About

Tawfiq Ammari is a mixed-methods researcher who connects critical approaches from science, technology, and society studies with computational social science techniques to advocate for equity and progressive social change in online contexts. His research sits at the intersection of social computing and data science and focuses on the interplay between technological and social role change, especially in families and other intimate social worlds. Ammari studies how large societal shifts, such as changing norms around masculinity and parenting, are associated with online interactions and social movements. He also examines how the mass adoption of technologies such as social media and voice assistants reshapes everyday life in the domestic sphere and how networked technologies can support people navigating stigma, caregiving, and other forms of vulnerability. His work has been published in venues such as the ACM CHI Conference on Human Factors in Computing Systems, the ACM Conference on Computer-Supported Cooperative Work and Social Computing, ACM Transactions on Computer-Human Interaction, and Child Abuse & Neglect. In 2022, Ammari received the “AI 2000 Most Influential Scholar Honorable Mention in Human-Computer Interaction” award from AMiner Scholar for his contributions to human–computer interaction research between 2012 and 2021.

Research topics

• Computer Science
• Sociology
• Political Science
• Psychology
• Social psychology
• Medical emergency
• Medicine
• Cognitive psychology
• World Wide Web
• Internet privacy
• Knowledge management
• Developmental psychology
• Media studies
• Business
• Virology

Selected publications

• Learning to Live with AI: How Students Develop AI Literacy Through Naturalistic ChatGPT Interaction

  ArXiv.org · 2026-01-28

  articleOpen access1st authorCorresponding

  How do students develop AI literacy through everyday practice rather than formal instruction? While normative AI literacy frameworks proliferate, empirical understanding of how students actually learn to work with generative AI remains limited. This study analyzes 10,536 ChatGPT messages from 36 undergraduates over one academic year, revealing five use genres -- academic workhorse, emotional companion, metacognitive partner, repair and negotiation, and trust calibration -- that constitute distinct configurations of student-AI learning. Drawing on domestication theory and emerging frameworks for AI literacy, we demonstrate that functional AI competence emerges through ongoing relational negotiation rather than one-time adoption. Students develop sophisticated genre portfolios, strategically matching interaction patterns to learning needs while exercising critical judgment about AI limitations. Notably, repair work during AI breakdowns produces substantial learning about AI capabilities, developing what we term "repair literacy" -- a crucial but underexplored dimension of AI competence. Our findings offer educators empirically grounded insights into how students actually learn to work with generative AI, with implications for AI literacy pedagogy, responsible AI integration, and the design of AI-enabled learning environments that support student agency.

  PublisherOA PDF

• Spatiotemporal Change-Points in Development Discourse: Insights from Social Media in Low-Resource Contexts

  ArXiv.org · 2026-01-10

  articleOpen accessSenior author

  This study investigates the spatiotemporal evolution of development discourse in low-resource settings. Analyzing more than two years of geotagged X data from Zambia, we introduce a mixed-methods pipeline utilizing topic modeling, change-point detection, and qualitative coding to identify critical shifts in public debate. We identify seven recurring themes, including public health challenges and frustration with government policy, shaped by regional events and national interventions. Notably, we detect discourse changepoints linked to the COVID19 pandemic and a geothermal project, illustrating how online conversations mirror policy flashpoints. Our analysis distinguishes between the ephemeral nature of acute crises like COVID19 and the persistent, structural reorientations driven by long-term infrastructure projects. We conceptualize "durable discourse" as sustained narrative engagement with development issues. Contributing to HCI and ICTD, we examine technology's socioeconomic impact, providing practical implications and future work for direct local engagement.

  PublisherOA PDF

• Racism, resistance, and Reddit: how popular culture sparks online reckonings

  Information Communication & Society · 2026-04-07

  articleOpen accessSenior author

  This study examines how Reddit users engaged with the racial narratives of Lovecraft Country and Watchmen, two television series that reimagine historical racial trauma. Drawing on narrative persuasion and multistep flow theory, we analyze 3,879 Reddit comments using topic modeling and critical discourse analysis. We identify three dynamic social roles advocates, adversaries, and adaptives and explore how users move between them in response to racial discourse. Findings reveal how Reddits pseudonymous affordances shape role fluidity, opinion leadership, and moral engagement. While adversaries minimized or rejected racism as exaggerated, advocates shared standpoint experiences and historical resources to challenge these claims. Adaptive users shifted perspectives over time, demonstrating how online publics can foster critical racial learning. This research highlights how popular culture and participatory platforms intersect in shaping collective meaning making around race and historical memory.

  PublisherDOI

• Beyond the Silence: How Men Navigate Infertility Through Digital Communities and Data Sharing

  2026-04-13

  articleOpen access1st authorCorresponding

  Men experiencing infertility face unique challenges navigating Traditional Masculinity Ideologies that discourage emotional expression and help-seeking. This study examines how Reddit’s r/maleinfertility community helps overcome these barriers through digital support networks. Using topic modeling (115 topics), network analysis (11 micro-communities), and time-lagged regression on 11,095 posts and 79,503 comments from 8,644 users, we found the community functions as a hybrid space: informal diagnostic hub, therapeutic commons, and governed institution. Medical advice dominates discourse (63.3%), while emotional support (7.4%) and moderation (29.2%) create essential infrastructure. Sustained engagement correlates with actionable guidance and affiliation language, not emotional processing. Network analysis revealed structurally cohesive but topically diverse clusters without echo chamber characteristics. Cross-posters (20% of users) who bridge r/maleinfertility and the gender-mixed r/infertility community serve as navigators and mentors, transferring knowledge between spaces. These findings inform trauma-informed design for stigmatized health communities, highlighting role-aware systems and navigation support.

  PublisherDOI

• Learning to Live with AI: How Students Develop AI Literacy Through Naturalistic ChatGPT Interaction

  Open MIND · 2026-01-28

  preprint1st authorCorresponding

  How do students develop AI literacy through everyday practice rather than formal instruction? While normative AI literacy frameworks proliferate, empirical understanding of how students actually learn to work with generative AI remains limited. This study analyzes 10,536 ChatGPT messages from 36 undergraduates over one academic year, revealing five use genres -- academic workhorse, emotional companion, metacognitive partner, repair and negotiation, and trust calibration -- that constitute distinct configurations of student-AI learning. Drawing on domestication theory and emerging frameworks for AI literacy, we demonstrate that functional AI competence emerges through ongoing relational negotiation rather than one-time adoption. Students develop sophisticated genre portfolios, strategically matching interaction patterns to learning needs while exercising critical judgment about AI limitations. Notably, repair work during AI breakdowns produces substantial learning about AI capabilities, developing what we term "repair literacy" -- a crucial but underexplored dimension of AI competence. Our findings offer educators empirically grounded insights into how students actually learn to work with generative AI, with implications for AI literacy pedagogy, responsible AI integration, and the design of AI-enabled learning environments that support student agency.

  DOI

• Spatiotemporal Change-Points in Development Discourse: Insights from Social Media in Low-Resource Contexts

  arXiv (Cornell University) · 2026-01-10

  preprintOpen accessSenior author

  This study investigates the spatiotemporal evolution of development discourse in low-resource settings. Analyzing more than two years of geotagged X data from Zambia, we introduce a mixed-methods pipeline utilizing topic modeling, change-point detection, and qualitative coding to identify critical shifts in public debate. We identify seven recurring themes, including public health challenges and frustration with government policy, shaped by regional events and national interventions. Notably, we detect discourse changepoints linked to the COVID19 pandemic and a geothermal project, illustrating how online conversations mirror policy flashpoints. Our analysis distinguishes between the ephemeral nature of acute crises like COVID19 and the persistent, structural reorientations driven by long-term infrastructure projects. We conceptualize "durable discourse" as sustained narrative engagement with development issues. Contributing to HCI and ICTD, we examine technology's socioeconomic impact, providing practical implications and future work for direct local engagement.

  PublisherDOI

• Digital pulse of development: Leveraging social media discourse for poverty analysis

  Information Processing & Management · 2026-04-10 · 1 citations

  articleOpen accessSenior author

  • We build a contextualized Twitter-based language model to construct poverty metrics. • Twitter discourse predicts village-level poverty. • Less affluent communities focus more on concrete, local development concerns. • Kriging interpolation improves sparse social media data with uncertainty estimates. • We propose a novel data pipeline for poverty assessment which utilizes citizen participation. We present a novel pipeline for poverty assessment using social media and apply it to a dataset of 1.2 million geotagged tweets from Zambia. Leveraging mixed-methods topic modeling with domain-guided feature selection, we develop an interpretable language model that explains more than 60 % of the variation in village-level wealth. Our findings show that the tweets from poorer villages emphasize local, concrete needs, whereas those from wealthier villages focus on abstract development concepts. We also compare imputation methods for data-sparse contexts and find that kriging improves predictive accuracy by 15 % over standard approaches, while providing uncertainty quantification for adaptive sampling. This work demonstrates the viability of social media discourse as a participatory, scalable poverty monitoring tool in regions with limited data.

  PublisherDOI

• Patient-Made Knowledge Networks: Long COVID Discourse, Epistemic Injustice, and Online Community Formation

  Open MIND · 2026-02-16

  preprint1st authorCorresponding

  Long COVID represents an unprecedented case of patient-led illness definition, emerging through Twitter in May 2020 when patients began collectively naming, documenting, and legitimizing their condition before medical institutions recognized it. This study examines 2.8 million tweets containing #LongCOVID to understand how contested illness communities construct knowledge networks and respond to epistemic injustice. Through topic modeling, reflexive thematic analysis, and exponential random graph modeling (ERGM), we identify seven discourse themes spanning symptom documentation, medical dismissal, cross-illness solidarity, and policy advocacy. Our analysis reveals a differentiated ecosystem of user roles -- including patient advocates, research coordinators, and citizen scientists -- who collectively challenge medical gatekeeping while building connections to established ME/CFS advocacy networks. ERGM results demonstrate that tie formation centers on epistemic practices: users discussing knowledge sharing and community building formed significantly more network connections than those focused on policy debates, supporting characterization of this space as an epistemic community. Long COVID patients experienced medical gaslighting patterns documented across contested illnesses, yet achieved WHO recognition within months -- contrasting sharply with decades-long struggles of similar conditions. These findings illuminate how social media affordances enable marginalized patient populations to rapidly construct alternative knowledge systems, form cross-illness coalitions, and contest traditional medical authority structures.

  DOI

• Digital Technology Use Among Age-Friendly Community Initiatives in the United States

  Innovation in Aging · 2026-03-28

  articleOpen accessSenior author

  Abstract Background and Objectives Although studies have established the importance of various types of resources for age-friendly community (AFC) initiatives, there has been little research on digital technologies. This study explored the extent of, and contexts for, digital technology use among AFC initiatives in the United States. Research Design and Methods This concurrent mixed-methods study used data from AARP’s 2024 Survey of the National Network of Age-Friendly States and Communities (NAFSC) (N = 200) alongside qualitative interviews with 13 communities that reported in the survey relatively high levels or novel types of digital technology use. Results Over 90% of survey respondents indicated using at least one technology, the most common being online survey platforms (65%), social media (64%), cloud-based video conferencing (57%), organizational websites (56%), and collaborative file sharing (54%). Initiatives later into the NAFSC program cycle, led by nonprofits or higher education, and with more sources of support, reported using a greater variety of tools. The qualitative analysis identified human capital, alongside the digital infrastructure and financial capital of collaborating organizations, as conditions for technology use and access. Shifting initiative circumstances, as well as perceptions of older adults’ digital capacities and preferences, also influenced technology use. Discussion and Implications Our findings support digital capital as a central component of the development and implementation of AFC initiatives in the context of organizational, network, and community contexts. We discuss how findings can guide future research to enhance the strategic use of technology toward greater AFC impact.

  PublisherDOI

• Understanding credibility: toward a networked evidence model of health information

  Information Research an international electronic journal · 2026-03-20

  articleOpen accessSenior author

  Introduction. Severe health issues trigger urgent information needs, yet digital environments complicate judgments of what counts as credible evidence. Traditional authority rooted in medical expertise now intersects with peer testimony, platform structures, and algorithmic curation. Method. We analysed qualitative interviews with 23 parents whose children contracted COVID-19, extending Uncertainty in Illness Theory (UIT) by reinterpreting the concept of ‘credible authority’ through a new theoretical lens. Analysis. Using an abductive, theory-building approach and a crystallisation immersion method, we examined how parents enacted epistemic practices in digital health contexts. Results. We propose the networked evidence model (NEM), which shows that health information is actively organised, validated, circulated, and trusted within socio-technical systems. Evidence was shaped through alignment across institutional expertise, testimonial resonance, and platform signals. Conclusion. NEM reframes credible authority as a networked accomplishment, advancing information science and informing the design of systems that promote equitable, transparent, and trustworthy access to health knowledge.

  PublisherOA PDFDOI

Frequent coauthors

• Sarita Schoenebeck

  9 shared

• Joyce Y. Lee

  The Ohio State University

  5 shared

• Frank Bentley

  5 shared

• Janice Tsai

  Google (United States)

  3 shared

• Eunhye Ahn

  Washington University in St. Louis

  2 shared

• Bryan Semaan

  University of Colorado Boulder

  2 shared

• Shagun Jhaver

  2 shared

• Joyojeet Pal

  University of Michigan–Ann Arbor

  2 shared

Labs

• Behavioral Informatics LabPI

Education

• PhD, School of Informatio

  University of Michigan

  2020

Awards & honors

• AI 2000 Most Influential Scholar Honorable Mention in Human-…