bluuebunny/crossref_metadata_2025 huggingface dataset:
Getting Meta: A Multimodal Approach for Detecting Unsafe Conversations within Instagram Direct Messages of Youth
Authors: Ali Shiza , Razi Afsaneh , Kim Seunghyun , Alsoubai Ashwaq , Ling Chen , De Choudhury Munmun , Wisniewski Pamela J. , Stringhini Gianluca
Published: April 2023

Instagram, one of the most popular social media platforms among youth, has recently come under scrutiny for potentially being harmful to the safety and well-being of our younger generations. Automated approaches for risk detection may be one way to help mitigate some of these risks if such algorithms are both accurate and contextual to the types of online harms youth face on social media platforms. However, the imminent switch by Instagram to end-to-end encryption for private conversations will limit the type of data that will be available to the platform to detect and mitigate such risks. In this paper, we investigate which indicators are most helpful in automatically detecting risk in Instagram private conversations, with an eye on high-level metadata, which will still be available in the scenario of end-to-end encryption. Toward this end, we collected Instagram data from 172 youth (ages 13-21) and asked them to identify private message conversations that made them feel uncomfortable or unsafe. Our participants risk-flagged 28,725 conversations that contained 4,181,970 direct messages, including textual posts and images. Based on this rich and multimodal dataset, we tested multiple feature sets (metadata, linguistic cues, and image features) and trained classifiers to detect risky conversations. Overall, we found that the metadata features (e.g., conversation length, a proxy for participant engagement) were the best predictors of risky conversations. However, for distinguishing between risk types, the different linguistic and media cues were the best predictors. Based on our findings, we provide design implications for AI risk detection systems in the presence of end-to-end encryption. More broadly, our work contributes to the literature on adolescent online safety by moving toward more robust solutions for risk detection that directly takes into account the lived risk experiences of youth.
Hate Raids on Twitch: Echoes of the Past, New Modalities, and Implications for Platform Governance
Authors: Han Catherine , Seering Joseph , Kumar Deepak , Hancock Jeffrey T. , Durumeric Zakir
Published: April 2023

In the summer of 2021, users on the livestreaming platform Twitch were targeted by a wave of "hate raids," a form of attack that overwhelms a streamer's chatroom with hateful messages, often through the use of bots and automation. Using a mixed-methods approach, we combine a quantitative measurement of attacks across the platform with interviews of streamers and third-party bot developers. We present evidence that confirms that some hate raids were highly-targeted, hate-driven attacks, but we also observe another mode of hate raid similar to networked harassment and specific forms of subcultural trolling. We show that the streamers who self-identify as LGBTQ+ and/or Black were disproportionately targeted and that hate raid messages were most commonly rooted in anti-Black racism and antisemitism. We also document how these attacks elicited rapid community responses in both bolstering reactive moderation and developing proactive mitigations for future attacks. We conclude by discussing how platforms can better prepare for attacks and protect at-risk communities while considering the division of labor between community moderators, tool-builders, and platforms.
Having your Privacy Cake and Eating it Too: Platform-supported Auditing of Social Media Algorithms for Public Interest
Authors: Imana Basileal , Korolova Aleksandra , Heidemann John
Published: April 2023

Social media platforms curate access to information and opportunities, and so play a critical role in shaping public discourse today. The opaque nature of the algorithms these platforms use to curate content raises societal questions. Prior studies have used black-box methods led by experts or collaborative audits driven by everyday users to show that these algorithms can lead to biased or discriminatory outcomes. However, existing auditing methods face fundamental limitations because they function independent of the platforms. Concerns of potential harmful outcomes have prompted proposal of legislation in both the U.S. and the E.U. to mandate a new form of auditing where vetted external researchers get privileged access to social media platforms. Unfortunately, to date there have been no concrete technical proposals to provide such auditing, because auditing at scale risks disclosure of users' private data and platforms' proprietary algorithms. We propose a new method for platform-supported auditing that can meet the goals of the proposed legislation. The first contribution of our work is to enumerate the challenges and the limitations of existing auditing methods to implement these policies at scale. Second, we suggest that limited, privileged access to relevance estimators is the key to enabling generalizable platform-supported auditing of social media platforms by external researchers. Third, we show platform-supported auditing need not risk user privacy nor disclosure of platforms' business interests by proposing an auditing framework that protects against these risks. For a particular fairness metric, we show that ensuring privacy imposes only a small constant factor increase (6.34x as an upper bound, and 4× for typical parameters) in the number of samples required for accurate auditing. Our technical contributions, combined with ongoing legal and policy efforts, can enable public oversight into how social media platforms affect individuals and society by moving past the privacy-vs-transparency hurdle.
How Recent Migrants Develop Trust Through Community Commerce: The Emergence of Sociotechnical Adaptation
Authors: Hsiao Joey Chiao-Yin , Darling Sylvia , Dillahunt Tawanna R.
Published: April 2023

Trust is key to community commerce or peer-to-peer e-commerce where transactions happen within local communities. Trust is especially vital among migrants who move to new countries and need time to develop trust after arrival. To understand migrants' trust development in community commerce and its potential and challenges for supporting their transition to the United States, we conducted 24 semi-structured interviews with migrants who had lived there for three years or less. We highlight practices embedded in difficulties engaging with technologies in a new place. We identify four forms of migrants' trust and show how their offline experiences with local communities reflect their online trust development in community commerce and vice versa, thereby creating unique challenges in their adaptation to new technologies. We coin the term sociotechnical adaptation to frame migrants' distinctive adjustments to social media technologies in a new country. We conclude with implications for creating community commerce platforms that foster migrants' trust and a reflection on how sociotechnical adaptation may vary among diverse migrant populations.
Improving Human-AI Collaboration With Descriptions of AI Behavior
Authors: Cabrera Ángel Alexander , Perer Adam , Hong Jason I.
Published: April 2023

People work with AI systems to improve their decision making, but often under- or over-rely on AI predictions and perform worse than they would have unassisted. To help people appropriately rely on AI aids, we propose showing them behavior descriptions, details of how AI systems perform on subgroups of instances. We tested the efficacy of behavior descriptions through user studies with 225 participants in three distinct domains: fake review detection, satellite image classification, and bird classification. We found that behavior descriptions can increase human-AI accuracy through two mechanisms: helping people identify AI failures and increasing people's reliance on the AI when it is more accurate. These findings highlight the importance of people's mental models in human-AI collaboration and show that informing people of high-level AI behaviors can significantly improve AI-assisted decision making.
In the Age of Collaboration, the Computer-Aided Design Ecosystem is Behind: An Interview Study of Distributed CAD Practice
Authors: Cheng Kathy , Davis Michal K. , Zhang Xiyue , Zhou Shurui , Olechowski Alison
Published: April 2023

Computer-aided design (CAD) has become indispensable to increasingly collaborative hardware design processes. Despite the long-standing and growing need for collaboration with CAD models and tools, anecdotal reports and ongoing researcher efforts point to a complex and unresolved set of challenges faced by designers when working with distributed CAD. We aim to close this academic-practitioner knowledge gap through the first systematic study of professional user-driven CAD collaboration challenges. In this work, we conduct semi-structured interviews with 20 CAD professionals of diverse industries, roles, and experience levels to understand their collaborative workflows with distributed CAD tools. In total, we identify 14 challenges related to collaborative design, communication, data management, and permissioning that are currently impeding effective collaboration in professional CAD teams. Our systematic classification of CAD collaboration challenges presents a guide for pressing areas of future work, highlighting important implications for CAD researchers, practitioners, and tool builders to target new advancement in CAD infrastructure, management choices, and modelling best practices. With the insights gained from this work, we hope to ultimately improve collaboration efficiency, quality, and innovation for future product design teams.
Intelligent Coaching Systems: Understanding One-to-many Coaching for Ill-defined Problem Solving
Authors: Huang Evey Jiaxin , Rees Lewis Daniel , Gaudani Shubhanshi , Easterday Matthew , Gerber Elizabeth
Published: April 2023

One-to-many coaching is a common, yet difficult, coaching technique used in environments with many novices learning to solve ill-defined problems. Intelligent systems might be designed to support 1-to-many coaching but designing such systems requires a 1-to-many coaching model that details novices' challenges, coaches' strategies, and coaches' goals. To build such a model, we conducted interaction analysis on 24 1-to-many coaching sessions with novices developing new products in a university incubator and conducted retrospective analyses with 3 coaches and 30 novices. We contribute a model that demonstrates that coaches in a 1-to-many setting not only need to help novices develop metacognitive skills (just as in 1-to-1 coaching), but also need to utilize the presence and expertise of a group of novices to learn from each other, to mitigate their fear of failures, and provide them accountability. Our model informs design implications for future intelligent coaching systems to (1) assist coaches in monitoring and comparing many novices' progress, learning, and expertise; (2) provide novices with checklists, templates, and scaffolds to help them self-evaluate, seek-help, and summarize learning; (3) showcase failures and growth; and (4) publicize planning and progress to provide accountability.
Learning With Pedagogical Models: Videos As Adjuncts to Apprenticeship for Surgical Training
Authors: Ferrier-Barbut Eléonore , Avellino Ignacio , Canlorbe Geoffroy , Vitrani Marie-Aude , Luengo Vanda
Published: April 2023

Videos are a powerful media to learn activities through guided physical training such as surgery, especially when they are produced following human learning models and not as "how-to" videos. However, their success greatly depends on how they are integrated into the extensive curricula of domains where learning occurs through guided practice. In this work, we investigate the impact of integrating video as a learning tool into the learning curricula of surgery. We created a pedagogical video on surgical hysterectomy through a model based on the Conceptual Fields theory (Vergnaud) and performed two rounds of interviews with seven medical residents, who watched the video freely during their residency in gynecology-obstetrics as they trained with experts. We find that videos can complement guided physical training, as they can provide the rationale behind expert action, something that is difficult to explicit during guided training. Still, their linear and static nature limits their integration as true adjuncts. We discuss our vision of moving towards interactive videos created with an ontological approach, developed in a workshop with four expert surgeons, which involves the ability to navigate through levels of information and layers of representations, so that experts can represent information to learners according to pedagogical models that complement their complex and extensive learning curricula.
Mobilizing Manufactured Reality: How Participatory Disinformation Shaped Deep Stories to Catalyze Action during the 2020 U.S. Presidential Election
Authors: Prochaska Stephen , Duskin Kayla , Kharazian Zarine , Minow Carly , Blucker Stephanie , Venuto Sylvie , West Jevin D. , Starbird Kate
Published: April 2023

Claims of election fraud throughout the 2020 U.S. Presidential Election and during the lead up to the January 6, 2021 insurrection attempt have drawn attention to the urgent need to better understand how people interpret and act on disinformation. In this work, we present three primary contributions: (1) a framework for understanding the interaction between participatory disinformation and informal and tactical mobilization; (2) three case studies from the 2020 U.S. election analyzed using detailed temporal, content, and thematic analysis; and (3) a qualitative coding scheme for understanding how digital disinformation functions to mobilize online audiences. We combine resource mobilization theory with previous work examining participatory disinformation campaigns and "deep stories" to show how false or misleading information functioned to mobilize online audiences before, during, and after election day. Our analysis highlights how users on Twitter collaboratively construct and amplify alleged evidence of fraud that is used to facilitate action, both online and off. We find that mobilization is dependent on the selective amplification of false or misleading tweets by influencers, the framing around those claims, as well as the perceived credibility of their source. These processes are a self-reinforcing cycle where audiences collaborate in the construction of a misleading version of reality, which in turn leads to offline actions that are used to further reinforce a manufactured reality. Through this work, we hope to better inform future interventions.
"Oh yes! over-preparing for meetings is my jam :)": The Gendered Experiences of System Administrators
Authors: Kaur Mannat , Sri Ramulu Harshini , Acar Yasemin , Fiebig Tobias
Published: April 2023

In the system and network administration domain, gender diversity remains a distant target. The experiences and perspectives of sysadmins who belong to marginalized genders (non cis-men) are not well understood beyond the fact that sysadmin work environments are generally not equitable. We address this knowledge gap in our study by focusing on the ways in which sysadmins from marginalized genders manage their work in men-dominated sysadmin work spaces and by understanding what an inclusive workplace would look like. Using a feminist research approach, we engaged with a group of 16 sysadmins who are not cis-men via six online focus groups. We found that managing the impact of gender identity in the sysadmin workplace means demonstrating excellence and going above and beyond in system administration tasks, and also requires performing additional care work not expected from cis men. Furthermore, our participants handle additional layers of work due to gender considerations and to actively find community in the workplace. We found that sysadmins manage by going above and beyond in their tasks, performing care work and doing extra layers of work because of gender considerations, and finding community in the workplace. To mitigate this additional workload, we recommend more care for care work. For future research, we recommend the use of feminist lenses when studying sysadmin work in order to provide more equitable solutions that ultimately contribute to improving system security by fostering a just workplace.
On the Potential of Mediation Chatbots for Mitigating Multiparty Privacy Conflicts - A Wizard-of-Oz Study
Authors: Salehzadeh Niksirat Kavous , Korka Diana , Harkous Hamza , Huguenin Kévin , Cherubini Mauro
Published: April 2023

Sharing multimedia content, without obtaining consent from the people involved causes multiparty privacy conflicts (MPCs). However, social-media platforms do not proactively protect users from the occurrence of MPCs. Hence, users resort to out-of-band, informal communication channels, attempting to mitigate such conflicts. So far, previous works have focused on hard interventions that do not adequately consider the contextual factors (e.g., social norms, cognitive priming) or are employed too late (i.e., the content has already been seen). In this work, we investigate the potential of conversational agents as a medium for negotiating and mitigating MPCs. We designed MediationBot, a mediator chatbot that encourages consent collection, enables users to explain their points of view, and proposes solutions to finding a middle ground. We evaluated our design using a Wizard-of-Oz experiment with N = 32 participants, where we found that MediationBot can effectively help participants to reach an agreement and to prevent MPCs. It produced a structured conversation where participants had well-clarified speaking turns. Overall, our participants found MediationBot to be supportive as it proposes useful middle-ground solutions. Our work informs the future design of mediator agents to support social-media users against MPCs.
Opportunities for Social Media to Support Aspiring Entrepreneurs with Financial Constraints
Authors: Israni Aarti , Hui Julie , Dillahunt Tawanna R.
Published: April 2023

Social media offers an alternative source for entrepreneurs to expand their social networks and obtain relevant resources to support their ambitions. Aspiring entrepreneurs with limited access to resources and social networks might rely more on the opportunities that social media tools offer. Aspiring entrepreneurs navigate social media to realize their economic dreams. Yet, those who face financial constraints often face challenges. Because aspiring entrepreneurs are transitioning to entrepreneurship, they must construct and even adapt to new work-role identities and new requisite skills, behaviors, attitudes, and patterns of interactions. In a re-analysis of a sub-sample of data from two empirical studies, this work examines how aspiring entrepreneurs living in a financially-constrained environment seek informational, social, and emotional support online and navigate their transition to entrepreneurship. These entrepreneurs obtained informational and emotional resources from observing other members' posts in online communities, including the next steps needed to adapt to their desired small business work roles. However, few publicly disclosed their informational or emotional needs online. We extend existing research on financially-constrained entrepreneurs' use of social media, contributing insights into how these resource-seeking practices limit their exploration of alternative entrepreneurial identities and feedback. We also contribute design implications to facilitate their online disclosure practices, including offering suggestions about ways to respond to questions and other disclosures in ways that restore trust and mitigate identity threats.
PATHWiSE: An Authoring Tool to Support Teachers to Create Robot-Supported Social Learning Experiences During Homework
Authors: Hatch Paul , Rahman Md Anisur , Michaelis Joseph E.
Published: April 2023

Educational technologies can provide students with adaptive feedback and guidance, but these systems lack personal interactions that make social and cultural connections to the student's own classroom and prior experiences. Social or companion robots have a high capacity for these types of interactions, but typically require advanced levels of expertise to program. In this study, we examined teachers use of an authoring tool to enable them to leverage their classroom-based expertise to design robot-assisted homework assignments, and explore how seeing a robot enact their designs influences their work. We found that the tool enabled the teachers to create novel social interactions for homework activities that were similar to their classroom interaction patterns. These interaction designs evolved over time and were shaped by the teacher's emerging mental model of the social robot, their concept of the students' perspective of these interactions, and a shift towards informal classroom-like interaction paradigms, thus transforming their view of what they can achieve with homework. We discuss how these findings demonstrate how the context of the activity can influence initial mental models of social activities and suggest practical guidance on designing authoring tools to best facilitate the creation of computer or robot supported social activities, such as homework.
Seeing Like a Toolkit: How Toolkits Envision the Work of AI Ethics
Authors: Wong Richmond Y. , Madaio Michael A. , Merrill Nick
Published: April 2023

Numerous toolkits have been developed to support ethical AI development. However, toolkits, like all tools, encode assumptions in their design about what work should be done and how. In this paper, we conduct a qualitative analysis of 27 AI ethics toolkits to critically examine how the work of ethics is imagined and how it is supported by these toolkits. Specifically, we examine the discourses toolkits rely on when talking about ethical issues, who they imagine should do the work of ethics, and how they envision the work practices involved in addressing ethics. Among the toolkits, we identify a mismatch between the imagined work of ethics and the support the toolkits provide for doing that work. In particular, we identify a lack of guidance around how to navigate labor, organizational, and institutional power dynamics as they relate to performing ethical work. We use these omissions to chart future work for researchers and designers of AI ethics toolkits.
"Showing the Context": A Need for Oligopticonic Information Systems in Homelessness Measurement
Authors: Bopp Chris , Voida Amy
Published: April 2023

Organizations like businesses, governments, and nonprofits often have established milestones to stay focused on their strategic goals. However, public and social sector organizations often have goals that are difficult to measure. To better understand how data can be more sensitively appropriated in difficult-to-measure contexts, we conducted design workshops with 25 individuals with a stake in how homelessness is measured - including funders, staff and people experiencing homelessness. This study provides a detailed account of how diverse stakeholders measure progress towards these often difficult and vague goals. We found that the approaches to data collection fall under either the sociocentric perspective (which seeks to answer questions about community-level impact) or the egocentric perspective (which focuses more on the experience of the individual experiencing homelessness). We argue that in contexts where goals are vague and difficult to observe or measure, collaborative information systems should be approached by combining the sociocentric and egocentric perspectives into an oligopticon, rather than focusing only on the sociocentric perspective (which can be understood as a panopticon). As we outline, oligopticonic information systems have the capacity to deal with more diverse types of data and experiences by embracing the requirements that we have outlined.
Side-by-Side vs Face-to-Face: Evaluating Colocated Collaboration via a Transparent Wall-sized Display
Authors: Gong Jiangtao , Sun Jingjing , Chu Mengdi , Wang Xiaoye , Luo Minghao , Lu Yi , Zhang Liuxin , Wu Yaqiang , Wang Qianying , Liu Can
Published: April 2023

Traditional wall-sized displays mostly only support side-by-side co-located collaboration, while transparent displays naturally support face-to-face interaction. Many previous works assume transparent displays support collaboration. Yet it is unknown how exactly its afforded face-to-face interaction can support loose or close collaboration, especially compared to the side-by-side configuration offered by traditional large displays. In this paper, we used an established experimental task that operationalizes different collaboration coupling and layout locality, to compare pairs of participants collaborating side-by-side versus face-to-face in each collaborative situation. We compared quantitative measures and collected interview and observation data to further illustrate and explain our observed user behavior patterns. The results showed that the unique face-to-face collaboration brought by transparent display can result in more efficient task performance, different territorial behavior, and both positive and negative collaborative factors. Our findings provided empirical understanding about the collaborative experience supported by wall-sized transparent displays and shed light on its future design.
Social Media is not a Health Proxy: Differences Between Social Media and Electronic Health Record Reports of Post-COVID Symptoms
Authors: Pater Jessica A , Coupe Amanda , Nova Fayika Farhat , Pfafman Rachel , Carroll Jeanne , Brouwer Abigal , Bohn Camden , Li Jason , Todd Noah , Chang Fen Lei , Guha Shion
Published: April 2023

The COVID-19 pandemic transformed many aspects of health and daily life. A subset of people who were infected with the virus have ongoing chronic health issues that range in type of symptom and severity. In this study, we conducted a qualitative assessment of self-reported post-COVID symptoms from patients' electronic health records (EHR, n=564) and a randomized collection of Reddit and Twitter posts (n=500 for each). We show the inconsistencies in what types of symptoms are shared between platforms in addition to assessing the severity of the symptoms and how social media characterizations of post-COVID do not tell a complete story of this phenomenon. This research contributes to CSCW health literature by connecting digital traces of post-COVID with EHR data, critiquing the use of social media as a health proxy and points to its potential to add context to the analysis of traditional health data extracted from the EHR.
"Strike at the Root": Co-designing Real-Time Social Media Interventions for Adolescent Online Risk Prevention
Authors: Agha Zainab , Badillo-Urquiola Karla , Wisniewski Pamela J.
Published: April 2023

Adolescent online safety researchers have emphasized the importance of moving beyond restrictive and privacy invasive approaches to online safety, towards resilience-based approaches for empowering teens to deal with online risks independently. Unfortunately, many of the existing online safety interventions are focused on parental mediation and not contextualized to teens' personal experiences online; thus, they do not effectively cater to the unique needs of teens. To better understand how we might design online safety interventions that help teens deal with online risks, as well as when and how to intervene, we must include teens as partners in the design process and equip them with the skills needed to contribute equally to the design process. As such, we conducted User Experience (UX) bootcamps with 21 teens (ages 13-17) to first teach them important UX design skills using industry standard tools, so they could create storyboards for unsafe online interactions commonly experienced by teens and high-fidelity, interactive prototypes for dealing with these situations. Based on their storyboards, teens often encountered information breaches and sexual risks with strangers, as well as cyberbullying from acquaintances or friends. While teens often blocked or reported strangers, they struggled with responding to risks from friends or acquaintances, seeking advice from others on the best action to take. Importantly, teens did not find any of the existing ways for responding to these risks to be effective in keeping them safe. When asked to create their own design-based interventions, teens frequently envisioned "nudges" that occurred in real-time. Interestingly, teens more often designed for risk prevention (rather than risk coping) by focusing on nudging the risk perpetrator (rather than the victim) to rethink their actions, block harmful actions from occurring, or penalizing perpetrators for inappropriate behavior to prevent it from happening again in the future. Teens also designed personalized sensitivity filters to provide teens the ability to manage content they wanted to see online. Some teens also designed personalized nudges, so that teens could receive intelligent, guided advice from the platform that would help them know how to handle online risks themselves without intervention from their parents. Our findings highlight how teens want to address online risks "at the root" by putting the onus of risk prevention on those who perpetrate them - rather than on the victim. Our work is the first to leverage co-design with teens to develop novel online safety interventions that advocate for a paradigm shift from youth risk protection to promoting good digital citizenship.
The Information Ecosystem of Conspiracy Theory: Examining the QAnon Narrative on Facebook
Authors: Kim Soojong , Kim Jisu
Published: April 2023

There has been concern about the proliferation of the "QAnon" conspiracy theory on Facebook, but little is known about how its misleading narrative propagated on the world's largest social media platform. Thus, the present research analyzed content generated by 2,813 Facebook pages and groups that contributed to promoting the conspiracy narrative between 2017 and 2020. The result demonstrated that activities of QAnon pages and groups started a significant surge months before the 2020 U.S. Presidential Election. We found that these pages and groups increasingly relied on internal sources, i.e., Facebook accounts or their content on the platform, while their dependence on external information sources decreased continuously since 2017. It was also found that QAnon posts based on the Facebook internal sources attracted significantly more shares and comments compared with other QAnon posts. These findings suggest that QAnon pages and groups increasingly isolated themselves from sources outside Facebook while having more internal interactions within the platform, and the endogenous creation and circulation of disinformation might play a significant role in boosting the influence of the misleading narrative within Facebook. The findings imply that the efforts to tackle disinformation on social media should target not only the cross-platform infiltration of falsehood but also the intra-platform production and propagation of disinformation.
The Value of Activity Traces in Peer Evaluations: An Experimental Study
Authors: Shi Wenxuan Wendy , Krishna Kumaran Sneha R. , Sundaram Hari , Bailey Brian P.
Published: April 2023

Peer evaluations are a well-established tool for evaluating individual and team performance in collaborative contexts, but are susceptible to social and cognitive biases. Current peer evaluation tools have also yet to address the unique opportunities that online collaborative technologies provide for addressing these biases. In this work, we explore the potential of one such opportunity for peer evaluations: data traces automatically generated by collaborative tools, which we refer to as "activity traces". We conduct a between-subjects experiment with 101 students and MTurk workers, investigating the effects of reviewing activity traces on peer evaluations of team members in an online collaborative task. Our findings show that the usage of activity traces led participants to make more and greater revisions to their evaluations compared to a control condition. These revisions also increased the consistency and participants' perceived accuracy of the evaluations that they received. Our findings demonstrate the value of activity traces as an approach for performing more reliable and objective peer evaluations of teamwork. Based on our findings as well as qualitative analysis of free-form responses in our study, we also identify and discuss key considerations and design recommendations for incorporating activity traces into real-world peer evaluation systems.
Toward Supporting Perceptual Complementarity in Human-AI Collaboration via Reflection on Unobservables
Authors: Holstein Kenneth , De-Arteaga Maria , Tumati Lakshmi , Cheng Yanghuidi
Published: April 2023

In many real world contexts, successful human-AI collaboration requires humans to productively integrate complementary sources of information into AI-informed decisions. However, in practice human decision-makers often lack understanding of what information an AI model has access to, in relation to themselves. There are few available guidelines regarding how to effectively communicate aboutunobservables: features that may influence the outcome, but which are unavailable to the model. In this work, we conducted an online experiment to understand whether and how explicitly communicating potentially relevant unobservables influences how people integrate model outputs and unobservables when making predictions. Our findings indicate that presenting prompts about unobservables can change how humans integrate model outputs and unobservables, but do not necessarily lead to improved performance. Furthermore, the impacts of these prompts can vary depending on decision-makers' prior domain expertise. We conclude by discussing implications for future research and design of AI-based decision support tools.
Understanding Disclosure and Support for Youth Mental Health in Social Music Communities
Authors: Jin Yucheng , Cai Wanling , Chen Li , Dai Yuwan , Jiang Tonglin
Published: April 2023

Online music platforms that include social networking features sometimes become supportive social communities where young people can disclose their emotional distress and receive support. However, few studies have examined young people's disclosure in social music communities or the support they provide or receive. In this study, which focuses on a large online music platform as a research site, we used mixed methods to analyze young users' comments (N = 163) and the associated replies (N = 2,732) related to their psychological distress (e.g., depression, anxiety, stress, and loneliness). We found that the main types of comments involved experience sharing, and these comments often invoked peer support in the form of encouragement, caring, or self-disclosure. We also conducted an interview study with 13 young users of our research site to understand their perceptions of and motives for engaging in disclosure and support. The interviewees stated that music-induced and comment-induced emotional resonance was the main reason for their disclosure and support. Finally, we discussed the implications of our findings for designing a supportive social music community to benefit youth mental health.
Understanding Safety Risks and Safety Design in Social VR Environments
Authors: Zheng Qingxiao , Xu Shengyang , Wang Lingqing , Tang Yiliu , Salvi Rohan C. , Freeman Guo , Huang Yun
Published: April 2023

Understanding emerging safety risks in nuanced social VR spaces and how existing safety features are used is crucial for the future development of safe and inclusive 3D social worlds. Prior research on safety risks in social VR is mainly based on interview or survey data about social VR users' experiences and opinions, which lacks "in-situ observations" of how individuals react to these risks. Using two empirical studies, this paper seeks to understand safety risks and safety design in social VR. In Study 1, we investigated 212 YouTube videos and their transcripts that document social VR users' immediate experiences of safety risks as victims, attackers, or bystanders. We also analyzed spectators' reactions to these risks shown in comments to the videos. In Study 2, we summarized 13 safety features across various social VR platforms and mapped how each existing safety feature in social VR can mitigate the risks identified in Study 1. Based on the uniqueness of social VR interaction dynamics and users' multi-modal simulated reactions, we call for further re-thinking and re-approaching safety designs for future social VR environments and propose potential design implications for future safety protection mechanisms in social VR.
Wisdom of Two Crowds: Misinformation Moderation on Reddit and How to Improve this Process---A Case Study of COVID-19
Authors: Bozarth Lia , Im Jane , Quarles Christopher , Budak Ceren
Published: April 2023

Past work has explored various ways for online platforms to leverage crowd wisdom for misinformation detection and moderation. Yet, platforms often relegate governance to their communities, and limited research has been done from the perspective of these communities and their moderators. How is misinformation currently moderated in online communities that are heavily self-governed? What role does the crowd play in this process, and how can this process be improved? In this study, we answer these questions through semi-structured interviews with Reddit moderators. We focus on a case study of COVID-19 misinformation. First, our analysis identifies a general moderation workflow model encompassing various processes participants use for handling COVID-19 misinformation. Further, we show that the moderation workflow revolves around three elements: content facticity, user intent, and perceived harm. Next, our interviews reveal that Reddit moderators rely on two types of crowd wisdom for misinformation detection. Almost all participants are heavily reliant on reports from crowds of ordinary users to identify potential misinformation. A second crowd--participants' own moderation teams and expert moderators of other communities--provide support when participants encounter difficult, ambiguous cases. Finally, we use design probes to better understand how different types of crowd signals---from ordinary users and moderators---readily available on Reddit can assist moderators with identifying misinformation. We observe that nearly half of all participants preferred these cues over labels from expert fact-checkers because these cues can help them discern user intent. Additionally, a quarter of the participants distrust professional fact-checkers, raising important concerns about misinformation moderation.
Increasing Gas Production of Continuous Freeze-Thaw Hydrate Deposits Based on Local Reservoir Reconstruction
Authors: Shen Pengfei , Mao Xiyu , Cui Chaoqun , Li Xinwang , Li Meng , Chen Li , Liu Dandan
Published: April 2023

The fracturing technology for increasing gas production based on hydrate reservoir reconstruction has been proven to have the application prospect of hydrate production. The main content of this work is to study the influence mechanism between multiple production wells after fracturing the reservoirs around horizontal wells. Simulation results indicated that the gas production rates and cumulative volume of released gas by using hydraulic fracturing were both higher than that by using the traditional depressurization method. The average gas-to-water ratio in this work has broken through the technical bottleneck of exploiting hydrate only by the traditional depressurization method. After the rock matrix around the horizontal well was fractured, the permeability of the reservoir in the fracturing area would be increased; thus, the propagation distance of pressure drop would be promoted. In addition, the penetration of the hydrate decomposition area between horizontal production wells was conducive to promoting the flow of decomposed gas and water to production wells. Besides, the hydraulic fracturing method to increase the permeability of the reservoir around the production well is very effective for the gas production of low-permeability natural hydrate deposits. The best distance between production wells was recommended to be 45~60 m, and it was recommended to provide appropriate heat in the area between the two wells to accelerate the decomposition of hydrate.
A Generalization of Hermite–Hadamard–Fejer Type Inequalities for the
p
-Convex Function via
α
-Generator
Authors: Ünlüyol Erdal , Erdaş Yeter
Published: April 2023

In the

17

t
h

century, I. Newton and G. Leibniz found independently each other the basic operations of calculus, i.e., differentiation and integration. And this development broke new ground in mathematics. From 1967 to 1970, Michael Grossman and Robert Katz gave definitions of a new kind of derivative and integral, converting the roles of subtraction and addition into division and multiplication, respectively. And then they generalised this operation. Later, they named this analysis non-Newtonian calculus. This calculus is basically generated by generators. So, in this article, first, we give the definition of the

p

-convex function due to

α

-generator. Second, we obtain some new theorems for this function with respect to the

α

-generator. Third, we get some new theorems using Hermite–Hadamard–Fejer inequality for the

α

p

-convex function. Finally, we show that our obtained results are reduced to the classical case in the special conditions.
Dual Toeplitz Operators on the Orthogonal Complement of the Fock–Sobolev Space
Authors: He Li , Wu Biqian
Published: April 2023

In this paper, we consider the dual Toeplitz operators on the orthogonal complement of the Fock–Sobolev space and characterize their boundedness and compactness. It turns out that the dual Toeplitz operator

S

f

is bounded if and only if

f
∈

L

∞

, and

S

f

=

f

∞

. We also obtain that the dual Toeplitz operator with

L

∞

symbol on orthogonal complement of the Fock–Sobolev space is compact if and only if the corresponding symbol is equal to zero almost everywhere.
A Systematic Review of Weight-Based Metoprolol for Acute Atrial Fibrillation with Rapid Ventricular Rate
Authors: Burum Alexandra , Carino Jasmine , McBeth Mackenzie , Samuel Nephy , Hintze Trager D.
Published: April 2023

Atrial fibrillation (AF) is the most common cardiac arrhythmia encountered in the emergency department (ED) and when patients present in acute AF with rapid ventricular rate (RVR), it can result in significant morbidity and mortality. Primary treatment modalities are aimed at rate control with the two most common agents being intravenous metoprolol and diltiazem. Some evidence suggests that diltiazem may be more effective at controlling rate in these patients; however, the dosing strategies, pharmacologic differences, and study designs may play a role in the observation of these differences. The purpose of this article is to review the evidence for using weight-based metoprolol in the treatment of AF with RVR. The vast majority of studies comparing metoprolol and diltiazem for the treatment of acute AF with RVR compare a flat dose of metoprolol to a weight-based dose of diltiazem. Following a comprehensive review, only two studies have compared a weight-based dosing strategy of intravenous (IV) metoprolol versus IV diltiazem for this disease state. Overall, the two studies only contained 94 patients and failed to meet power. Beyond differing dosing strategies, differences in pharmacokinetics between the two medications (like the onset of action and metabolism) could have played a role in the differences observed in the studies. Further studies are warranted to provide better guidance on which agent should be used in the treatment of acute AF with RVR.
Design and Optimization of Blockchain-Based Distributed Data-Sharing System for Urban Rail Transit
Authors: Chen Mo , Jiang Hailin , Zhao Hongli , Zuo Huijun , Zhang Qiang
Published: April 2023

With the wide application of data-driven intelligence technology, the management efficiency and quality of urban rail transit improve considerably. However, due to data privacy and security protection, a large amount of data is still scattered among operators or rail transit departments in the form of data islands. The data barriers between urban rail departments severely hinder the intelligent development of urban rail transit systems. In this study, we design a distributed data-sharing system based on blockchain for urban rail transit system. Data production node in urban rail department, such as servers in data centers, wayside equipment, and onboard equipment, can share their data in a distributed way. Blockchain provides audit and check functions to guarantee data-sharing security. We explore the data-sharing incentive mechanism which has an impact on sharing willingness of data production nodes. To maximize the individual utility of nodes, we formulate an evolutionary game model for data nodes with bounded rationality to adapt their sharing strategies. The uniqueness and stability of the equilibrium of the game are also analyzed theoretically. Extensive experiments are conducted and illustrated that data production nodes can share their data efficiently and safely in our proposed data-sharing system. Our proposed evolutionary game model can determine the most effective data-sharing incentive mechanism.
Simple One-Step Synthesis of Nipa Frond-Derived Magnetic Porous Carbon for Decolorization of Acid Yellow 23
Authors: Nguyen Linh Thi Kim , Nguyen Long Quang , Nguyen Hung Minh , Nguyen Thuan Minh , Lam Hung Hoa , Tran-Thuy Tuyet-Mai , Nguyen Dung Van
Published: April 2023

Nipa is an abundant, underutilized palm whose major part is its fronds. Nipa fronds (NF) were, therefore, valorized as a renewable carbon resource for the preparation of advanced magnetic porous carbon (MPC) via simple one-step pyrolysis with FeCl3 addition as a magnetic precursor. Properties of the obtained material were determined by X-ray diffraction (XRD), nitrogen adsorption and desorption isotherms, vibrating sample magnetometer (VSM), scanning electron microscopy (SEM) images, energy-dispersive X-ray (EDX) spectroscopy, and Fourier-transform infrared (FTIR) spectroscopy. XRD results showed that Fe3O4 along with Fe0 particles were formed in the porous carbon base. FeCl3-activation of NF yielded MPC with a high specific surface area (SBET) of 330 m2/g, a large total pore volume (Vtotal) of 0.26 cm3/g, and a strong specific saturation magnetization of 7.65 emu/g. Subsequently, MPC was explored for the removal of acid yellow 23 (AY23) using H2O2 as an oxidation agent. Before H2O2 addition, MPC (0.80 g/L) at pH 3.0 partly eliminated AY23 (initial 100 ppm) with an adsorption capacity of 14.5 mg/g. In further catalytic oxidation with 200 ppm of H2O2, MPC removed 89.1% of AY23 within 120 min. Moreover, AY23 decolorization with different MPC samples obeyed pseudo-first-order kinetics, with the greatest rate constant being 0.0186 min−1. Interestingly, the utilized MPC samples could be easily removed from the treated media using a magnet. Altogether, the findings suggest that low-cost magnetic porous carbon produced from one-step pyrolysis of FeCl3-loaded nipa frond might be applied to the treatment of acid yellow 23 in wastewater due to its relative adsorption capacity, efficient catalytic performance, and powerful magnetic separability.