An Online Risk Index for the Cross-Sectional Prediction of New HIV Chlamydia, and Gonorrhea Diagnoses Across U.S. Counties and Across Years

[1]  Maarten Sap,et al.  DLATK: Differential Language Analysis ToolKit , 2017, EMNLP.

[2]  W. Goedel,et al.  Punitive laws, key population size estimates, and Global AIDS Response Progress Reports: an ecological study of 154 countries , 2017, Journal of the International AIDS Society.

[3]  Maeve Duggan,et al.  Social Media Update 2016 , 2016 .

[4]  H. Andrew Schwartz,et al.  Action Tweets Linked to Reduced County-Level HIV Prevalence in the United States: Online Messages and Structural Determinants , 2016, AIDS and Behavior.

[5]  Mark Dredze,et al.  News and Internet Searches About Human Immunodeficiency Virus After Charlie Sheen's Disclosure. , 2016, JAMA internal medicine.

[6]  B. Reboussin,et al.  The HIV Risk Profiles of Latino Sexual Minorities and Transgender Persons Who Use Websites or Apps Designed for Social and Sexual Networking , 2016, Health education & behavior : the official publication of the Society for Public Health Education.

[7]  J. Galea,et al.  Substance use and sexual risk behaviors among Peruvian MSM social media users , 2016, AIDS care.

[8]  K. Horvath,et al.  Higher eHealth Literacy is Associated With HIV Risk Behaviors among HIV‐Infected Women Who Use the Internet , 2016, The Journal of the Association of Nurses in AIDS Care : JANAC.

[9]  Kaye Wellings,et al.  Use of the Internet for Sexual Health Among Sexually Experienced Persons Aged 16 to 44 Years: Evidence from a Nationally Representative Survey of the British Population , 2016, Journal of medical Internet research.

[10]  Aaron Smith,et al.  Teens, technology and friendships , 2015 .

[11]  Todd J. Bodnar,et al.  Identifying Adverse Effects of HIV Drug Treatment and Associated Sentiments Using Twitter , 2015, JMIR public health and surveillance.

[12]  D. Chege,et al.  Monitoring quality at scale: implementing quality assurance in a diverse, multicountry HIV program , 2015, AIDS (London).

[13]  Mallory O. Johnson,et al.  Correlation of Internet Use for Health Care Engagement Purposes and HIV Clinical Outcomes Among HIV-Positive Individuals Using Online Social Media , 2015, Journal of health communication.

[14]  Gregory J. Park,et al.  Automatic personality assessment through social media language. , 2015, Journal of personality and social psychology.

[15]  B. Bedard,et al.  Using Smartphone Apps in STD Interviews to Find Sexual Partners , 2015, Public health reports.

[16]  Gregory J. Park,et al.  Psychological Language on Twitter Predicts County-Level Heart Disease Mortality , 2015, Psychological science.

[17]  John P. A. Ioannidis,et al.  Big data meets public health , 2014, Science.

[18]  S. Young.  Behavioral insights on big data: using social media for predicting biomedical outcomes. , 2014, Trends in microbiology.

[19]  Brian H. Spitzberg,et al.  The Reliability of Tweets as a Supplementary Method of Seasonal Influenza Surveillance , 2014, Journal of medical Internet research.

[20]  K. Page,et al.  Cell Phone Utilization Among Foreign-Born Latinos: A Promising Tool for Dissemination of Health and HIV Information , 2014, Journal of Immigrant and Minority Health.

[21]  B. Lewis,et al.  Methods of using real-time social media technologies for detection and remote monitoring of HIV outcomes. , 2014, Preventive medicine.

[22]  Sérgio Matos,et al.  Analysing Twitter and web queries for flu trend prediction , 2014, Theoretical Biology and Medical Modelling.

[23]  D. Lazer,et al.  The Parable of Google Flu: Traps in Big Data Analysis , 2014, Science.

[24]  Margaret L. Kern,et al.  Personality, Gender, and Age in the Language of Social Media: The Open-Vocabulary Approach , 2013, PloS one.

[25]  Megha Agrawal,et al.  Characterizing Geographic Variation in Well-Being Using Tweets , 2013, ICWSM.

[26]  Sourav Bandyopadhyay,et al.  Bringing it all together: big data and HIV research. , 2013, AIDS.

[27]  T. Graepel,et al.  Private traits and attributes are predictable from digital records of human behavior , 2013, Proceedings of the National Academy of Sciences.

[28]  Reena Mahajan,et al.  The Estimated Direct Medical Cost of Selected Sexually Transmitted Infections in the United States, 2008 , 2013, Sexually transmitted diseases.

[29]  Francisco Iacobelli,et al.  Large Scale Personality Classification of Bloggers , 2011, ACII.

[30]  N. Kleiman.  Bringing it all together: integration of physiology with anatomy during cardiac catheterization. , 2011, Journal of the American College of Cardiology.

[31]  E. Hovy,et al.  Contextual Bearing on Linguistic Variation in Social Media , 2011 .

[32]  Alberto Maria Segre,et al.  The Use of Twitter to Track Levels of Disease Activity and Public Concern in the U.S. during the Influenza A H1N1 Pandemic , 2011, PloS one.

[33]  E. Gouws,et al.  Has the quality of serosurveillance in low- and middle-income countries improved since the last HIV estimates round in 2007? Status and trends through 2009 , 2010, Sexually Transmitted Infections.

[34]  Aaron Smith,et al.  Social Media & Mobile Internet Use among Teens and Young Adults. Millennials. , 2010 .

[35]  Peter Vogel,et al.  Bringing IT All Together , 2007 .

[36]  Pierre Geurts,et al.  Extremely randomized trees , 2006, Machine Learning.

[37]  J. Pennebaker,et al.  Psychological aspects of natural language. use: our words, our selves. , 2003, Annual review of psychology.

[38]  S. Kalichman,et al.  Men Who Have Met Sex Partners via the Internet: Prevalence, Predictors, and Implications for HIV Prevention , 2002, Archives of sexual behavior.

[39]  Michael I. Jordan,et al.  Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..

[40]  B. Karon.  The clinical interpretation of the Thematic Apperception Test, Rorschach, and other clinical data: A reexamination of statistical versus clinical prediction. , 2000 .

[41]  D. C. Howell.  Statistical Methods for Psychology , 1987 .

[42]  D. Himmelstein,et al.  Public Health's Falling Share of US Health Spending. , 2016, American journal of public health.

[43]  L. Ungar,et al.  Future-oriented tweets predict lower county-level HIV prevalence in the United States. , 2015, Health psychology : official journal of the Division of Health Psychology, American Psychological Association.

[44]  Jacob Cohen.  QUANTITATIVE METHODS IN PSYCHOLOGY A Power Primer , 1992 .