Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Citing this Article

Right click to copy or hit: ctrl+c (cmd+c on mac)

Published on 17.10.16 in Vol 2, No 2 (2016): Jul-Dec

This paper is in the following e-collection/theme issue:

Works citing "Building a National Neighborhood Dataset From Geotagged Twitter Data for Indicators of Happiness, Diet, and Physical Activity"

According to Crossref, the following articles are citing this article (DOI 10.2196/publichealth.5869):

(note that this is only a small subset of citations)

  1. Huang D, Huang Y, Khanna S, Dwivedi P, Slopen N, Green K, He X, Puett R, Nguyen Q. Twitter-derived social neighborhood characteristics and individual level cardiometabolic outcomes: a cross-sectional study in a nationally representative sample (Preprint). JMIR Public Health and Surveillance 2020;
    CrossRef
  2. Wilkins E, Aravani A, Downing A, Drewnowski A, Griffiths C, Zwolinsky S, Birkin M, Alvanides S, Morris MA. Evidence from big data in obesity research: international case studies. International Journal of Obesity 2020;44(5):1028
    CrossRef
  3. Zhu B, Zheng X, Liu H, Li J, Wang P. Analysis of spatiotemporal characteristics of big data on social media sentiment with COVID-19 epidemic topics. Chaos, Solitons & Fractals 2020;140:110123
    CrossRef
  4. Cesare N, Oladeji O, Ferryman K, Wijaya D, Hendricks‐Muñoz KD, Ward A, Nsoesie EO. Discussions of miscarriage and preterm births on Twitter. Paediatric and Perinatal Epidemiology 2020;
    CrossRef
  5. Nguyen TT, Adams N, Huang D, Glymour MM, Allen AM, Nguyen QC. The Association Between State-Level Racial Attitudes Assessed From Twitter Data and Adverse Birth Outcomes: Observational Study. JMIR Public Health and Surveillance 2020;6(3):e17103
    CrossRef
  6. Felmlee DH, Blanford JI, Matthews SA, MacEachren AM, Tang W. The geography of sentiment towards the Women’s March of 2017. PLOS ONE 2020;15(6):e0233994
    CrossRef
  7. DePriest KN, Shields TM, Curriero FC. Returning to our roots: The use of geospatial data for nurse‐led community research. Research in Nursing & Health 2019;42(6):467
    CrossRef
  8. Nguyen TT, Criss S, Allen AM, Glymour MM, Phan L, Trevino R, Dasari S, Nguyen QC. Pride, Love, and Twitter Rants: Combining Machine Learning and Qualitative Techniques to Understand What Our Tweets Reveal about Race in the US. International Journal of Environmental Research and Public Health 2019;16(10):1766
    CrossRef
  9. Gibbons J, Malouf R, Spitzberg B, Martinez L, Appleyard B, Thompson C, Nara A, Tsou M, Danforth CM. Twitter-based measures of neighborhood sentiment as predictors of residential population health. PLOS ONE 2019;14(7):e0219550
    CrossRef
  10. Hobbiss MH, Fairnie J, Jafari K, Lavie N. Attention, mindwandering, and mood. Consciousness and Cognition 2019;72:1
    CrossRef
  11. Shelton RC, Lee M, Brotzman LE, Crookes DM, Jandorf L, Erwin D, Gage-Bouchard EA. Use of social network analysis in the development, dissemination, implementation, and sustainability of health behavior interventions for adults: A systematic review. Social Science & Medicine 2019;220:81
    CrossRef
  12. Cesare N, Dwivedi P, Nguyen QC, Nsoesie EO. Use of social media, search queries, and demographic data to assess obesity prevalence in the United States. Palgrave Communications 2019;5(1)
    CrossRef
  13. Leatherdale ST, Lee J. Artificial intelligence (AI) and cancer prevention: the potential application of AI in cancer control programming needs to be explored in population laboratories such as COMPASS. Cancer Causes & Control 2019;30(7):671
    CrossRef
  14. Huang Y, Huang D, Nguyen QC. Census Tract Food Tweets and Chronic Disease Outcomes in the U.S., 2015–2018. International Journal of Environmental Research and Public Health 2019;16(6):975
    CrossRef
  15. Velasco K, Paxton P, Ressler RW, Weiss I, Pivnick L. Do National Service Programs Improve Subjective Well-Being in Communities?. The American Review of Public Administration 2019;49(3):275
    CrossRef
  16. Liu S, Chen B, Kuo A. Monitoring Physical Activity Levels Using Twitter Data: Infodemiology Study. Journal of Medical Internet Research 2019;21(6):e12394
    CrossRef
  17. Nguyen TT, Meng H, Sandeep S, McCullough M, Yu W, Lau Y, Huang D, Nguyen QC. Twitter-derived measures of sentiment towards minorities (2015–2016) and associations with low birth weight and preterm birth in the United States. Computers in Human Behavior 2018;89:308
    CrossRef
  18. DeGregory KW, Kuiper P, DeSilvio T, Pleuss JD, Miller R, Roginski JW, Fisher CB, Harness D, Viswanath S, Heymsfield SB, Dungan I, Thomas DM. A review of machine learning in obesity. Obesity Reviews 2018;19(5):668
    CrossRef
  19. Muralidhara S, Paul MJ. #Healthy Selfies: Exploration of Health Topics on Instagram. JMIR Public Health and Surveillance 2018;4(2):e10150
    CrossRef
  20. Pearce JR. Complexity and Uncertainty in Geography of Health Research: Incorporating Life-Course Perspectives. Annals of the American Association of Geographers 2018;108(6):1491
    CrossRef
  21. Cao X, MacNaughton P, Deng Z, Yin J, Zhang X, Allen J. Using Twitter to Better Understand the Spatiotemporal Patterns of Public Sentiment: A Case Study in Massachusetts, USA. International Journal of Environmental Research and Public Health 2018;15(2):250
    CrossRef
  22. Timmins KA, Green MA, Radley D, Morris MA, Pearce J. How has big data contributed to obesity research? A review of the literature. International Journal of Obesity 2018;42(12):1951
    CrossRef
  23. Roccetti M, Marfia G, Salomoni P, Prandi C, Zagari RM, Gningaye Kengni FL, Bazzoli F, Montagnani M. Attitudes of Crohn’s Disease Patients: Infodemiology Case Study and Sentiment Analysis of Facebook and Twitter Posts. JMIR Public Health and Surveillance 2017;3(3):e51
    CrossRef
  24. Nguyen QC, Brunisholz KD, Yu W, McCullough M, Hanson HA, Litchman ML, Li F, Wan Y, VanDerslice JA, Wen M, Smith KR. Twitter-derived neighborhood characteristics associated with obesity and diabetes. Scientific Reports 2017;7(1)
    CrossRef
  25. Meng H, Kath S, Li D, Nguyen QC, Giraud-Carrier C. National substance use patterns on Twitter. PLOS ONE 2017;12(11):e0187691
    CrossRef
  26. Delir Haghighi P, Kang Y, Buchbinder R, Burstein F, Whittle S. Investigating Subjective Experience and the Influence of Weather Among Individuals With Fibromyalgia: A Content Analysis of Twitter. JMIR Public Health and Surveillance 2017;3(1):e4
    CrossRef
  27. Luhmann M. Using Big Data to study subjective well-being. Current Opinion in Behavioral Sciences 2017;18:28
    CrossRef
  28. Nguyen Q, Meng H, Li D, Kath S, McCullough M, Paul D, Kanokvimankul P, Nguyen T, Li F. Social media indicators of the food environment and state health outcomes. Public Health 2017;148:120
    CrossRef
  29. Nguyen QC, McCullough M, Meng H, Paul D, Li D, Kath S, Loomis G, Nsoesie EO, Wen M, Smith KR, Li F. Geotagged US Tweets as Predictors of County-Level Health Outcomes, 2015–2016. American Journal of Public Health 2017;107(11):1776
    CrossRef
  30. Paul MJ, Dredze M. Social Monitoring for Public Health. Synthesis Lectures on Information Concepts, Retrieval, and Services 2017;9(5):1
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/publichealth.5869)

:
  1. Spitzberg BH, Tsou M, Jung C. The Handbook of Applied Communication Research. 2020. :163
    CrossRef
  2. Sandhu M, Giabbanelli PJ, Mago VK. Social Computing and Social Media. Design, Human Behavior and Analytics. 2019. Chapter 31:434
    CrossRef
  3. Lim KH, Lee KE, Kendal D, Rashidi L, Naghizade E, Feng Y, Wang J. Smart Cities: Issues and Challenges. 2019. :77
    CrossRef