Recommending research articles to consumers of online vaccination information
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Didi Surian | Adam G. Dunn | Paige Martin | Eliza Harrison | A. Dunn | Didi Surian | Paige Martin | Eliza Harrison
[1] Christian Köhler,et al. How do consumers search for and appraise health information on the world wide web? Qualitative study using focus groups, usability tests, and in-depth interviews , 2002, BMJ : British Medical Journal.
[2] Tie-Yan Liu,et al. Learning to Rank for Information Retrieval , 2011 .
[3] Tie-Yan Liu,et al. Learning to rank for information retrieval , 2009, SIGIR.
[4] Enrico W. Coiera,et al. Automatically applying a credibility appraisal tool to track vaccination-related communications shared on social media , 2019, ArXiv.
[5] Jungsuk Han,et al. Searching for Information , 2017, J. Econ. Theory.
[6] Juan Enrique Ramos,et al. Using TF-IDF to Determine Word Relevance in Document Queries , 2003 .
[7] Tianxi Cai,et al. Clinical Concept Embeddings Learned from Massive Sources of Medical Data , 2018, ArXiv.
[8] Adam G. Dunn,et al. Meeting the challenges of reporting on public health in the new media landscape , 2017 .
[9] D Charnock,et al. DISCERN: an instrument for judging the quality of written consumer health information on treatment choices. , 1999, Journal of epidemiology and community health.
[10] Enrico Coiera,et al. Prevalence of Disclosed Conflicts of Interest in Biomedical Research and Associations With Journal Impact Factors and Altmetric Scores , 2018, JAMA.
[11] Sebastian Ruder,et al. Universal Language Model Fine-tuning for Text Classification , 2018, ACL.
[12] Florence T. Bourgeois,et al. Document similarity measures can support semi-automated identification of unreported links between trial registrations and published reports , 2017, Journal of clinical epidemiology.
[13] Bart Van Looy,et al. Exploring the feasibility and accuracy of Latent Semantic Analysis based text mining techniques to detect similarity between patent documents and scientific publications , 2009, Scientometrics.
[14] Sasha Shepperd,et al. Learning to DISCERN online: applying an appraisal tool to health websites in a workshop setting. , 2004, Health education research.
[15] Stephen E. Robertson,et al. Understanding inverse document frequency: on theoretical arguments for IDF , 2004, J. Documentation.
[16] A. Kata. A postmodern Pandora's box: anti-vaccination misinformation on the Internet. , 2010, Vaccine.
[17] Annie Y. S. Lau,et al. Research Paper: Do People Experience Cognitive Biases while Searching for Information? , 2007, J. Am. Medical Informatics Assoc..
[18] J. Leask,et al. Australian Newspaper Coverage of Human Papillomavirus Vaccination, October 2006–December 2009 , 2012, Journal of health communication.
[19] M. Moran,et al. What makes anti-vaccine websites persuasive? A content analysis of techniques used by anti-vaccine websites to engender anti-vaccine sentiment , 2016 .
[20] Jeffrey Dean,et al. Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.
[21] A. Kata. Anti-vaccine activists, Web 2.0, and the postmodern paradigm--an overview of tactics and tropes used online by the anti-vaccination movement. , 2012, Vaccine.
[22] Nathan Halko,et al. Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions , 2009, SIAM Rev..
[23] Hsinchun Chen,et al. Link prediction approach to collaborative filtering , 2005, Proceedings of the 5th ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL '05).
[24] Roger Levy,et al. A new approach to cross-modal multimedia retrieval , 2010, ACM Multimedia.
[25] S. J. Bean. Emerging and continuing trends in vaccine opposition website content. , 2011, Vaccine.
[26] M. Moreno,et al. Human Papilloma Virus Vaccination. , 2019, JAMA pediatrics.
[27] Vinay Prasad,et al. Media Coverage of Medical Journals: Do the Best Articles Make the News? , 2014, PloS one.
[28] Sanjay Chawla,et al. Cross-Modal Retrieval: A Pairwise Classification Approach , 2015, SDM.
[29] S. Ratzan,et al. Addressing the vaccine confidence gap , 2011, The Lancet.
[30] Luke S. Zettlemoyer,et al. Deep Contextualized Word Representations , 2018, NAACL.
[31] Karen Spärck Jones. A statistical interpretation of term specificity and its application in retrieval , 2021, J. Documentation.
[32] Isabelle Boutron,et al. Misrepresentation of Randomized Controlled Trials in Press Releases and News Coverage: A Cohort Study , 2012, PLoS medicine.
[33] James B. Weaver,et al. Healthcare non-adherence decisions and internet health information , 2009, Comput. Hum. Behav..
[34] Patrick Seemann,et al. Matrix Factorization Techniques for Recommender Systems , 2014 .
[35] Karen Sparck Jones. A statistical interpretation of term specificity and its application in retrieval , 1972 .
[36] Enrico Coiera,et al. Automatically Appraising the Credibility of Vaccine-Related Web Pages Shared on Social Media: A Twitter Surveillance Study , 2019, Journal of medical Internet research.
[37] Lee Rainie,et al. The online health care revolution: how the web helps americans take better care of themselves , 2000 .
[38] H. Hotelling. Relations Between Two Sets of Variates , 1936 .
[39] D. Veale,et al. Classification approach , 2005, British Dental Journal.
[40] J. Hirsh,et al. The development and validation of an instrument to measure the quality of health research reports in the lay media , 2017, BMC Public Health.
[41] Isabelle Boutron,et al. Factors associated with online media attention to research: a cohort study of articles evaluating cancer treatments , 2017, Research integrity and peer review.
[42] Heidi J. Larson,et al. The biggest pandemic risk? Viral misinformation , 2018, Nature.
[43] Dario Landa Silva,et al. ES-Rank: evolution strategy learning to rank approach , 2017, SAC.