT FROM AUTHOR]

Introduction: Loneliness has been shown to affect both mental and physical health, and was a major concern even before the COVID-19 pandemic. During the COVID-19 distancing measures, millions of people took to social media to express their feelings and seek social support. Methods: In this mixed-methods study, we examine the self-disclosure of loneliness by users identifying as male or female (via self-disclosed naming conventions) on Twitter before and during the COVID-19 "lockdowns". Results: We show that in the first two months of COVID-19 restrictions, selfdisclosure of loneliness on this platform rose dramatically, and also have changed qualitatively. We find that female accounts tend to post more loneliness self-disclosures compared to male ones, even before COVID. Female disclosures more often center around pregnancy, family, and close relationships, whereas those posted by the male ones are more related to leadership, video gaming and sex. During COVID lockdowns, female accounts turn to online messaging apps and hobbies, and male become increasingly vocal in seeking partners. Discussion: The insights of this study have important implications for the design of interventions for lessening the burden of loneliness in the current digitized world. [ABSTRACT FROM AUTHOR]

The workshop program of the Association for the Advancement of Artificial Intelligence's Fourteenth International Conference on Web and Social Media was held June 8 to 20, 2020. The conference venue, which had originally been Atlanta, Georgia, USA, had to be revamped into a virtual edition, due to the 2019 Corona Virus Disease pandemic. There were five full-day workshops in the program. They included Emoji Understanding and Applications in Social Media (W1), Social Sensing: Narrative Analysis on Social Media (W2), News and Public Opinion (W3), Cyber Social Threats (W4), and Mediate: Social and News Media Misinformation (W5). This report contains summaries of all five workshops. [ABSTRACT FROM AUTHOR]

The workshop program of the Association for the Advancement of Artifi- cial Intelligence's 13th International Conference on Web and Social Media was held at the Bavarian School of Public Policy in Munich, Germany on June 11, 2019. There were five full-day workshops, one half-day workshop, and the annual evening Science Slam in the program. The proceedings of the workshops were published in Research Topic of the Frontiers in Big Data. This report contains summaries of those workshops. [ABSTRACT FROM AUTHOR]

The article discusses the highlights of the workshop program of the Association for the Advancement of Artificial Intelligence's 12th International Conference on Web and Social Media (AAAI-18) held at Stanford University, in Stanford, California on June 25, 2018. Topics discussed include the Algorithmic Personalization and News workshop, the Beyond Online Data workshop and the Bridging the Gaps workshop.

The 2015 workshops at the International AAAI Conference on Web and Social Media were held on May 26 in Oxford, UK. The workshop program included seven workshops, including Auditing Algorithms from the Outside: Methods and Implications; Digital Placemaking: Augmenting Physical Places with Contextual Social Data; Modeling and Mining Temporal Interactions; Religion on Social Media; Standards and Practices in Large-Scale Social Media Research; the ICWSM Science Slam; and Wikipedia, a Social Pedia: Research Challenges and Opportunities. This article contains the written reports of six of the workshops. [ABSTRACT FROM AUTHOR]

Millions of people living with diabetes are using mobile phones, Internet and social media to socialize with other patients, share experience or search information relevant for their self-management. This phenomena is leading towards a new paradigm of hyper-connected diabetes digital self-management. This is also leading towards an explosion on data, a large amount of data is collected on populations around the world. This panel will address the opportunities this data presents, discuss the latest research that uses it, and the limitations and other concerns. [ABSTRACT FROM AUTHOR]