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Journal of Medical Internet Research

Citing this Article

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Published on 20.05.13 in Vol 15, No 5 (2013): May

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

Works citing "Crowdsourcing a Normative Natural Language Dataset: A Comparison of Amazon Mechanical Turk and In-Lab Data Collection"

According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.2620):

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

  1. Costela FM, Sheldon SS, Walker B, Woods RL. People with Hemianopia Report Difficulty with TV, Computer, Cinema Use, and Photography. Optometry and Vision Science 2018;:1
    CrossRef
  2. Mares M, Stephenson L, Martins N, Nathanson AI. A house divided: Parental disparity and conflict over media rules predict children's outcomes. Computers in Human Behavior 2018;81:177
    CrossRef
  3. Martins N, Matthews NL, Ratan RA. Playing by the Rules: Parental Mediation of Video Game Play. Journal of Family Issues 2017;38(9):1215
    CrossRef
  4. Bateman DR, Brady E, Wilkerson D, Yi E, Karanam Y, Callahan CM. Comparing Crowdsourcing and Friendsourcing: A Social Media-Based Feasibility Study to Support Alzheimer Disease Caregivers. JMIR Research Protocols 2017;6(4):e56
    CrossRef
  5. Sato P, Hötzel M, von Keyserlingk M. American Citizens’ Views of an Ideal Pig Farm. Animals 2017;7(12):64
    CrossRef
  6. Dixon GN. Making Vaccine Messaging Stick: Perceived Causal Instability as a Barrier to Effective Vaccine Messaging. Journal of Health Communication 2017;22(8):631
    CrossRef
  7. Woods KJP, Siegel MH, Traer J, McDermott JH. Headphone screening to facilitate web-based auditory experiments. Attention, Perception, & Psychophysics 2017;79(7):2064
    CrossRef
  8. Cardoso CS, Hötzel MJ, Weary DM, Robbins JA, von Keyserlingk MA. Imagining the ideal dairy farm. Journal of Dairy Science 2016;99(2):1663
    CrossRef
  9. Sadler PM, Sonnert G, Coyle HP, Miller KA. Identifying Promising Items: The Use of Crowdsourcing in the Development of Assessment Instruments. Educational Assessment 2016;21(3):196
    CrossRef
  10. Dixon G, McComas K, Besley J, Steinhardt J. Transparency in the food aisle: the influence of procedural justice on views about labeling GM foods. Journal of Risk Research 2016;19(9):1158
    CrossRef
  11. Dixon GN. Negative Affect as a Mechanism of Exemplification Effects. Communication Research 2016;43(6):761
    CrossRef
  12. Clarke CE, Weberling McKeever B, Holton A, Dixon GN. The Influence of Weight-of-Evidence Messages on (Vaccine) Attitudes: A Sequential Mediation Model. Journal of Health Communication 2015;20(11):1302
    CrossRef
  13. Kuang J, Argo L, Stoddard G, Bray BE, Zeng-Treitler Q. Assessing Pictograph Recognition: A Comparison of Crowdsourcing and Traditional Survey Approaches. Journal of Medical Internet Research 2015;17(12):e281
    CrossRef
  14. Hosseini M, Shahri A, Phalp K, Taylor J, Ali R. Crowdsourcing: A taxonomy and systematic mapping study. Computer Science Review 2015;17:43
    CrossRef
  15. Thawrani V, Londhe ND, Singh R. Crowdsourcing of Medical Data. IETE Technical Review 2014;31(3):249
    CrossRef
  16. Turner-McGrievy GM, Helander EE, Kaipainen K, Perez-Macias JM, Korhonen I. The use of crowdsourcing for dietary self-monitoring: crowdsourced ratings of food pictures are comparable to ratings by trained observers. Journal of the American Medical Informatics Association 2014;
    CrossRef
  17. Cui L, Carter R, Zhang G. Evaluation of a Novel Conjunctive Exploratory Navigation Interface for Consumer Health Information: A Crowdsourced Comparative Study. Journal of Medical Internet Research 2014;16(2):e45
    CrossRef
  18. Saunders DR, Bex PJ, Rose DJ, Woods RL, Pelli DG. Measuring Information Acquisition from Sensory Input Using Automated Scoring of Natural-Language Descriptions. PLoS ONE 2014;9(4):e93251
    CrossRef