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1. Let's Talk about Sext: How Adolescents Seek Support and Advice about Their Online Sexual Experiences

   https://doi.org/10.1145/3313831.3376400  

   Razi, Afsaneh ; Badillo-Urquiola, Karla ; Wisniewski, Pamela J. ( April 2020 , Let’s Talk about Sext: How Teens Seek Support and Advice for Online Sexual Interactions)

   We conducted a thematic content analysis of 4,180 posts by adolescents (ages 12-17) on an online peer support mental health forum to understand what and how adolescents talk about their online sexual interactions. Youth used the platform to seek support (83%), connect with others (15%), and give advice (5%) about sexting, their sexual orientation, sexual abuse, and explicit content. Females often received unwanted nudes from strangers and struggled with how to turn down sexting requests from people they knew. Meanwhile, others who sought support complained that they received unwanted sexual solicitations while doing so—to the point that adolescents gave advice to one another on which users to stay away from. Our research provides insight into the online sexual experiences of adolescents and how they seek support around these issues. We discuss how to design peer-based social media platforms to support the well-being and safety of youth.
2. Seeing Should Probably not be Believing: The Role of Deceptive Support in COVID-19 Misinformation on Twitter

   https://doi.org/10.1145/3546914  

   Zuo, Chaoyuan ; Banerjee, Ritwik ; Shirazi, Hossein ; Chaleshtori, Fateme Hashemi ; Ray, Indrakshi ( August 2022 , Journal of Data and Information Quality)

   With the spread of the SARS-CoV-2, enormous amounts of information about the pandemic are disseminated through social media platforms such as Twitter. Social media posts often leverage the trust readers have in prestigious news agencies and cite news articles as a way of gaining credibility. Nevertheless, it is not always the case that the cited article supports the claim made in the social media post. We present a cross-genre ad hoc pipeline to identify whether the information in a Twitter post (i.e., a “Tweet”) is indeed supported by the cited news article. Our approach is empirically based on a corpus of over 46.86 million Tweets and is divided into two tasks: (i) development of models to detect Tweets containing claim and worth to be fact-checked and (ii) verifying whether the claims made in a Tweet are supported by the newswire article it cites. Unlike previous studies that detect unsubstantiated information by post hoc analysis of the patterns of propagation, we seek to identify reliable support (or the lack of it) before the misinformation begins to spread. We discover that nearly half of the Tweets (43.4%) are not factual and hence not worth checking – a significant filter, given the sheermore »volume of social media posts on a platform such as Twitter. Moreover, we find that among the Tweets that contain a seemingly factual claim while citing a news article as supporting evidence, at least 1% are not actually supported by the cited news, and are hence misleading.« less
3. Highlights and Outcomes of the 2021 Global Community Consultation

   https://doi.org/10.3897/biss.5.72716  

   Ellwood, Elizabeth R. ; Bentley, Andrew ; Buschbom, Jutta ; Hardisty, Alex ; Mast, Austin ; Miller, Joe ; Monfils, Anna ; Nelson, Gil ; Paul, Deborah L ( August 2021 , Biodiversity Information Science and Standards)

   International collaboration between collections, aggregators, and researchers within the biodiversity community and beyond is becoming increasingly important in our efforts to support biodiversity, conservation and the life of the planet. The social, technical, logistical and financial aspects of an equitable biodiversity data landscape – from workforce training and mobilization of linked specimen data, to data integration, use and publication – must be considered globally and within the context of a growing biodiversity crisis. In recent years, several initiatives have outlined paths forward that describe how digital versions of natural history specimens can be extended and linked with associated data. In the United States, Webster (2017) presented the “extended specimen”, which was expanded upon by Lendemer et al. (2019) through the work of the Biodiversity Collections Network (BCoN). At the same time, a “digital specimen” concept was developed by DiSSCo in Europe (Hardisty 2020). Both the extended and digital specimen concepts depict a digital proxy of an analog natural history specimen, whose digital nature provides greater capabilities such as being machine-processable, linkages with associated data, globally accessible information-rich biodiversity data, improved tracking, attribution and annotation, additional opportunities for data use and cross-disciplinary collaborations forming the basis for FAIR (Findable, Accessible, Interoperable,more »Reproducible) and equitable sharing of benefits worldwide, and innumerable other advantages, with slight variation in how an extended or digital specimen model would be executed. Recognizing the need to align the two closely-related concepts, and to provide a place for open discussion around various topics of the Digital Extended Specimen (DES; the current working name for the joined concepts), we initiated a virtual consultation on the discourse platform hosted by the Alliance for Biodiversity Knowledge through GBIF. This platform provided a forum for threaded discussions around topics related and relevant to the DES. The goals of the consultation align with the goals of the Alliance for Biodiversity Knowledge: expand participation in the process, build support for further collaboration, identify use cases, identify significant challenges and obstacles, and develop a comprehensive roadmap towards achieving the vision for a global specification for data integration. In early 2021, Phase 1 launched with five topics: Making FAIR data for specimens accessible; Extending, enriching and integrating data; Annotating specimens and other data; Data attribution; and Analyzing/mining specimen data for novel applications. This round of full discussion was productive and engaged dozens of contributors, with hundreds of posts and thousands of views. During Phase 1, several deeper, more technical, or additional topics of relevance were identified and formed the foundation for Phase 2 which began in May 2021 with the following topics: Robust access points and data infrastructure alignment; Persistent identifier (PID) scheme(s); Meeting legal/regulatory, ethical and sensitive data obligations; Workforce capacity development and inclusivity; Transactional mechanisms and provenance; and Partnerships to collaborate more effectively. In Phase 2 fruitful progress was made towards solutions to some of these complex functional and technical long-term goals. Simultaneously, our commitment to open participation was reinforced, through increased efforts to involve new voices from allied and complementary fields. Among a wealth of ideas expressed, the community highlighted the need for unambiguous persistent identifiers and a dedicated agent to assign them, support for a fully linked system that includes robust publishing mechanisms, strong support for social structures that build trustworthiness of the system, appropriate attribution of legacy and new work, a system that is inclusive, removed from colonial practices, and supportive of creative use of biodiversity data, building a truly global data infrastructure, balancing open access with legal obligations and ethical responsibilities, and the partnerships necessary for success. These two consultation periods, and the myriad activities surrounding the online discussion, produced a wide variety of perspectives, strategies, and approaches to converging the digital and extended specimen concepts, and progressing plans for the DES -- steps necessary to improve access to research-ready data to advance our understanding of the diversity and distribution of life. Discussions continue and we hope to include your contributions to the DES in future implementation plans.« less
4. Raiders of the lost kek: 3.5 years of augmented 4chan posts from the politically incorrect board

   Papasavva, A ; Zannettou, S. ; De Cristofaro, E. ; Stringhini, G. ; Blackburn, J. ( June 2020 , Proceedings of the International AAAI Conference on Weblogs and Social Media)

   This paper presents a dataset with over 3.3M threads and 134.5M posts from the Politically Incorrect board (/pol/) of the imageboard forum 4chan, posted over a period of almost 3.5 years (June 2016–November 2019). To the best of our knowledge, this represents the largest publicly available 4chan dataset, providing the community with an archive of posts that have been permanently deleted from 4chan and are otherwise inaccessible. We augment the data with a set of additional labels, including toxicity scores and the named entities mentioned in each post. We also present a statistical analysis of the dataset, providing an overview of what researchers interested in using it can expect, as well as a simple content analysis, shedding light on the most prominent discussion topics, the most popular entities mentioned, and the toxicity level of each post. Overall, we are confident that our work will motivate and assist researchers in studying and understanding 4chan, as well as its role on the greater Web. For instance, we hope this dataset may be used for cross-platform studies of social media, as well as being useful for other types of research like natural language processing. Finally, our dataset can assist qualitative work focusing onmore »in-depth case studies of specific narratives, events, or social theories.« less
5. Characterizing Twitter Users Who Engage in Adversarial Interactions against Political Candidates

   https://doi.org/https://doi.org/10.1145/3313831.3376548  

   Hua, Yiqing ; Naaman, Mor ; Ristenpart, Thomas ( April 2020 , Human factors in computing systems)

   Social media provides a critical communication platform for political figures, but also makes them easy targets for harassment. In this paper, we characterize users who adversarially interact with political figures on Twitter using mixed-method techniques. The analysis is based on a dataset of 400 thousand users' 1.2 million replies to 756 candidates for the U.S. House of Representatives in the two months leading up to the 2018 midterm elections. We show that among moderately active users, adversarial activity is associated with decreased centrality in the social graph and increased attention to candidates from the opposing party. When compared to users who are similarly active, highly adversarial users tend to engage in fewer supportive interactions with their own party's candidates and express negativity in their user profiles. Our results can inform the design of platform moderation mechanisms to support political figures countering online harassment.