Liu, J., So, J., & Pei, R. (2025). Diminished valuation in the brain: How repeated exposure reduces health message engagement. Annals of Behavioral Medicine. https://doi.org/10.1093/abm/kaaf037
So, J., & Song, H.1 (2023). Two faces of message repetition: Audience favorability as a determinant of the explanatory capacities of processing fluency and message fatigue. Journal of Communication, 73, 574-586. https://doi:10.1093/joc/jqad025
So, J., & Liu, J. (2023). The role of audience favorability in processing (un)familiar messages: A heuristic-systematic model perspective. Human Communication Research, 49, 383-395. https://doi.org/10.1093/hcr/hqad024
Hwang, Y., So, J., & Jeong, S. (2023). Does COVID-19 message fatigue lead to misinformation acceptance? An extension of the risk information seeking and processing model. Health Communication, 38, 2742-2749. https://doi.org/10.1080/10410236.2022.2111636
So, J., Shim, M., & Song, H.2 (2023). Diffusion of COVID-19 misinformation: Mechanisms for threat- and efficacy-related misinformation diffusion. Computers in Human Behavior, 149, 107967. https://doi.org/10.1016/j.chb.2023.107967
Song, H.1, & So, J. (2023). Message fatigue beyond the health message context: A replication and further extension of So et al. (2017). Human Communication Research, 49, 339-344. https://doi.org/10.1093/hcr/hqad021
So, J. (2022). Counterproductive effects of overfamiliar anti-tobacco messages on smoking cessation intentions via message fatigue and resistance to persuasion. Psychology of Addictive Behaviors, 36, 931-941. https://doi.org/10.1037/adb0000776 [Lead Article]
So, J. & Alam, N.* (2019). Predictors and effects of anti-obesity message fatigue: A thought-listing analysis. Health Communication, 34, 755–763. DOI:10.1080/10410236.2018.1434736
So, J., & Popova, L. (2018). A profile of individuals with anti-tobacco message fatigue. American Journal of Health Behavior, 42, 109-118. DOI: https://doi.org/10.5993/AJHB.42.1.11
Kim, S.* & So, J. (2018). How message fatigue toward health messages leads to ineffective persuasive outcomes: Examining the mediating roles of reactance and inattention. Journal of Health Communication, 23, 109-116.
DOI: 10.1080/10810730.2017.1414900
So, J., Kim, S.,* & Cohen, H.* (2017). Message fatigue: Conceptual definition, operationalization, and correlates. Communication Monographs, 84, 5-29. DOI: 10.1080/03637751.2016.1250429 [Lead Article]
Kim, H.*, Han, J. Y., So, J., & Seo, Y.* (2020). An investigation of cognitive processing of fear appeal messages promoting HPV vaccination: Predictors and outcomes of magnitude and valence of cognitive responses. Journal of Health Communication, 25, 885-894. https://doi.org/10.1080/10810730.2020.1842566
Owusu, D., So, J., & Popova, L. (2019). Reactions to tobacco warning labels: Predictors and outcomes of adaptive and maladaptive responses. Addiction Research and Theory, 27, 383-393. DOI: 10.1080/16066359.2018.1531127
Popova, L., So, J., Sangalang, A. L., Neilands, T. B., & Ling, P.M. (2017). Do emotions spark interest in alternative tobacco products? Health Education and Behavior, 44, 598-612. DOI: 10.1177/1090198116683169
So, J., Kuang, K.,* & Cho, H. (2016). Reexamining fear appeal models from cognitive appraisal theory and functional emotion theory perspectives. Communication Monographs, 83, 120-144. DOI:10.1080/03637751.2015.1044257
So, J. (2013). A further extension of the extended parallel processing model (E-EPPM): Implications of cognitive appraisal theory of emotions and dispositional coping style. Health Communication, 28, 72-83. DOI:10.1080/10410236.2012.708633
Hwang, Y., So, J., & Jeong, S. (2023). Does COVID-19 message fatigue lead to misinformation acceptance? An extension of the risk information seeking and processing model. Health Communication, 38, 2742-2749. https://doi.org/10.1080/10410236.2022.2111636
So, J., Shim, M., & Song, H.2 (2023). Diffusion of COVID-19 misinformation: Mechanisms for threat- and efficacy-related misinformation diffusion. Computers in Human Behavior, 149, 107967. https://doi.org/10.1016/j.chb.2023.107967
Song, H.2, So, J., Shim, M., Kim, J., Kim, A., & Lee, K. (2023). What message features influence the intention to share misinformation about COVID-19 on social media? The role of efficacy and novelty. Computers in Human Behavior, 138, 107439.
https://doi.org/10.1016/j.chb.2022.107439 [Lead Article]
So, J., Ahn, J., & Guan, M. (2022). Beyond depth and breadth: Taking “types” of health information sought into consideration with cluster analysis. Journal of Health Communication, 27, 27-36. https://doi.org/10.1080/10810730.2022.2029978
So, J., Kuang, K., & Cho, H. (2019). Information seeking upon exposure to risk messages: Predictors, outcomes, and mediating roles of health information seeking. Communication Research, 46, 663-687. DOI: 10.1177/0093650216679536
Quan, L.*, Chung, S., Kim, Y., & So, J. (2022). Is a success story of an underdog more powerful than one of a similar other? Examining effects of model similarity and success attribution on intention to exercise. Communication Quarterly, 70, 205-225. https://doi.org/10.1080/01463373.2022.2036213
Alam, N.* & So, J. (2020). Contributions of emotional flow in narrative persuasion: An empirical test of the emotional flow framework. Communication Quarterly, 68, 161–182. DOI:10.1080/01463373.2020.1725079
So. J. & Shen, L. (2016). Personalization of risk through convergence of self- and character-risk: Narrative effects on social distance and self-character risk perception gap. Communication Research, 43, 1094–1115. DOI: 10.1177/0093650215570656
So, J. & Nabi, R. L. (2013). Reduction of social distance as an explanation for media’s influence on personal risk perceptions: An initial test of the risk convergence model. Human Communication Research, 39, 317–338. DOI: 10.1111/hcre.12005
So, J., Prestin, A., Lee, L.,* Wang, Y.,* Yen, J., & Chou, W. S. (2016). What do people like to “share” about obesity? A content analysis of frequent retweets about obesity on Twitter. Health Communication, 31, 193-206. DOI: 10.1080/10410236.2014.940675
Nabi, R. L., Prestin, A., & So, J. (2013). Facebook friends with (health) benefits?: Exploring the palliative effects of social network sites compared to interpersonal networks. Cyberpsychology, Behavior, and Social Networking, 16, 721-727. DOI:10.1089/cyber.2012.0521.
Kim, Y.*, Chung, S., & So, J. (2020). Success expectancy: A mediator for the effects of source similarity and self-efficacy on health behavior intention. Health Communication, 35, 1063-1072. DOI: 10.1080/10410236.2019.1613475
Quan, L.*, Chung, S., Kim, Y., & So, J. (2022). Is a success story of an underdog more powerful than one of a similar other? Examining effects of model similarity and success attribution on intention to exercise. Communication Quarterly, 70, 205-225. https://doi.org/10.1080/01463373.2022.2036213
Guan, M.,* & So, J. (2016). Influence of social identity on self-efficacy beliefs through perceived social support: A social identity theory perspective. Communication Studies, 67, 588–604. DOI: 10.1080/10510974.2016.1239645
Cho, H., So, J., & Lee, J. (2009). Personal, social, and cultural correlates of self-efficacy beliefs among South Korean college smokers. Health Communication, 24, 337–345. DOI: 10.1080/10410230902889381
Choi, J. H.*, & So, J. (2021). The effects of COVID-19 news frames on support for punishment policy in individuals: The mediating effects of responsibility perception and anger. Korean Journal of Journalism & Communication Studies, 65, 70-105. https://doi.org/10.20879/kjjcs.2021.65.4.002
Guan, M. & So, J. (2020). Tailoring temporal message frames to individuals’ time orientation strengthens the relationship between risk perception and behavioral intention. Journal of Health Communication, 25, 971-981. https://doi.org/10.1080/10810730.2021.1878310
Choi, J. & So, J. (2019). Effects of self-affirmation on message persuasiveness: A cross-cultural study of the U.S. and South Korea. Asian Journal of Communication, 29, 128-148. DOI: 10.1080/01292986.2018.1555265
Lauckner, C., Smith, S., Kotowski, M., Nazione, S., Stohl, C., Prestin, A. L. So, J., & Nabi, R. E. (2012). An initial investigation into naturally occurring loss- and gain-framed memorable breast cancer messages. Communication Quarterly, 60, 1-16. DOI:10.1080/01463373.2012.642269
Nabi, R., Prestin, A., & So, J. (2016). Could watching TV be good for you? Examining how media consumption patterns relate to salivary cortisol. Health Communication, 31, 1345-1355. DOI: 10.1080/10410236.2015.1061309
Lieberman, D. A., Bates, C. H., & So, J. (2009). Young children's learning with digital media. Computers in the Schools, 26, 271-283. DOI:10.1080/07380560903360194
Nabi, R. L., So, J., Prestin, A., & Pérez Torres, D. (2021). Media-based emotional coping: Examining the emotional benefits and pitfalls of media consumption. In E. Konijn, K. Doveling, & C. von Scheve (Eds.), The Routledge International Handbook of Emotions and Media, (pp. 85–101). New York: Routledge. DOI: 10.4324/9780429465758-6
Nabi, R. E., So, J., & de los Santos, T. (2013). Tracing the course of reality TV effects research. In Scharrer, E. (Ed.), The International Encyclopedia of Media Studies: Media Effects/Media Psychology, (pp. 355-373). Blackwell Publishing.
Nabi, R. L., So, J., & Prestin, A. (2010). Media-based emotional coping: Examining the emotional benefits and pitfalls of media consumption. In E. Konijn, K. Doveling, & C. von Scheve (Eds.), The Routledge handbook of emotions and mass media, (pp. 116–133). New York: Routledge.
So, J., Jeong, S., & Hwang, Y. (2017). Which type of risk information to use for whom?: Moderating role of outcome-relevant involvement in the effects of statistical and exemplified risk information on risk perceptions. Journal of Health Communication, 22, 304-311. DOI:10.1080/10810730.2016.1252819
So, J. (2012). Uses, gratifications, and beyond: Towards a model of motivated media exposure and its effects on risk perception. Communication Theory, 22, 116-137. DOI:10.1111/j.1468-2885.2012.01400.x [Lead article]
So, J., Cho, H., & Lee, J. (2011). Genre-specific media and perceptions of personal and social risk of smoking among South Korean college students. Journal of Health Communication, 16, 5, 533- 549. DOI: 10.1080/10810730.2010.546488
So, J. (2014). Emotion appraisals regarding risk. In T. Thompson (Ed.), Encyclopedia of Health Communication, (pp. 397-399). Sage.
So, J. & Song, H. (2026). Validity of a measurement scale. In L. Shen (Ed.), Quantitative Research Methods in Communication Science, (pp. 217-234). https://doi.org/10.1515/9783111087139-010
Guan, M., & So, J. (2023). Social identity theory. In E. Ho, C. L. Bylund, & J. van Weert (Eds.), The International Encyclopedia of Health Communication. New York: Wiley-Blackwell. DOI: 10.1002/9781119678816.iehc0667
Nabi, R. L., So, J., Prestin, A., & Pérez Torres, D. (2021). Media-based emotional coping: Examining the emotional benefits and pitfalls of media consumption. In E. Konijn, K. Doveling, & C. von Scheve (Eds.), The Routledge International Handbook of Emotions and Media, (pp. 85–101). New York: Routledge. DOI: 10.4324/9780429465758-6
So, J. (2014). Emotion appraisals regarding risk. In T. Thompson (Ed.), Encyclopedia of Health Communication, (pp. 397-399). Sage.
Nabi, R. E., So, J., & de los Santos, T. (2013). Tracing the course of reality TV effects research. In Scharrer, E. (Ed.), The International Encyclopedia of Media Studies: Media Effects/Media Psychology, (pp. 355-373). Blackwell Publishing.
Nabi, R. L., So, J., & Prestin, A. (2010). Media-based emotional coping: Examining the emotional benefits and pitfalls of media consumption. In E. Konijn, K. Doveling, & C. von Scheve (Eds.), The Routledge handbook of emotions and mass media, (pp. 116–133). New York: Routledge.
Department of Communication, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea