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A Think-Aloud Study to Understand Factors Affecting Online Health Search

, , and . Proceedings of the 2020 Conference on Human Information Interaction and Retrieval, page 273-282. ACM, (March 2020)
DOI: 10.1145/3343413.3377961

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The Positive and Negative Influence of Search Results on People's Decisions about the Efficacy of Medical Treatments., , , and . ICTIR, page 209-216. ACM, (2017)Catching Zika Fever: Application of Crowdsourcing and Machine Learning for Tracking Health Misinformation on Twitter., and . ICHI, page 518. IEEE Computer Society, (2017)Fake Cures: User-centric Modeling of Health Misinformation in Social Media., and . Proc. ACM Hum. Comput. Interact., 2 (CSCW): 58:1-58:20 (2018)Addressing Misinformation in Online Social Networks: Diverse Platforms and the Potential of Multiagent Trust Modeling., , , , , , , , , and 2 other author(s). Inf., 11 (11): 539 (2020)Health Misinformation in Search and Social Media.. DH, page 235-236. ACM, (2017)How COVID-19 Conspiracy Theories Spread on Twitter., , and . HICSS, page 2465-2474. ScholarSpace, (2024)e-Health for Older Adults: Navigating Misinformation., , , , , and . ICT4AWE, page 195-202. SCITEPRESS, (2021)Dynamic Sampling Meets Pooling., , , , , , , and . SIGIR, page 1217-1220. ACM, (2019)A Think-Aloud Study to Understand Factors Affecting Online Health Search, , and . Proceedings of the 2020 Conference on Human Information Interaction and Retrieval, page 273-282. ACM, (March 2020)WaterlooClarke: TREC 2015 Clinical Decision Support Track., , , and . TREC, volume 500-319 of NIST Special Publication, National Institute of Standards and Technology (NIST), (2015)