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In today’s digital age, characterized by rapid news consumption and increasing vulnerability to propaganda, fostering citizens' critical thinking is crucial for stable democracies. This paper introduces the design of ClarifAI, a novel automated propaganda detection tool designed to nudge readers towards more critical news consumption by activating the analytical mode of thinking, following Kahneman's dual-system theory of cognition. Using Large Language Models, ClarifAI detects propaganda in news articles and provides context-rich explanations, enhancing users' understanding and critical thinking. Our contribution is threefold: first, we propose the design of ClarifAI; second, in an online experiment, we demonstrate that this design effectively encourages news readers to engage in more critical reading; and third, we emphasize the value of explanations for fostering critical thinking. The study thus offers both a practical tool and useful design knowledge for mitigating propaganda in digital news.
Energy communities are a key focus for governments around the world in support of more sustainable energy practices. However, interactive systems for supporting energy communities to coordinate around renewable energy resources are still lacking. We present SolarClub, a demand-shifting visualization system that supported households in coordinating their energy usage by booking energy-hungry activities when solar energy was available. We deployed SolarClub with four groups of neighbors (N=15) for a month. SolarClub successfully enabled neighbors to coordinate, even when some of those participating households were less flexible. While participants reported that SolarClub did not foster a feeling of community, it helped them empathize with their neighbors. Our findings demonstrate the potential of sensor- and visualization-based technology to help understand the relation between everyday practices and resources consumption, beyond individual eco-feedback. This work thus contributes to the development of a next generation of practices and technologies that support collective action for environmental sustainability.
This study explores the impact of peer acknowledgement on learner engagement and implicit psychological attributes in written annotations on an online social reading platform. Participants included 91 undergraduates from a large North American University. Using log file data, we analyzed the relationship between learners’ received peer acknowledgement and their subsequent annotation behaviours using cross-lag regression. Higher peer acknowledgements correlate with increased initiation of annotations and responses to peer annotations. By applying text mining techniques and calculating Shapley values to analyze 1,969 social annotation entries, we identified prominent psychological themes within three dimensions (i.e., affect, cognition, and motivation) that foster peer acknowledgment in digital social annotation. These themes include positive affect, openness to learning and discussion, and expression of motivation. The findings assist educators in improving online learning communities and provide guidance to technology developers in designing effective prompts, drawing from both implicit psychological cues and explicit learning behaviours.
Moderating user-generated content on online platforms is crucial for balancing user safety and freedom of speech. Particularly in the United States, platforms are not subject to legal constraints prescribing permissible content. Each platform has thus developed bespoke content moderation policies, but there is little work towards a comparative understanding of these policies across platforms and topics. This paper presents the first systematic study of these policies from the 43 largest online platforms hosting user-generated content, focusing on policies around copyright infringement, harmful speech, and misleading content. We build a custom web-scraper to obtain policy text and develop a unified annotation scheme to analyze the text for the presence of critical components. We find significant structural and compositional variation in policies across topics and platforms, with some variation attributable to disparate legal groundings. We lay the groundwork for future studies of ever-evolving content moderation policies and their impact on users.
The objective of this study was to investigate and classify the roles, or distinct contribution styles, adopted by participants within the OpenStreetMap (OSM) community. Using a quantitative analysis of mapping behaviors, we devised a methodology to identify distinct features associated with specific roles. We used an unsupervised clustering approach and unveiled eight discernible roles, or types of mapper in OSM. Each role displays specific patterns of mapping behaviors related to their habits and preferences for adding or editing map objects over time. We validated our roles, in part, using known affiliations with humanitarian and corporate organizations. Using these roles, we examine community composition and contributor retention over time. Our contributions include applying existing methods on the analysis of contributor behavior in online platforms to OSM, the identification of eight roles that can guide future research and design within OSM, and further understanding into the overall trajectory of the world's largest geospatial peer production community.
We report on a six-year collaboration with a small community organisation to develop and deploy a permanent physical / digital locative media experience as part on an ongoing community regeneration project. We describe how this unfolded over four phases: approach and pilot; public deployment; supporting subsequent community-led spin-off experiences; and planning legacy and technology handovers. The project was distinctive for being a Knowledge Exchange project in which we were approached and formally contracted by the community to deliver the digital technology, rather than instigating and leading a research project. We identify seven considerations for handing over technologies that combine both digital and physical elements to communities of stakeholders that encompass businesses, councils, and volunteers, and how this illuminates the unique strengths and weaknesses of Knowledge Exchange projects within the wider design research landscape.
Driven by pragmatic, cost-related, and environmental factors, voice-based remote community engagement tools (such as Interactive Voice Response) are emerging as a key modality for engaging marginalized communities. These voice-based digital solutions offer new opportunities for distributed community engagement and empowerment, and the ability to capture, store, and access a wide range of different records (i.e., recordings, interactions and contextual metadata) associated with community engagements. This potential for large scale, distributed community record collection necessitates an understanding of inclusive and effective recordkeeping approaches for appraisal, documentation, preservation, and accessibility of different types of records (such as audio recordings, transcripts, reports, and observatory notes) related to voice-based community engagements. Through qualitative analysis of stakeholder focus group discussions with domestic workers (as marginalized community members) and NGOs working in the sector, we present valuable insights and recommendations for the development of recordkeeping approaches tailored to voice-based remote community engagement records.