Published on in Vol 18, No 8 (2016): August

Characterizing Twitter Discussions About HPV Vaccines Using Topic Modeling and Community Detection

Characterizing Twitter Discussions About HPV Vaccines Using Topic Modeling and Community Detection

Characterizing Twitter Discussions About HPV Vaccines Using Topic Modeling and Community Detection

Journals

  1. Xu Z. Personal stories matter: topic evolution and popularity among pro- and anti-vaccine online articles. Journal of Computational Social Science 2019;2(2):207 View
  2. Tangherlini T, Roychowdhury V, Glenn B, Crespi C, Bandari R, Wadia A, Falahi M, Ebrahimzadeh E, Bastani R. “Mommy Blogs” and the Vaccination Exemption Narrative: Results From A Machine-Learning Approach for Story Aggregation on Parenting Social Media Sites. JMIR Public Health and Surveillance 2016;2(2):e166 View
  3. Shah Z, Surian D, Dyda A, Coiera E, Mandl K, Dunn A. Automatically Appraising the Credibility of Vaccine-Related Web Pages Shared on Social Media: A Twitter Surveillance Study. Journal of Medical Internet Research 2019;21(11):e14007 View
  4. Dyda A, Shah Z, Surian D, Martin P, Coiera E, Dey A, Leask J, Dunn A. HPV vaccine coverage in Australia and associations with HPV vaccine information exposure among Australian Twitter users. Human Vaccines & Immunotherapeutics 2019;15(7-8):1488 View
  5. Stephens A, Wynn C, Stockwell M. Understanding the use of digital technology to promote human papillomavirus vaccination – A RE-AIM framework approach. Human Vaccines & Immunotherapeutics 2019;15(7-8):1549 View
  6. Paul M, Dredze M. Social Monitoring for Public Health. Synthesis Lectures on Information Concepts, Retrieval, and Services 2017;9(5):1 View
  7. Francia M, Gallinucci E, Golfarelli M. Social BI to understand the debate on vaccines on the Web and social media: unraveling the anti-, free, and pro-vax communities in Italy. Social Network Analysis and Mining 2019;9(1) View
  8. Kunneman F, Lambooij M, Wong A, Bosch A, Mollema L. Monitoring stance towards vaccination in twitter messages. BMC Medical Informatics and Decision Making 2020;20(1) View
  9. Zhang J, Centola D. Social Networks and Health: New Developments in Diffusion, Online and Offline. Annual Review of Sociology 2019;45(1):91 View
  10. Liu C, Lu X. Analyzing hidden populations online: topic, emotion, and social network of HIV-related users in the largest Chinese online community. BMC Medical Informatics and Decision Making 2018;18(1) View
  11. Huang M, ElTayeby O, Zolnoori M, Yao L. Public Opinions Toward Diseases: Infodemiological Study on News Media Data. Journal of Medical Internet Research 2018;20(5):e10047 View
  12. Massey P, Leader A, Yom-Tov E, Budenz A, Fisher K, Klassen A. Applying Multiple Data Collection Tools to Quantify Human Papillomavirus Vaccine Communication on Twitter. Journal of Medical Internet Research 2016;18(12):e318 View
  13. Zhang R, Fu J. Linking Network Characteristics of Online Social Networks to Individual Health: A Systematic Review of Literature. Health Communication 2021;36(12):1549 View
  14. Toor R, Chana I. Network Analysis as a Computational Technique and Its Benefaction for Predictive Analysis of Healthcare Data: A Systematic Review. Archives of Computational Methods in Engineering 2021;28(3):1689 View
  15. Son Y, Kang H. A Text Mining Analysis of HPV Vaccination Research Trends. Child Health Nursing Research 2019;25(4):458 View
  16. Du J, Xu J, Song H, Liu X, Tao C. Optimization on machine learning based approaches for sentiment analysis on HPV vaccines related tweets. Journal of Biomedical Semantics 2017;8(1) View
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  20. Chen T, Dredze M. Vaccine Images on Twitter: Analysis of What Images are Shared. Journal of Medical Internet Research 2018;20(4):e130 View
  21. Jelodar H, Wang Y, Rabbani M, Xiao G, Zhao R. A Collaborative Framework Based for Semantic Patients-Behavior Analysis and Highlight Topics Discovery of Alcoholic Beverages in Online Healthcare Forums. Journal of Medical Systems 2020;44(5) View
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  23. Lama Y, Chen T, Dredze M, Jamison A, Quinn S, Broniatowski D. Discordance Between Human Papillomavirus Twitter Images and Disparities in Human Papillomavirus Risk and Disease in the United States: Mixed-Methods Analysis. Journal of Medical Internet Research 2018;20(9):e10244 View
  24. Hwang Y, Kim H, Choi H, Lee J. Exploring Abnormal Behavior Patterns of Online Users With Emotional Eating Behavior: Topic Modeling Study. Journal of Medical Internet Research 2020;22(3):e15700 View
  25. Hall G, Bialek W. The statistical mechanics of Twitter communities. Journal of Statistical Mechanics: Theory and Experiment 2019;2019(9):093406 View
  26. Kearney M, Selvan P, Hauer M, Leader A, Massey P. Characterizing HPV Vaccine Sentiments and Content on Instagram. Health Education & Behavior 2019;46(2_suppl):37S View
  27. Raghupathi V, Zhou Y, Raghupathi W. Exploring Big Data Analytic Approaches to Cancer Blog Text Analysis. International Journal of Healthcare Information Systems and Informatics 2019;14(4):1 View
  28. Raghupathi V, Ren J, Raghupathi W. Studying Public Perception about Vaccination: A Sentiment Analysis of Tweets. International Journal of Environmental Research and Public Health 2020;17(10):3464 View
  29. Ortiz R, Smith A, Coyne-Beasley T. A systematic literature review to examine the potential for social media to impact HPV vaccine uptake and awareness, knowledge, and attitudes about HPV and HPV vaccination. Human Vaccines & Immunotherapeutics 2019;15(7-8):1465 View
  30. Bednarczyk R. Addressing HPV vaccine myths: practical information for healthcare providers. Human Vaccines & Immunotherapeutics 2019;15(7-8):1628 View
  31. Massey P, Budenz A, Leader A, Fisher K, Klassen A, Yom-Tov E. What Drives Health Professionals to Tweet About #HPVvaccine? Identifying Strategies for Effective Communication. Preventing Chronic Disease 2018;15 View
  32. Deiner M, Fathy C, Kim J, Niemeyer K, Ramirez D, Ackley S, Liu F, Lietman T, Porco T. Facebook and Twitter vaccine sentiment in response to measles outbreaks. Health Informatics Journal 2019;25(3):1116 View
  33. Zhang J, Le G, Larochelle D, Pasick R, Sawaya G, Sarkar U, Centola D. Facts or stories? How to use social media for cervical cancer prevention: A multi-method study of the effects of sender type and content type on increased message sharing. Preventive Medicine 2019;126:105751 View
  34. Jamison A, Broniatowski D, Smith M, Parikh K, Malik A, Dredze M, Quinn S. Adapting and Extending a Typology to Identify Vaccine Misinformation on Twitter. American Journal of Public Health 2020;110(S3):S331 View
  35. Dunn A, Surian D, Dalmazzo J, Rezazadegan D, Steffens M, Dyda A, Leask J, Coiera E, Dey A, Mandl K. Limited Role of Bots in Spreading Vaccine-Critical Information Among Active Twitter Users in the United States: 2017–2019. American Journal of Public Health 2020;110(S3):S319 View
  36. Leis A, Ronzano F, Mayer M, Furlong L, Sanz F. Evaluating Behavioral and Linguistic Changes During Drug Treatment for Depression Using Tweets in Spanish: Pairwise Comparison Study. Journal of Medical Internet Research 2020;22(12):e20920 View
  37. Karafillakis E, Martin S, Simas C, Olsson K, Takacs J, Dada S, Larson H. Methods for Social Media Monitoring Related to Vaccination: Systematic Scoping Review. JMIR Public Health and Surveillance 2021;7(2):e17149 View
  38. Gallagher J, Lawrence H. Rhetorical Appeals and Tactics in New York Times Comments About Vaccines: Qualitative Analysis. Journal of Medical Internet Research 2020;22(12):e19504 View
  39. Massey P, Kearney M, Hauer M, Selvan P, Koku E, Leader A. Dimensions of Misinformation About the HPV Vaccine on Instagram: Content and Network Analysis of Social Media Characteristics. Journal of Medical Internet Research 2020;22(12):e21451 View
  40. Du J, Luo C, Shegog R, Bian J, Cunningham R, Boom J, Poland G, Chen Y, Tao C. Use of Deep Learning to Analyze Social Media Discussions About the Human Papillomavirus Vaccine. JAMA Network Open 2020;3(11):e2022025 View
  41. Kwok S, Vadde S, Wang G. Tweet Topics and Sentiments Relating to COVID-19 Vaccination Among Australian Twitter Users: Machine Learning Analysis. Journal of Medical Internet Research 2021;23(5):e26953 View
  42. Tacheva Z, Ivanov A. Exploring the Association Between the “Big Five” Personality Traits and Fatal Opioid Overdose: County-Level Empirical Analysis. JMIR Mental Health 2021;8(3):e24939 View
  43. Massaro M, Tamburro P, La Torre M, Dal Mas F, Thomas R, Cobianchi L, Barach P. Non-pharmaceutical Interventions and the Infodemic on Twitter: Lessons Learned from Italy during the Covid-19 Pandemic. Journal of Medical Systems 2021;45(4) View
  44. Lang R, Benham J, Atabati O, Hollis A, Tombe T, Shaffer B, Burns K, MacKean G, Léveillé T, McCormack B, Sheikh H, Fullerton M, Tang T, Boucher J, Constantinescu C, Mourali M, Manns B, Marshall D, Hu J, Oxoby R. Attitudes, behaviours and barriers to public health measures for COVID-19: a survey to inform public health messaging. BMC Public Health 2021;21(1) View
  45. Vlachogiannis D, Xu Y, Jin L, González M. Correlation networks of air particulate matter ($$\hbox {PM}_{2.5}$$): a comparative study. Applied Network Science 2021;6(1) View
  46. Bandy J, Diakopoulos N. More Accounts, Fewer Links. Proceedings of the ACM on Human-Computer Interaction 2021;5(CSCW1):1 View
  47. Lossio-Ventura J, Gonzales S, Morzan J, Alatrista-Salas H, Hernandez-Boussard T, Bian J. Evaluation of clustering and topic modeling methods over health-related tweets and emails. Artificial Intelligence in Medicine 2021;117:102096 View
  48. Dunn A, Steffens M, Dyda A, Mandl K. Knowing when to act: A call for an open misinformation library to guide actionable surveillance. Big Data & Society 2021;8(1):205395172110187 View
  49. Yousefinaghani S, Dara R, Mubareka S, Papadopoulos A, Sharif S. An analysis of COVID-19 vaccine sentiments and opinions on Twitter. International Journal of Infectious Diseases 2021;108:256 View
  50. Zhang J, Xue H, Calabrese C, Chen H, Dang J. Understanding Human Papillomavirus Vaccine Promotions and Hesitancy in Northern California Through Examining Public Facebook Pages and Groups. Frontiers in Digital Health 2021;3 View
  51. Perlstein S, Verboord M, Gesser-Edelsburg A. Lockdowns, lethality, and laissez-faire politics. Public discourses on political authorities in high-trust countries during the COVID-19 pandemic. PLOS ONE 2021;16(6):e0253175 View
  52. Miah S, Vu H, Alahakoon D. A social media analytics perspective for human‐oriented smart city planning and management. Journal of the Association for Information Science and Technology 2022;73(1):119 View
  53. Li S, Wang R, Zhang Y, Lu H, Cai N, Yu Z. Potential social media influencers discrimination for concept marketing in online brand community. Journal of Intelligent & Fuzzy Systems 2021;41(1):317 View
  54. Tomaszewski T, Morales A, Lourentzou I, Caskey R, Liu B, Schwartz A, Chin J. Identifying False Human Papillomavirus (HPV) Vaccine Information and Corresponding Risk Perceptions From Twitter: Advanced Predictive Models. Journal of Medical Internet Research 2021;23(9):e30451 View
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