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Consumer Health Informatics

  1. Wang, X. & Lee, W.-J. (2020). Negative emotions shape the diffusion of cancer tweets: toward an integrated social network–text analytics approach. Internet Research. 
  2. Wang, X., Shi, J., Kong, H. (2020). Online health information seeking: A review and meta-analysis. Health Communication. ​​
  3. Chu, T.H.*, Su, Y.*, Kong, H.*, Shi, J., Wang, X. (2020). Online social support for intimate partner violence victims in China: Quantitative and automatic content analysis. Violence Against Women. (*Student co-author)​​
  4. Shi, J., Wang, X., Peng, T. Q., & Chen, L. (2019). Cancer-prevention messages on Chinese social media: A content analysis grounded in the Extended Parallel Process Model and Attribution Theory Model and Attribution Theory. International Journal of Communication, 13, 18.
  5. Wang, X., Chen, L., Shi, J., & Peng, T-Q. (2019). What makes cancer information viral on social media? Computers in Human Behavior, 93, 149-156.​​
  6. Chen, L.*, Wang, X.*, & Peng, T-Q. (2018). Nature and Diffusion of Gynecologic Cancer–Related Misinformation on Social Media: Analysis of Tweets. Journal of Medical Internet Research, 20, e11515. (*contributed equally).
  7. Shi J., Wang, X., Peng, T-Q., & Chen, L. (2017). Understanding interactions in virtual HIV communities: A social network analysis approach. AIDS Care, 29, 239-243. 
  8. Wang, X., Shi, J., Chen, L., & Peng, T-Q. (2016). An examination of users’ influence in online HIV/AIDS communities. Cyberpsychology, Behavior, and Social networking, 19, 314-320.​

Communicaiton

  1. ​​Dienlin, T., Johannes, N., Bowman, N. D., Masur, P. K., Engesser, S., … Wang, X., … de Vreese, C. (2020). An agenda for open science in Communication. Journal of Communication. ​​

New Media and Technologies

  1. Wang, X. & Lee, K. M. (2020). The paradox of technology innovativeness and risk perceptions - A profile of Asian smartphone users. Telematics and Informatics, 51, 101415.
  2. Wang, X. & Song, Y. (2020). Viral misinformation and echo chambers: the diffusion of rumors about Genetically Modified Organisms on social media. Internet Research, 30, 1547-1564
  3. Wang, X., Goh, D. H.-L., Lim, E.-P. (2020). Understanding continuance intention toward crowdsourcing games: A longitudinal investigation. International Journal of Human-Computer Interaction, 36, 1168-1177.​​​
  4. ​Wang, X., Goh, D. H.-L. (2020). Components of game experience: An automatic text analysis of online reviews. Entertainment Computing. 33, 100338.​
  5. Luqiu, L. W. & Wang, X. (2018). From observers to change Makers: How Hong Kong’s news media are adapting to Artificial Intelligence. In: Lee, R. & Huang, Y. (ed)s. Hong Kong Digital Media Landscape.
  6. Wang, X., Goh, D. H.-L. (2017). Video games acceptance: A meta-analysis of the extended technology acceptance model. Cyberpsychology, Behavior, and Social networking, 20, 662-671.​​​
  7. Wang, X., Goh, D. H.-L., Lim, E.-P., Vu, A. W.-L., & Alton C. Y.-K. (2017). Examining the effectiveness of gamification in human computation. International Journal of Human-Computer Interaction, 33, 813-821.
  8. Wang, X., Goh, D. H.-L., Lim, E.-P., & Vu, A. W. L. (2016). Understanding the determinants of human computation game acceptance - The effects of aesthetic experience and output quality. Online Information Review, 40, 481-496.​
  9. Wang X., Goh, D. H.-L., Lim, E.-P., & Vu, A. W.-L. (2015). Aesthetic experience and acceptance of human computation games. In: Allen R., Hunter J., Zeng M. (eds). Digital Libraries: Providing Quality Information. Lecture Notes in Computer Science, Vol 9469 (pp 264-273). Springer, Cham. (ICADL 2015, 22% acceptance rate).
  10. Wang, X. (2015). Determinants of human computation game acceptance. In Proceedings of the 2015 Annual Symposium on Computer-Human Interaction in Play (pp. 423-426). ACM. (CHI PLAY 2015, 30% acceptance rate).
  11. Wang X., Goh, D. H.-L., Lim, E.-P., & Vu, A. W.-L. (2014). Player acceptance of human computation games: An aesthetic perspective. In: Tuamsuk K., Jatowt A., Rasmussen E. (eds). The Emergence of Digital Libraries – Research and Practices. Lecture Notes in Computer Science, Vol 8839 (pp 233-242). Springer, Cham. (ICADL 2014, 23.5% acceptance rate).​​