Wanwan Li, Changyang Li, Minyoung Kim, Haikun Huang, L. Yu
The recent popularity of augmented reality (AR) devices has enabled players to participate in interactive narratives through virtual events and characters populated in a real-world environment, where different actions may lead to different story branches. In this paper, we propose a novel approach to adapt narratives to real spaces for AR experiences. Our optimization-based approach automatically assigns contextually compatible locations to story events, synthesizing a navigation graph to guide players through different story branches while considering their walking experiences. We validated the effectiveness of our approach for adapting AR narratives to different scenes through experiments and user studies.
{"title":"Location-Aware Adaptation of Augmented Reality Narratives","authors":"Wanwan Li, Changyang Li, Minyoung Kim, Haikun Huang, L. Yu","doi":"10.1145/3544548.3580978","DOIUrl":"https://doi.org/10.1145/3544548.3580978","url":null,"abstract":"The recent popularity of augmented reality (AR) devices has enabled players to participate in interactive narratives through virtual events and characters populated in a real-world environment, where different actions may lead to different story branches. In this paper, we propose a novel approach to adapt narratives to real spaces for AR experiences. Our optimization-based approach automatically assigns contextually compatible locations to story events, synthesizing a navigation graph to guide players through different story branches while considering their walking experiences. We validated the effectiveness of our approach for adapting AR narratives to different scenes through experiments and user studies.","PeriodicalId":314098,"journal":{"name":"Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131078384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alyxander Burns, C. Lee, Ria Chawla, Evan M. Peck, Narges Mahyar
As more people rely on visualization to inform their personal and collective decisions, researchers have focused on a broader range of audiences, including “novices.” But successfully applying, interrogating, or advancing visualization research for novices demands a clear understanding of what “novice” means in theory and practice. Misinterpreting who a “novice” is could lead to misapplying guidelines and overgeneralizing results. In this paper, we investigated how visualization researchers define novices and how they evaluate visualizations intended for novices. We analyzed 79 visualization papers that used “novice,” “non-expert,” “laypeople,” or “general public” in their titles or abstracts. We found ambiguity within papers and disagreement between papers regarding what defines a novice. Furthermore, we found a mismatch between the broad language describing novices and the narrow population representing them in evaluations (i.e., young people, students, and US residents). We suggest directions for inclusively supporting novices in both theory and practice.
{"title":"Who Do We Mean When We Talk About Visualization Novices?","authors":"Alyxander Burns, C. Lee, Ria Chawla, Evan M. Peck, Narges Mahyar","doi":"10.1145/3544548.3581524","DOIUrl":"https://doi.org/10.1145/3544548.3581524","url":null,"abstract":"As more people rely on visualization to inform their personal and collective decisions, researchers have focused on a broader range of audiences, including “novices.” But successfully applying, interrogating, or advancing visualization research for novices demands a clear understanding of what “novice” means in theory and practice. Misinterpreting who a “novice” is could lead to misapplying guidelines and overgeneralizing results. In this paper, we investigated how visualization researchers define novices and how they evaluate visualizations intended for novices. We analyzed 79 visualization papers that used “novice,” “non-expert,” “laypeople,” or “general public” in their titles or abstracts. We found ambiguity within papers and disagreement between papers regarding what defines a novice. Furthermore, we found a mismatch between the broad language describing novices and the narrow population representing them in evaluations (i.e., young people, students, and US residents). We suggest directions for inclusively supporting novices in both theory and practice.","PeriodicalId":314098,"journal":{"name":"Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131207045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Studies of mapper conflict in OpenStreetMap (OSM) have focused exclusively on cartographic vandalism and its effect on data quality. This paper takes a broader view on mapper conflict in OSM. Using a Delphi survey method, we collect qualitative data on perceived conflict from long-time OSM mappers. We ask mappers about four aspects of conflict in OSM: (1) topic of conflict, (2) factors leading to conflict, (3) effects of conflict, and (4) potential conflict management methods. Our results show that conflict in OSM can be explained by clashing values and opinions within and across different mapper subgroups and can be exacerbated by negative mapper behaviors. The boundaries of these subgroups, while implicit, are often defined by gender, mappers’ geographic location, level of expertise, and mappers’ professional affiliation. Based on these results, we discuss design options for OSM’s existing public communication channels that often become foci of mapper conflict management.
{"title":"Assessing Mapper Conflict in OpenStreetMap Using the Delphi Survey Method","authors":"Youjin Choe, Martin Tomko, Mohsen Kalantari","doi":"10.1145/3544548.3580758","DOIUrl":"https://doi.org/10.1145/3544548.3580758","url":null,"abstract":"Studies of mapper conflict in OpenStreetMap (OSM) have focused exclusively on cartographic vandalism and its effect on data quality. This paper takes a broader view on mapper conflict in OSM. Using a Delphi survey method, we collect qualitative data on perceived conflict from long-time OSM mappers. We ask mappers about four aspects of conflict in OSM: (1) topic of conflict, (2) factors leading to conflict, (3) effects of conflict, and (4) potential conflict management methods. Our results show that conflict in OSM can be explained by clashing values and opinions within and across different mapper subgroups and can be exacerbated by negative mapper behaviors. The boundaries of these subgroups, while implicit, are often defined by gender, mappers’ geographic location, level of expertise, and mappers’ professional affiliation. Based on these results, we discuss design options for OSM’s existing public communication channels that often become foci of mapper conflict management.","PeriodicalId":314098,"journal":{"name":"Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130906363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Seo-Yeon Kim, Donghoon Shin, Jeongyeon Kim, S. Kwon, Juho Kim
Online videos are a promising medium for older adults to learn. Yet, few studies have investigated what, how, and why they learn through online videos. In this study, we investigated older adults’ motivation, watching patterns, and difficulties in using online videos for learning by (1) running interviews with 13 older adults and (2) analyzing large-scale video event logs (N=41.8M) from a Korean Massive Online Open Course (MOOC) platform. Our results show that older adults (1) are motivated to learn practical topics, leading to less consumption of STEM domains than non-older adults, (2) watch videos with less interaction and watch a larger portion of a single video compared to non-older adults, and (3) face various difficulties (e.g., inconvenience arisen due to their unfamiliarity with technologies) that limit their learning through online videos. Based on the findings, we propose design guidelines for online videos and platforms targeted to support older adults’ learning.
{"title":"How Older Adults Use Online Videos for Learning","authors":"Seo-Yeon Kim, Donghoon Shin, Jeongyeon Kim, S. Kwon, Juho Kim","doi":"10.1145/3544548.3580671","DOIUrl":"https://doi.org/10.1145/3544548.3580671","url":null,"abstract":"Online videos are a promising medium for older adults to learn. Yet, few studies have investigated what, how, and why they learn through online videos. In this study, we investigated older adults’ motivation, watching patterns, and difficulties in using online videos for learning by (1) running interviews with 13 older adults and (2) analyzing large-scale video event logs (N=41.8M) from a Korean Massive Online Open Course (MOOC) platform. Our results show that older adults (1) are motivated to learn practical topics, leading to less consumption of STEM domains than non-older adults, (2) watch videos with less interaction and watch a larger portion of a single video compared to non-older adults, and (3) face various difficulties (e.g., inconvenience arisen due to their unfamiliarity with technologies) that limit their learning through online videos. Based on the findings, we propose design guidelines for online videos and platforms targeted to support older adults’ learning.","PeriodicalId":314098,"journal":{"name":"Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133430116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Error rates (ERs) in target-pointing tasks are typically modelled in two steps: predicting the click-point variability (σ) based on target sizes and then computing the probability that a click falls outside a target. This is an indirect approach if the researcher’s purpose is to achieve the accurate prediction of ERs because the model coefficients are optimized to predict σ accurately in the first step. We compared the prediction accuracies of this method with a more direct technique in which the coefficients used for σ are determined in such a way as to optimize the closeness between observed and predicted ERs. Our re-analysis of eight datasets from mouse- and touch-based pointing studies showed that the latter approach consistently outperforms the conventional one if the starting values for the parameter search are appropriate (which can be achieved by hyperparameter optimization), thus enabling the interface configuration on the basis of accurately predicted ERs.
{"title":"Tuning Endpoint-variability Parameters by Observed Error Rates to Obtain Better Prediction Accuracy of Pointing Misses","authors":"Shota Yamanaka, Hiroki Usuba","doi":"10.1145/3544548.3580746","DOIUrl":"https://doi.org/10.1145/3544548.3580746","url":null,"abstract":"Error rates (ERs) in target-pointing tasks are typically modelled in two steps: predicting the click-point variability (σ) based on target sizes and then computing the probability that a click falls outside a target. This is an indirect approach if the researcher’s purpose is to achieve the accurate prediction of ERs because the model coefficients are optimized to predict σ accurately in the first step. We compared the prediction accuracies of this method with a more direct technique in which the coefficients used for σ are determined in such a way as to optimize the closeness between observed and predicted ERs. Our re-analysis of eight datasets from mouse- and touch-based pointing studies showed that the latter approach consistently outperforms the conventional one if the starting values for the parameter search are appropriate (which can be achieved by hyperparameter optimization), thus enabling the interface configuration on the basis of accurately predicted ERs.","PeriodicalId":314098,"journal":{"name":"Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131935014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Simret Araya Gebreegziabher, Zheng Zhang, Xiaohang Tang, Yihao Meng, Elena L. Glassman, Toby Jia-Jun Li
Over the years, the task of AI-assisted data annotation has seen remarkable advancements. However, a specific type of annotation task, the qualitative coding performed during thematic analysis, has characteristics that make effective human-AI collaboration difficult. Informed by a formative study, we designed PaTAT, a new AI-enabled tool that uses an interactive program synthesis approach to learn flexible and expressive patterns over user-annotated codes in real-time as users annotate data. To accommodate the ambiguous, uncertain, and iterative nature of thematic analysis, the use of user-interpretable patterns allows users to understand and validate what the system has learned, make direct fixes, and easily revise, split, or merge previously annotated codes. This new approach also helps human users to learn data characteristics and form new theories in addition to facilitating the “learning” of the AI model. PaTAT’s usefulness and effectiveness were evaluated in a lab user study.
{"title":"PaTAT: Human-AI Collaborative Qualitative Coding with Explainable Interactive Rule Synthesis","authors":"Simret Araya Gebreegziabher, Zheng Zhang, Xiaohang Tang, Yihao Meng, Elena L. Glassman, Toby Jia-Jun Li","doi":"10.1145/3544548.3581352","DOIUrl":"https://doi.org/10.1145/3544548.3581352","url":null,"abstract":"Over the years, the task of AI-assisted data annotation has seen remarkable advancements. However, a specific type of annotation task, the qualitative coding performed during thematic analysis, has characteristics that make effective human-AI collaboration difficult. Informed by a formative study, we designed PaTAT, a new AI-enabled tool that uses an interactive program synthesis approach to learn flexible and expressive patterns over user-annotated codes in real-time as users annotate data. To accommodate the ambiguous, uncertain, and iterative nature of thematic analysis, the use of user-interpretable patterns allows users to understand and validate what the system has learned, make direct fixes, and easily revise, split, or merge previously annotated codes. This new approach also helps human users to learn data characteristics and form new theories in addition to facilitating the “learning” of the AI model. PaTAT’s usefulness and effectiveness were evaluated in a lab user study.","PeriodicalId":314098,"journal":{"name":"Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133134413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Farnaz Jahanbakhsh, Yannis Katsis, Dakuo Wang, Lucian Popa, Michael J. Muller
This work aims to explore how human assessments and AI predictions can be combined to identify misinformation on social media. To do so, we design a personalized AI which iteratively takes as training data a single user’s assessment of content and predicts how the same user would assess other content. We conduct a user study in which participants interact with a personalized AI that learns their assessments of a feed of tweets, shows its predictions of whether a user would find other tweets (in)accurate, and evolves according to the user feedback. We study how users perceive such an AI, and whether the AI predictions influence users’ judgment. We find that this influence does exist and it grows larger over time, but it is reduced when users provide reasoning for their assessment. We draw from our empirical observations to identify design implications and directions for future work.
{"title":"Exploring the Use of Personalized AI for Identifying Misinformation on Social Media","authors":"Farnaz Jahanbakhsh, Yannis Katsis, Dakuo Wang, Lucian Popa, Michael J. Muller","doi":"10.1145/3544548.3581219","DOIUrl":"https://doi.org/10.1145/3544548.3581219","url":null,"abstract":"This work aims to explore how human assessments and AI predictions can be combined to identify misinformation on social media. To do so, we design a personalized AI which iteratively takes as training data a single user’s assessment of content and predicts how the same user would assess other content. We conduct a user study in which participants interact with a personalized AI that learns their assessments of a feed of tweets, shows its predictions of whether a user would find other tweets (in)accurate, and evolves according to the user feedback. We study how users perceive such an AI, and whether the AI predictions influence users’ judgment. We find that this influence does exist and it grows larger over time, but it is reduced when users provide reasoning for their assessment. We draw from our empirical observations to identify design implications and directions for future work.","PeriodicalId":314098,"journal":{"name":"Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134634858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Patient-generated data from commercially available self-tracking devices has the potential to enhance support for people transitioning from hospitalization to self-care. However, studies have revealed significant barriers to the routine use of such data in clinical settings. This paper explores the use of patient-generated data in the context of cardiac rehabilitation. We describe a two-stage investigation: (1) a co-design study with clinicians to design a data system that combines objective and subjective patient data; and (2) an 18-week field-study where this system was deployed as part of a hospital-based rehabilitation program. Our findings suggest the system is feasible, supported clinicians’ workflow, and helped patients to bridge the gap between supervised and self-managed care. Subjective data contextualized objective data and a structured approach data collection helped generate actionable information. The paper also provides insight on patients' attitudes towards peer data sharing and demonstrates the importance of timing when introducing self-tracking technology.
{"title":"Using Patient-Generated Data to Support Cardiac Rehabilitation and the Transition to Self-Care","authors":"Shreya Tadas, Jane Dickson, D. Coyle","doi":"10.1145/3544548.3580822","DOIUrl":"https://doi.org/10.1145/3544548.3580822","url":null,"abstract":"Patient-generated data from commercially available self-tracking devices has the potential to enhance support for people transitioning from hospitalization to self-care. However, studies have revealed significant barriers to the routine use of such data in clinical settings. This paper explores the use of patient-generated data in the context of cardiac rehabilitation. We describe a two-stage investigation: (1) a co-design study with clinicians to design a data system that combines objective and subjective patient data; and (2) an 18-week field-study where this system was deployed as part of a hospital-based rehabilitation program. Our findings suggest the system is feasible, supported clinicians’ workflow, and helped patients to bridge the gap between supervised and self-managed care. Subjective data contextualized objective data and a structured approach data collection helped generate actionable information. The paper also provides insight on patients' attitudes towards peer data sharing and demonstrates the importance of timing when introducing self-tracking technology.","PeriodicalId":314098,"journal":{"name":"Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115464724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The concept of phubbing (generally defined as a practice of ignoring co-present others by focusing on one's mobile device) is now widely used in studies aiming to understand the effects of smartphone use on co-present interactions. However, most of these studies are quantitative in nature and fail to grasp the interactional context of smartphone use. Drawing on video recordings and utilizing multimodal interaction analysis, the present study examines phubbing in naturally occurring interactions among young adults. Contrary to most previous research, the analysis reveals that disengagement often precedes self-initiated smartphone use rather than follows it. The study identifies factors that affect whether phubbing is reciprocated and whether it is oriented to as problematic. As a result of the analysis, an alternative conceptualization of phubbing is offered. By reflecting on participants’ ways of managing phubbing and its consequences, we discuss design solutions for supporting them in this task.
{"title":"Respecifying Phubbing: Video-Based Analysis of Smartphone Use in Co-Present Interactions","authors":"Iuliia Avgustis","doi":"10.1145/3544548.3581052","DOIUrl":"https://doi.org/10.1145/3544548.3581052","url":null,"abstract":"The concept of phubbing (generally defined as a practice of ignoring co-present others by focusing on one's mobile device) is now widely used in studies aiming to understand the effects of smartphone use on co-present interactions. However, most of these studies are quantitative in nature and fail to grasp the interactional context of smartphone use. Drawing on video recordings and utilizing multimodal interaction analysis, the present study examines phubbing in naturally occurring interactions among young adults. Contrary to most previous research, the analysis reveals that disengagement often precedes self-initiated smartphone use rather than follows it. The study identifies factors that affect whether phubbing is reciprocated and whether it is oriented to as problematic. As a result of the analysis, an alternative conceptualization of phubbing is offered. By reflecting on participants’ ways of managing phubbing and its consequences, we discuss design solutions for supporting them in this task.","PeriodicalId":314098,"journal":{"name":"Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115543563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wei Zhao, Ryan M. Kelly, Melissa J. Rogerson, Jenny Waycott
Restrictions during the COVID-19 pandemic significantly affected people's opportunities to engage in activities that are meaningful to their lives. In response to these constraints, many people, including older adults, turned to digital technologies as alternative ways to pursue meaningful activities. These technology-mediated activities, however, presented new challenges for older adults’ everyday use of technology. In this paper, we investigate how older adults used digital technologies for meaningful activities during COVID-19 restrictions. We conducted in-depth interviews with 40 older adults and analyzed the interview data through the lens of self-determination theory (SDT). Our analysis shows that using digital technologies for meaningful activities can both support and undermine older people's three basic psychological needs for autonomy, competence, and relatedness. We argue that future technologies should be designed to empower older adults’ content creation, engagement in personal interests, exploration of technology, effortful communication, and participation in beneficent activities.
{"title":"Older Adults Using Technology for Meaningful Activities During COVID-19: An Analysis Through the Lens of Self-Determination Theory","authors":"Wei Zhao, Ryan M. Kelly, Melissa J. Rogerson, Jenny Waycott","doi":"10.1145/3544548.3580839","DOIUrl":"https://doi.org/10.1145/3544548.3580839","url":null,"abstract":"Restrictions during the COVID-19 pandemic significantly affected people's opportunities to engage in activities that are meaningful to their lives. In response to these constraints, many people, including older adults, turned to digital technologies as alternative ways to pursue meaningful activities. These technology-mediated activities, however, presented new challenges for older adults’ everyday use of technology. In this paper, we investigate how older adults used digital technologies for meaningful activities during COVID-19 restrictions. We conducted in-depth interviews with 40 older adults and analyzed the interview data through the lens of self-determination theory (SDT). Our analysis shows that using digital technologies for meaningful activities can both support and undermine older people's three basic psychological needs for autonomy, competence, and relatedness. We argue that future technologies should be designed to empower older adults’ content creation, engagement in personal interests, exploration of technology, effortful communication, and participation in beneficent activities.","PeriodicalId":314098,"journal":{"name":"Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems","volume":"272 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115902611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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