Reflecting on Online Content

会議の名前
CHI 2024
Help Me Reflect: Leveraging Self-Reflection Interface Nudges to Enhance Deliberativeness on Online Deliberation Platforms
要旨

The deliberative potential of online platforms has been widely examined. However, little is known about how various interface-based reflection nudges impact the quality of deliberation. This paper presents two user studies with 12 and 120 participants, respectively, to investigate the impacts of different reflective nudges on the quality of deliberation. In the first study, we examined five distinct reflective nudges: persona, temporal prompts, analogies and metaphors, cultural prompts and storytelling. Persona, temporal prompts, and storytelling emerged as the preferred nudges for implementation on online deliberation platforms. In the second study, we assess the impacts of these preferred reflectors more thoroughly. Results revealed a significant positive impact of these reflectors on deliberative quality. Specifically, persona promotes a deliberative environment for balanced and opinionated viewpoints while temporal prompts promote more individualised viewpoints. Our findings suggest that the choice of reflectors can significantly influence the dynamics and shape the nature of online discussions.

著者
ShunYi Yeo
Singapore University of Technology and Design, Singapore, Singapore
Gionnieve Lim
Singapore University of Technology and Design, Singapore, Singapore
Jie Gao
Singapore University of Technology and Design, Singapore, Singapore
Weiyu Zhang
National University of Singapore, Singapore, Singapore
Simon Tangi. Perrault
Singapore University of Technology and Design, Singapore, Singapore
論文URL

https://doi.org/10.1145/3613904.3642530

動画
Capra: Making Use of Multiple Perspectives for Capturing, Noticing and Revisiting Hiking Experiences Over Time
要旨

As the practice of hiking becomes increasingly captured through personal data, it is timely to consider what kinds of alternative data encounters might support forms of noticing and connecting to nature as well as one’s self and life history over time. To investigate this emerging design space, we designed Capra — a system that brings together the capture, storage, and exploration of personal hiking data with an emphasis on longer-term, occasional yet indefinite use. Over four years, our team adopted a designer-researcher approach where we progressively designed, built, refined, and tested Capra. This process produced frictions in terms of balancing unobtrusiveness, transforming hiking data into evolving interconnected elements in the archive, and managing the sheer quantity and diversity of information with our goal of supporting open-ended and ongoing engagements. It is these insights that emerged through the practice-based design research approach involved in creating Capra that we reflect on in this paper.

著者
William Odom
Simon Fraser University, Surrey, British Columbia, Canada
Jordan White
Simon Fraser University, Surrey, British Columbia, Canada
Samuel Barnett
Simon Fraser University, Surrey, British Columbia, Canada
Nico Brand
Simon Fraser University, Surrey, British Columbia, Canada
Henry Lin
SFU, Vancouver, British Columbia, Canada
MinYoung Yoo
Simon Fraser University, Surrey, British Columbia, Canada
Tal Amram
Simon Fraser University, Surrey, British Columbia, Canada
論文URL

https://doi.org/10.1145/3613904.3642284

動画
AI-Driven Mediation Strategies for Audience Depolarisation in Online Debates
要旨

Online polarisation can tear the fabric of civility through reinforcing social media's perceptions of division and discord. Social media platforms often rely on content-moderation to combat polarisation, contingent on the reactive removal or flagging of content. However, this approach often remains agnostic of the underlying debate's ideas and stifles open discourse. In this study, we use prompt-tuned language models to mediate social media debates, applying the strategies of the Thomas-Kilmann Conflict Mode Instrument (TKI). We evaluate multiple mediation strategies in providing targeted responses to the debates, as shown to a debate audience. Our findings show that high-cooperativeness TKI strategies offered more persuasive arguments, while an accommodating argument strategy was the most successful at depolarising the audience's opinion. Furthermore, high-cooperativeness strategies also increased the perception that the debaters will reach a consensus. Our work paves the way for scalable and personalised tools that mediate social media debates to encourage depolarisation.

著者
Jarod Govers
University of Melbourne, Melbourne, Victoria, Australia
Eduardo Velloso
University of Melbourne, Melbourne, Victoria, Australia
Vassilis Kostakos
University of Melbourne, Melbourne, Victoria, Australia
Jorge Goncalves
University of Melbourne, Melbourne, Australia
論文URL

https://doi.org/10.1145/3613904.3642322

動画
Debate Chatbots to Facilitate Critical Thinking on YouTube: Social Identity and Conversational Style Make A Difference
要旨

Exposure to diverse perspectives is helpful for bursting the filter bubble in online public video platforms. The recent advancement of Large Language Models (LLMs) illuminates the potential of creating a debate chatbot that prompts users to critically examine their stances on a topic formed by watching videos. However, whether the viewer is influenced by the chatbot may depend on its persona. In this paper, we investigated the effect of two relevant persona attributes - social identity and rhetorical styles - on critical thinking. In a mixed-methods study (n=36), we found that chatbots with outgroup (vs. ingroup) identity (t(33)=-2.33, p=0.03) and persuasive (vs. eristic) rhetoric (t(44)=1.98, p=0.05) induced critical thinking most effectively, making participants re-examine their arguments. However, participants' stances remain largely unaffected, likely due to the chatbot's lack of contextual knowledge and human touch. Our paper provides empirical groundwork for designing chatbot persona for remedying filter bubbles in online communities.

受賞
Best Paper
著者
Thitaree Tanprasert
University of British Columbia, Vancouver, British Columbia, Canada
Sidney S. Fels
University of British Columbia, Vancouver, British Columbia, Canada
Luanne Sinnamon
University of British Columbia, Vancouver, British Columbia, Canada
Dongwook Yoon
University of British Columbia, Vancouver, British Columbia, Canada
論文URL

https://doi.org/10.1145/3613904.3642513

動画
Viblio: Introducing Credibility Signals and Citations to Video-Sharing Platforms
要旨

As more users turn to video-sharing platforms like YouTube as an information source, they may consume misinformation despite their best efforts. In this work, we investigate ways that users can better assess the credibility of videos by first exploring how users currently determine credibility using existing signals on platforms and then by introducing and evaluating new credibility-based signals. We conducted 12 contextual inquiry interviews with YouTube users, determining that participants used a combination of existing signals, such as the channel name, the production quality, and prior knowledge, to evaluate credibility, yet sometimes stumbled in their efforts to do so. We then developed Viblio, a prototype system that enables YouTube users to view and add citations and related information while watching a video based on our participants' needs. From an evaluation with 12 people, all participants found Viblio to be intuitive and useful in the process of evaluating a video’s credibility and could see themselves using Viblio in the future.

著者
Emelia May. Hughes
University of Notre Dame, South Bend, Indiana, United States
Renee Wang
University of Washington, Seattle, Washington, United States
Prerna Juneja
Seattle University, Seattle, Washington, United States
Tony W. Li
University of California, San Diego, La Jolla, California, United States
Tanushree Mitra
University of Washington, Seattle, Washington, United States
Amy X.. Zhang
University of Washington, Seattle, Washington, United States
論文URL

https://doi.org/10.1145/3613904.3642490

動画