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  • 1
    Online Resource
    Online Resource
    Crebot: Exploring Interactive Question Prompts for Critical Paper Reading
    Elsevier BV ; 2022
    In:  SSRN Electronic Journal
    Details
    In: SSRN Electronic Journal, Elsevier BV
    Type of Medium: Online Resource
    ISSN: 1556-5068
    URL: Article
    DOI: 10.2139/ssrn.4001460
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2022
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  • 2
    Online Resource
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    supp1-3209440.mp4
    Institute of Electrical and Electronics Engineers (IEEE) ; 2022
    In:  IEEE Transactions on Visualization and Computer Graphics
    Details
    In: IEEE Transactions on Visualization and Computer Graphics, Institute of Electrical and Electronics Engineers (IEEE)
    Type of Medium: Online Resource
    ISSN: 1077-2626 , 1941-0506 , 2160-9306
    URL: Article
    URL: Article
    DOI: 10.1109/TVCG.2022.3209440
    DOI: 10.1109/TVCG.2022.3209440/mm1
    RVK:
    SQ 1100
    Language: Unknown
    Publisher: Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2022
    detail.hit.zdb_id: 2027333-2
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  • 3
    Online Resource
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    Love in Lyrics : An Exploration of Supporting Textual Manifestation of Affection in Social Messaging
    Association for Computing Machinery (ACM) ; 2019
    In:  Proceedings of the ACM on Human-Computer Interaction Vol. 3, No. CSCW ( 2019-11-07), p. 1-27
    Details
    In: Proceedings of the ACM on Human-Computer Interaction, Association for Computing Machinery (ACM), Vol. 3, No. CSCW ( 2019-11-07), p. 1-27
    Abstract: Affectionate communication, the conveyance of closeness, care, and fondness for another, plays a key role in romantic relationships. While the pervasive use of digital technology for communication limits affectionate interaction through nonverbal cues -- a major channel of expression in face-to-face settings, there have been few approaches which scaffold couples' romantic text conversations. To bridge this gap, we propose a novel interactive system Lily which gives users inspirations to enrich their romantic expressions in text messaging. It first listens to users' original input and then recommends romantic lyrics holding the closest meaning in real-time during chats with partners. After a three-day empirical study, participants who are real-life couples reported that they not only received useful cues from Lily in terms of how to polish their affectionate expressions, but also learnt to enrich the conversation with topics enlightened by its recommendations. Based on our findings, we finally provide several design considerations for actual deployment of such an application.
    Type of Medium: Online Resource
    ISSN: 2573-0142
    URL: Article
    DOI: 10.1145/3359181
    Language: English
    Publisher: Association for Computing Machinery (ACM)
    Publication Date: 2019
    detail.hit.zdb_id: 2930194-4
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  • 4
    Online Resource
    Online Resource
    CASS : Towards Building a Social-Support Chatbot for Online Health Community
    Association for Computing Machinery (ACM) ; 2021
    In:  Proceedings of the ACM on Human-Computer Interaction Vol. 5, No. CSCW1 ( 2021-04-13), p. 1-31
    Details
    In: Proceedings of the ACM on Human-Computer Interaction, Association for Computing Machinery (ACM), Vol. 5, No. CSCW1 ( 2021-04-13), p. 1-31
    Abstract: Chatbots systems, despite their popularity in today's HCI and CSCW research, fall short for one of the two reasons: 1) many of the systems use a rule-based dialog flow, thus they can only respond to a limited number of pre-defined inputs with pre-scripted responses; or 2) they are designed with a focus on single-user scenarios, thus it is unclear how these systems may affect other users or the community. In this paper, we develop a generalizable chatbot architecture (CASS) to provide social support for community members in an online health community. The CASS architecture is based on advanced neural network algorithms, thus it can handle new inputs from users and generate a variety of responses to them. CASS is also generalizable as it can be easily migrate to other online communities. With a follow-up field experiment, CASS is proven useful in supporting individual members who seek emotional support. Our work also contributes to fill the research gap on how a chatbot may influence the whole community's engagement.
    Type of Medium: Online Resource
    ISSN: 2573-0142
    URL: Article
    DOI: 10.1145/3449083
    Language: English
    Publisher: Association for Computing Machinery (ACM)
    Publication Date: 2021
    detail.hit.zdb_id: 2930194-4
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  • 5
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    DesignQuizzer: A Community-Powered Conversational Agent for Learning Visual Design
    Association for Computing Machinery (ACM) ; 2024
    In:  Proceedings of the ACM on Human-Computer Interaction Vol. 8, No. CSCW1 ( 2024-04-17), p. 1-40
    Details
    In: Proceedings of the ACM on Human-Computer Interaction, Association for Computing Machinery (ACM), Vol. 8, No. CSCW1 ( 2024-04-17), p. 1-40
    Abstract: Online design communities, where members exchange free-form views on others' designs, offer a space for beginners to learn visual design. However, the content of these communities is often unorganized for learners, containing many redundancies and irrelevant comments. In this paper, we propose a computational approach for leveraging online design communities to run a conversational agent that assists informal learning of visual elements (e.g., color and space). Our method extracts critiques, suggestions, and rationales on visual elements from comments. We present DesignQuizzer, which asks questions about visual design in UI examples and provides structured comment summaries. Two user studies demonstrate the engagement and usefulness of DesignQuizzer compared with the baseline (reading reddit.com/r/UI_design). We also showcase how effectively novices can apply what they learn with DesignQuizzer in a design critique task and a visual design task. We discuss how to use our approach with other communities and offer design considerations for community-powered learning support tools.
    Type of Medium: Online Resource
    ISSN: 2573-0142
    URL: Article
    DOI: 10.1145/3637321
    Language: English
    Publisher: Association for Computing Machinery (ACM)
    Publication Date: 2024
    detail.hit.zdb_id: 2930194-4
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  • 6
    Online Resource
    Online Resource
    Amplifying the music listening experience through song comments on music streaming platforms
    Springer Science and Business Media LLC ; 2024
    In:  Journal of Visualization Vol. 27, No. 3 ( 2024-06), p. 401-419
    Details
    In: Journal of Visualization, Springer Science and Business Media LLC, Vol. 27, No. 3 ( 2024-06), p. 401-419
    Type of Medium: Online Resource
    ISSN: 1343-8875 , 1875-8975
    URL: Article
    DOI: 10.1007/s12650-024-00966-2
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2024
    detail.hit.zdb_id: 2094841-4
    SSG: 11
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  • 7
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    Online Resource
    Know It to Defeat It: Exploring Health Rumor Characteristics and Debunking Efforts on Chinese Social Media during COVID-19 Crisis
    Association for the Advancement of Artificial Intelligence (AAAI) ; 2022
    In:  Proceedings of the International AAAI Conference on Web and Social Media Vol. 16 ( 2022-05-31), p. 1157-1168
    Details
    In: Proceedings of the International AAAI Conference on Web and Social Media, Association for the Advancement of Artificial Intelligence (AAAI), Vol. 16 ( 2022-05-31), p. 1157-1168
    Abstract: Health-related rumors being spread online during a public crisis may pose a serious threat to people's well-being. Existing crisis informatics research lacks in-depth insights into the characteristics of health rumors and the efforts to debunk them on social media in a pandemic. To fill this gap, we conduct a comprehensive analysis of four months of rumor-related online discussion during COVID-19 on Weibo, a Chinese microblogging site. Results suggest that the dread (cause fear) type of health rumors provoked significantly more discussions and lasted longer than the wish (raise hope) type. We further explore how four kinds of social media users (i.e., government, media, organization, and individual) combat health rumors, and identify their preferred way of sharing the debunking information and the key rhetoric strategies used in the process. We examine the relationship between debunking and rumor discussions using a Granger causality approach, and show the efficacy of debunking in suppressing rumor discussions, which is time-sensitive and varies according to rumor type and debunker. Our results can provide insights into crisis informatics and risk management on social media in pandemic settings.
    Type of Medium: Online Resource
    ISSN: 2334-0770 , 2162-3449
    URL: Article
    DOI: 10.1609/icwsm.v16i1.19366
    Language: Unknown
    Publisher: Association for the Advancement of Artificial Intelligence (AAAI)
    Publication Date: 2022
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  • 8
    Online Resource
    Online Resource
    PlanHelper : Supporting Activity Plan Construction with Answer Posts in Community-based QA Platforms
    Association for Computing Machinery (ACM) ; 2022
    In:  Proceedings of the ACM on Human-Computer Interaction Vol. 6, No. CSCW2 ( 2022-11-07), p. 1-26
    Details
    In: Proceedings of the ACM on Human-Computer Interaction, Association for Computing Machinery (ACM), Vol. 6, No. CSCW2 ( 2022-11-07), p. 1-26
    Abstract: Community-based Question Answering (CQA) platforms can provide rich experience and suggestions for people who seek to construct Activity Plans (AP), such as bodybuilding or sightseeing. However, answer posts in CQA platforms could be too unstructured and overwhelming to be easily applied to AP construction, as validated by our formative study for understanding relevant user challenges. We therefore proposed an answer-post processing pipeline, based on which we built PlanHelper, a tool assisting users in processing the CQA information and constructing AP interactively. We conducted a within-subject study (N=24) with a Quora-like interface as the baseline. Results suggested that when creating AP with PlanHelper, users were significantly more satisfied with the informational support and more engaged during the interaction. Moreover, we performed an in-depth analysis on the user behaviors with PlanHelper and summarized the design considerations for such supporting tools.
    Type of Medium: Online Resource
    ISSN: 2573-0142
    URL: Article
    DOI: 10.1145/3555555
    Language: English
    Publisher: Association for Computing Machinery (ACM)
    Publication Date: 2022
    detail.hit.zdb_id: 2930194-4
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  • 9
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    CReBot: Exploring interactive question prompts for critical paper reading
    Elsevier BV ; 2022
    In:  International Journal of Human-Computer Studies Vol. 167 ( 2022-11), p. 102898-
    Details
    In: International Journal of Human-Computer Studies, Elsevier BV, Vol. 167 ( 2022-11), p. 102898-
    Type of Medium: Online Resource
    ISSN: 1071-5819
    URL: Article
    DOI: 10.1016/j.ijhcs.2022.102898
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2022
    detail.hit.zdb_id: 1183233-2
    detail.hit.zdb_id: 1468030-0
    SSG: 12
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  • 10
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    Investigating the Effects of Robot Engagement Communication on Learning from Demonstration
    Springer Science and Business Media LLC ; 2022
    In:  International Journal of Social Robotics Vol. 14, No. 3 ( 2022-04), p. 789-806
    Details
    In: International Journal of Social Robotics, Springer Science and Business Media LLC, Vol. 14, No. 3 ( 2022-04), p. 789-806
    Abstract: Robot learning from demonstration (RLfD) is a technique for robots to derive policies from instructors’ examples. Although the reciprocal effects of student engagement on teacher behavior are widely recognized in the educational community, it is unclear whether the same phenomenon holds for RLfD. To fill this gap, we first design three types of robot engagement behavior (gaze, imitation, and a hybrid of the two) based on the learning literature. We then conduct, in a simulation environment, a within-subject user study to investigate the impact of different robot engagement cues on humans compared to a “without-engagement” condition. Results suggest that engagement communication has significantly negative influences on the human’s estimation of the simulated robots’ capability and significantly raises their expectation towards the learning outcomes, even though we do not run actual imitation learning algorithms in the experiments. Moreover, imitation behavior affects humans more than gaze does in all metrics, while their combination has the most profound influences on humans. We also find that communicating engagement via imitation or the combined behavior significantly improves humans’ perception towards the quality of simulated demonstrations, even if all demonstrations are of the same quality.
    Type of Medium: Online Resource
    ISSN: 1875-4791 , 1875-4805
    URL: Article
    DOI: 10.1007/s12369-021-00825-2
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 2486751-2
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