When Health Information Meets Social Media: Exploring Virality on Sina Weibo

Health Communication

Volumn 32, Issue 10, 2017, Pages 1252-1260

  Liu, Xinchuan ^a   Lu, Jia ^b   Wang, Haiyan ^b  

^a PEKING UNIVERSITY   (China)

^b TSINGHUA UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

CONTENT ANALYSIS; HUMAN; MEDICAL INFORMATION; PRIVACY; PROBABILITY SAMPLE; SOCIAL MEDIA; TRANSCRIPTION REGULATION; BLOGGING; CHINA; INFORMATION DISSEMINATION; PROCEDURES;

BLOGGING; CHINA; HEALTH COMMUNICATION; HUMANS; INFORMATION DISSEMINATION; SOCIAL MEDIA;

EID: 84991273852     PISSN: 10410236     EISSN: 15327027     Source Type: Journal    
DOI: 10.1080/10410236.2016.1217454     Document Type: Article

References (54)

1. Adams, S. A., (2010). Revisiting the online health information reliability debate in the wake of “web 2.0”:An inter-disciplinary literature and website review. International Journal of Medical Informatics, 79, 391–400. doi:10.1016/j.ijmedinf.2010.01.006
2. Alhabash, S., & McAlister, A. R., (2015). Redefining virality in less broad strokes:Predicting viral behavioral intentions from motivations and uses of Facebook and Twitter. New Media & Society, 17, 1317–1339. doi:10.1177/1461444814523726
3. Averbeck, J. M., Jones, A., & Robertson, K., (2011). Prior knowledge and health messages:An examination of affect as heuristics and information as systematic processing for fear appeals. Southern Communication Journal, 76, 35–54. doi:10.1080/10417940902951824
4. Baker, S. M., & Petty, R. E., (1994). Majority and minority influence:Source-position imbalance as a determinant of message scrutiny. Journal of Personality and Social Psychology, 67, 5–19. doi:10.1037/0022-3514.67.1.5
5. Barbalet, J. M., (1998). Emotion, social theory, and social structure:A macrosociological approach. Cambridge, UK:Cambridge University Press.
6. Barnes, S. B., (2006). A privacy paradox:Social networking in the United States. First Monday, 11(9). Retrieved from http://firstmonday.org/issues/issue11_9/barnes/index.html
7. Bonabeau, E., (2004). The perils of the imitation age. Harvard Business Review, 82(6), 45–54.
8. Boyd, D., Golder, S., & Lotan, D., (2010, January 6). Tweet, tweet, retweet:Conversational aspects of retweeting on Twitter (HICSS-43). Kauai, HI:IEEE.
9. Castells, M., (1996). The rise of the network society. Malden, MA:Blackwell.
10. Chaiken, S., (1980). Heuristic versus systematic information processing and the use of source versus message cues in persuasion. Journal of Personality and Social Psychology, 39, 752–766. doi:10.1037/0022-3514.39.5.752
11. Chew, C., & Eysenbach, G., (2010). Pandemics in the age of Twitter:Content analysis of tweets during the 2009 H1N1 outbreak. PLoS ONE, 5(11), e14118. doi:10.1371/journal.pone.0014118
12. Choi, Y. B., Capitan, K. E., Krause, J. S., & Streeper, M. M., (2006). Challenges associated with privacy in health care industry:Implementation of HIPAA and the security rules. Journal of Medical Systems, 30, 57–64. doi:10.1007/s10916-006-7405-0
13. Chou, W. Y. S., Hunt, Y. M., Beckjord, E. B., Moser, R. P., & Hesse, B. W., (2009). Social media use in the United States:Implications for health communication. Journal of Medical Internet Research, 11(4), e48. doi:10.2196/jmir.1249
14. Cody, R., & Lee, C., (1990). Behaviors, beliefs, and intentions in skin cancer prevention. Journal of Behavioral Medicine, 13, 373–389. doi:10.1007/BF00844885
15. Eysenbach, G., (2008). Credibility of health information and digital media:New perspectives and implications for youth. In M. J., Metzger & A. J., Flanagin (Eds.), Digital media, youth, and credibility (pp. 123–154). Cambridge, MA:MIT Press.
16. Fritch, J. W., & Cromwell, R. L., (2001). Evaluating Internet resources:Identity, affiliation, and cognitive authority in a networked world. Journal of the American Society for Information Science and Technology, 52, 499–507. doi:10.1002/(ISSN)1532-2890
17. George, D. R., (2011). “Friending Facebook?” A minicourse on the use of social media by health professionals. Journal of Continuing Education in the Health Professions, 31, 215–219. doi:10.1002/chp.20129
18. Gorrell, G., & Bontcheva, K., (2014). Classifying Twitter favorites:Like, bookmark, or thanks? Journal of the Association for Information Science and Technology. doi:10.1002/asi.23352
19. Greene, K., & Brinn, L. S., (2003). Messages influencing college women’s tanning bed use:Statistical versus narrative evidence format and a self-assessment to increase perceived susceptibility. Journal of Health Communication, 8, 443–461. doi:10.1080/713852118
20. Greysen, S. R., Kind, T., & Chretien, K. C., (2010). Online professionalism and the mirror of social media. Journal of General Internal Medicine, 25, 1227–1229. doi:10.1007/s11606-010-1447-1
21. Guseh, J. S., Brendel, R. W., & Brendel, D. H., (2009). Medical professionalism in the age of online social networking. Journal of Medical Ethics, 35, 584–586. doi:10.1136/jme.2009.029231
22. Hansen, L., Arvidsson, A., Nielsen, F., Colleoni, E., & Etter, M., (2011). Good friends, bad news-affect and virality in Twitter. In J. J., Park, L. T., Yang, & C., Lee (Eds.), Future information technology (pp. 34–43). Berlin, Germany:Springer.
23. Hastings, G., Stead, M., & Webb, J., (2004). Fear appeals in social marketing:Strategic and ethical reasons for concern. Psychology & Marketing, 21, 961–986. doi:10.1002/(ISSN)1520-6793
24. Jenders, M., Kasneci, G., & Naumann, F., (2013, May 13–17). Analyzing and predicting viral tweets. Proceedings WWW 2013 Companion, Rio de Janeiro, Brazil (pp. 657–664).
25. Kline, S. L., (1987). Self-monitoring and attitude-behavior correspondence in cable television subscription. Journal of Social Psychology, 127, 605–609.
26. Kopfman, J. E., Smith, S. W., Yun, J. K. A., & Hodges, A., (1998). Affective and cognitive reactions to narrative versus statistical evidence organ donation messages. Journal of Applied Communication Research, 26, 279–300. doi:10.1080/00909889809365508
27. Lash, S., (2002). Critique of information. London, UK:Sage.
28. Lee, J. Y., & Sundar, S. S., (2013). To tweet or to retweet? That is the question for health professionals on Twitter. Health Communication, 28, 509–524. doi:10.1080/10410236.2012.700391
29. Leshner, G., & Cheng, I., (2009). The effects of frame, appeal, and outcome extremity of antismoking messages on cognitive processing. Health Communication, 24, 219–227. doi:10.1080/10410230902804117
30. Levin, I. P., Wall, L. L., Dolezal, J. M., & Norman, K. L., (1972). Different weighting of positive and negative traits in impression formation as a function of prior exposure. Journal of Experimental Psychology, 97, 114–115. doi:10.1037/h0033846
31. Lewis, I. M., Watson, B., Tay, R., & White, K. M., (2007). The role of fear appeals in improving driver safety:A review of the effectiveness of fear-arousing (threat) appeals in road safety advertising. International Journal of Behavioral and Consultation Therapy, 3, 203–222. doi:10.1037/h0100799
32. Maher, C. A., Lewis, L. K., Ferrar, K., Marshall, S., De Bourdeaudhuij, I., & Vandelanotte, C., (2014). Are health behavior change interventions that use online social networks effective? A systematic review. Journal of Medical Internet Research, 16(2), e40. doi:10.2196/jmir.2952
33. Meier, F., Elsweiler, D., & Wilson, M. L., (2014, June 1–4). More than liking and bookmarking? Towards understanding Twitter favoriting behavior. Proceedings of the Eighth International AAAI Conference on Weblogs and Social Media, Ann Arbor, Michigan, USA (pp. 346–355). Palo Alto, CA:AAAI Press.
34. Metaxas, P., Mustafaraj, E., Wong, K., Zeng, L., O’Keefe, M., & Finn, S., (2014, November). Do retweets indicate interest, trust, agreement? Computation and Journalism Symposium, New York, NY.
35. Metzger, M. J., Flanagin, A. J., & Medders, R., (2010). Social and heuristic approaches to credibility evaluation online. Journal of Communication, 60, 413–439. doi:10.1111/jcom.2010.60.issue-3
36. Neiger, B. L., Thackeray, R., Burton, S. H., Thakeray, C. R., & Reese, J. H., (2013). Use of Twitter among local health departments:An analysis of information sharing, engagement, and action. Journal of Medical Internet Research, 15(8), e177. doi:10.2196/jmir.2775
37. O’Keefe, D., & Jensen, J. D., (2008). Do loss-framed persuasive messages engender greater message processing than do gain-framed messages? A meta-analytic review. Communication Studies, 59, 51–67. doi:10.1080/10510970701849388
38. O’Keefe, D. J., & Jensen, J. D., (2007). The relative persuasiveness of gain-framed and loss-farmed messages for encouraging disease prevention behaviors:A meta-analytic review. Journal of Health Communication, 12, 623–644. doi:10.1080/10810730701615198
39. O’Keefe, D. J., & Jensen, J. D., (2009). The relative persuasiveness of gain-framed and loss-framed messages for encouraging disease detection behaviors:A meta-analytic review. Journal of Communication, 59, 296–316. doi:10.1111/j.1460-2466.2009.01417.x
40. Papacharissi, Z., (2010). A private sphere:Democracy in a digital age. Cambridge, MA:Polity.
41. Parrott, R., Silk, K., Dorgan, K., Condit, C., & Harris, T., (2005). Risk comprehension and judgments of statistical evidentiary appeals when a picture is not worth a thousand words. Human Communication Research, 31, 423–452.
42. Recuero, R., Araújo, R. M., & Zago, G., (2011). How does social capital affect retweets? Proceedings of Fifth International AAAI Conference on Weblogs and Social Media (ICWSM), Barcelona, Spain (pp. 305–312). Palo Alto, CA:AAAI Press.
43. Reinard, J. C., (1988). The empirical study of the persuasive effects of evidence:The status after fifty years of research. Human Communication Research, 15, 3–59. doi:10.1111/j.1468-2958.1988.tb00170.x
44. Reynolds, R. A., & Reynolds, J. L., (2002). Evidence. In J. E., Dillard & M., Pfau (Eds.), The persuasion handbook:Developments in theory and practice (pp. 513–542). Thousand Oaks, CA:Sage.
45. Rothman, A. J., Bartels, R. D., Wlaschin, J., & Salovey, P., (2006). The strategic use of gain- and loss-framed messages to promote health behavior:How theory can inform practice. Journal of Communication, 56(S1), S202–S220. doi:10.1111/j.1460-2466.2006.00290.x
46. Salovey, P., & Williams-Piehota, P., (2004). Field experiments in social psychology:Message framing and the promotion of health protective behaviors. American Behavioral Scientist, 47, 488–505. doi:10.1177/0002764203259293
47. Smock, A. D., Ellison, N. B., Lampe, C., & Wohn, D. Y., (2011). Facebook as a toolkit:A U&G approach to unbundling feature use. Computers in Human Behavior, 27, 2322–2329. doi:10.1016/j.chb.2011.07.011
48. Starr, P., (1999). Health and the right to privacy. American Journal of Law & Medicine, 25, 193–201.
49. Sundar, S. S., (2008). The MAIN model:A heuristic approach to understanding technology effects on credibility. In M. J., Metzger & A. J., Flanagin (Eds.), Digital media, youth, and credibility (pp. 72–100). Cambridge, MA:MIT Press.
50. Thackeray, R., Neiger, B. L., Burton, S. H., & Thackeray, C. R., (2013). Analysis of the purpose of state health departments’ tweets:Information sharing, engagement, and action. Journal of Medical Internet Research, 15(11), e255. doi:10.2196/jmir.3002
51. Todorov, A., Chaiken, S., & Henderson, M. D., (2002). The heuristics-systematic model of socialinformation processing. In J. P., Dillard & M., Pfau (Eds.), Persuasion handbook:Advancements in theory and practice (pp. 195–213). London, UK:Sage.
52. Trumbo, C. W., (2002). Information processing and risk perception:An adaptation of the heuristic-systematic model. Journal of Communication, 52, 367–382. doi:10.1111/jcom.2002.52.issue-2
53. Yu, G., (2011). Public opinion in the Chinese society:Annual report 2011. Beijing, China:People’s Daily Press.
54. Zhang, L., (2016). Reflexive expectations in EU–China relations:A media analysis approach. Journal of Common Market Studies, 54, 463–479. doi:10.1111/jcms.12286