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The Korean Society for Journalism & Communication (KSJCS)
[ Article ]
Korean Journal of Journalism & Communication Studies - Vol. 65, No. 5, pp.286-327
ISSN: 2586-7369 (Online)
Print publication date 31 Oct 2021
Received 07 Jun 2021 Accepted 28 Sep 2021 Revised 07 Oct 2021
DOI: https://doi.org/10.20879/kjjcs.2021.65.5.008

여론으로서의 소셜미디어 : 이념 극단성과 SNS 유형, 이용자 관여의 관계에 대한 분석

유효선*** ; 이재국****
***성균관대학교 미디어커뮤니케이션학과 석박통합과정 hsryu0123@gmail.com
****성균관대학교 미디어커뮤니케이션학과 교수 jklee0714@g.skku.edu
Social Media as Public Opinion : Relationship between Ideological Extremity, SNS Types, and User Engagement
Hyo-sun Ryu*** ; Jae Kook Lee****
***Graduate student, Department of Media and Communication, Sungkyunkwan University hsryu0123@gmail.com
****Professor, Department of Media and Communication, Sungkyunkwan University, corresponding author jklee0714@g.skku.edu

초록

오늘날 언론은 소셜미디어 이용자 지표를 통해 여론을 해석하는 경향이 있다. 소셜미디어 데이터는 대표성이 부족하고 양극화된 목소리를 반영한다는 우려가 있기 때문에, 소셜미디어에서 누가 어떤 상황에 의견을 표현하는지 이해하는 것은 매우 중요하다. 소셜네트워크서비스(SNS) 이용자는 공감 및 추천, 댓글, 공유 등 관여 행동을 통해 자신의 의견을 표현한다. 본 연구는 SNS 관여가 청중의 존재를 염두에 둔 이용자의 의견 표현 행위라는 점에 주목해 이념 극단성과 SNS 유형이 SNS 관여도에 미치는 영향을 확인하고자 했다. 이를 위해 SNS 유형을 폐쇄형과 개방형으로 나누고 각 유형에 대한 이용자 선호가 SNS 관여도와 어떤 관련성을 갖는지 분석했다. 2016년 한국미디어패널조사 자료를 활용한 연구결과, 이념 극단성과 SNS 관여도 사이의 정적인 관련성이 확인되었다. SNS 유형과 관련, 개방형 SNS 선호도와 SNS 관여도 간의 정적인 상관관계가 발견됐지만 폐쇄형 SNS 선호도와 SNS 관여도의 관계는 통계적으로 유의미하지 않았다. 또, 이념 극단성과 각 SNS 유형에 대한 선호도의 상호작용 효과가 확인되었다. 폐쇄형 SNS 선호도와 SNS 관여도의 정적인 관계는 이념 극단성이 높은 조건에서, 개방형 SNS 선호도와 SNS 관여도의 정적인 관계는 이념 극단성이 낮은 조건에서 선명하게 나타났다. 이상의 결과는 이념 극단성이 높은 이용자들이 소셜미디어 대화를 주도하고 있을 가능성을 보여주며, 소셜미디어 이용자 지표를 여론 해석에 활용하는 데에 특별한 주의가 필요함을 시사한다.

Abstract

Journalists often use social media data to understand public opinion. However, it is likely that social media data reflect unrepresentative and polarized opinions. In this sense, it is important to understand who express their opinions on social media and in which context they do. SNS users can express their opinions by engagement (e.g., ‘liking’, recommending, commenting, and sharing), assuming the presence of an audience. Using the data from the 2016 Korean Media Panel Survey (N = 630), this study examines whether and how the user engagement was associated with ideological extremity and SNS types. For that, we categorized SNS platforms into two types (closed and open) and tested how user preference for each type was related to engagement on SNSs. The results showed that ideological extremity could positively predict user engagement. We also found a positive correlation between preference for open SNSs and engagement, while the relationship between preference for closed SNSs and engagement was not statistically significant. In addition, it was found that ideological extremity and SNS type interactively influenced user engagement. Specifically, the positive correlation between preference for closed [open] SNSs and engagement was strengthened when the ideological extremity was of a high [low] than low [high] condition. Implications of the findings are discussed.

Keywords:

Public Opinion, User Engagement, Ideological Extremity, Closed SNSs, Open SNSs

키워드:

여론, 이용자 관여, 이념 극단성, 폐쇄형 SNS, 개방형 SNS

Acknowledgments

This study is based on the data of 2016 Korean Media Panel Survey conducted by the Korea Information Society Development Institute (본 연구는 정보통신정책연구원이 2016년 실시한 미디어패널조사의 자료를 활용하였음).

This research was supported by the SungKyunKwan University and the BK21 FOUR(Graduate School Innovation) funded by the Ministry of Education(MOE, Korea) and National Research Foundation of Korea (NRF) (본 논문은 성균관대학교 및 교육부, 한국연구재단의 4단계 두뇌한국21 사업 대학원혁신으로 지원된 연구임).

References

  • Ahn, H., & Lee, S. (2015). An analytic study on private SNS for bonding social networking. Paper presented at the Social Computing and Social Media, Los Angeles, CA, USA. [https://doi.org/10.1007/978-3-319-20367-6_12]
  • Al-Rawi, A. (2019). Viral news on social media. Digital Journalism, 7(1), 63-79. [https://doi.org/10.1080/21670811.2017.1387062]
  • Alicke, M. D., & Govorun, O. (2005). The better-than-average effect. In M. D. Alicke, D. A. Dunning, & J. I. Krueger (Eds.), The self in social judgment (Vol. 1, pp. 85-106). New York: Psychology Press.
  • Allport, F. H. (1937). Toward a science of public opinion. Public Opinion Quarterly, 1(1), 7-23. [https://doi.org/10.1086/265034]
  • Ancu, M., & Cozma, R. (2009). MySpace politics: Uses and gratifications of befriending candidates. Journal of Broadcasting & Electronic Media, 53(4), 567-583. [https://doi.org/10.1080/08838150903333064]
  • Anstead, N., & O’Loughlin, B. (2015). Social media analysis and public opinion: The 2010 UK general election. Journal of Computer-Mediated Communication,, 20(2), 204-220. [https://doi.org/10.1111/jcc4.12102]
  • Bakshy, E., Messing, S., & Adamic, L. A. (2015). Exposure to ideologically diverse news and opinion on Facebook. Science, 348(6239), 1130-1132. [https://doi.org/10.1126/science.aaa1160]
  • Bakshy, E., Rosenn, I., Marlow, C., & Adamic, L. (2012). The role of social networks in information diffusion. Paper presented at the 21st international conference on World Wide Web. [https://doi.org/10.1145/2187836.2187907]
  • Baldwin, M. W., & Holmes, J. G. (1987). Salient private audiences and awareness of the self. Journal of Personality and Social Psychology, 52(6), 1087. [https://doi.org/10.1037/0022-3514.52.6.1087]
  • Barasch, A., & Berger, J. (2014). Broadcasting and narrowcasting: How audience size affects what people share. Journal of Marketing Research, 51(3), 286-299. [https://doi.org/10.1509/jmr.13.0238]
  • Barnidge, M., & Rojas, H. (2014). Hostile media perceptions, presumed media influence, and political talk: Expanding the corrective action hypothesis. International Journal of Public Opinion Research, 26(2), 135-156. [https://doi.org/10.1093/ijpor/edt032]
  • Baugut, P., & Neumann, K. (2019). How right-wing extremists use and perceive news media. Journalism & Mass Communication Quarterly, 96(3), 696-720. [https://doi.org/10.1177/1077699018803080]
  • Baumeister, R. F., & Hutton, D. G. (1987). Self-presentation theory: Self-construction and audience pleasing. In B. Mullen & G. R. Goethals (Eds.), Theories of group behavior (pp. 71-87). New York: Springer. [https://doi.org/10.1007/978-1-4612-4634-3_4]
  • Baym, N. K., & boyd, D. (2012). Socially mediated publicness: An introduction. Journal of Broadcasting & Electronic Media, 56(3), 320-329. [https://doi.org/10.1080/08838151.2012.705200]
  • Berger, J. (2014). Word of mouth and interpersonal communication: A review and directions for future research. Journal of Consumer Psychology, 24(4), 586-607. [https://doi.org/10.1016/j.jcps.2014.05.002]
  • Berger, J., & Iyengar, R. (2013). Communication channels and word of mouth: How the medium shapes the message. Journal of Consumer Research, 40(3), 567-579. [https://doi.org/10.1086/671345]
  • Berger, J., & Milkman, K. L. (2012). What makes online content viral?? Journal of Marketing Research, 49(2), 192-205. [https://doi.org/10.1509/jmr.10.0353]
  • Berger, J., & Schwartz, E. M. (2011). What drives immediate and ongoing word of mouth? Journal of Marketing Research, 48(5), 869-880. [https://doi.org/10.1509/jmkr.48.5.869]
  • Bernstein, M. S., Bakshy, E., Burke, M., & Karrer, B. (2013). Quantifying the invisible audience in social networks. Paper presented at the SIGCHI conference on human factors in computing systems. [https://doi.org/10.1145/2470654.2470658]
  • Bisgin, H., Agarwal, N., & Xu, X. (2010). Investigating homophily in online social networks. Paper presented at the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology. [https://doi.org/10.1109/WI-IAT.2010.61]
  • Blumer, H. (1948). Public opinion and public opinion polling. American Sociological Review, 13(5), 542-549. [https://doi.org/10.2307/2087146]
  • boyd, D. (2010a). Big data: Opportunities for computational and social sciences. Retrieved from http://www.zephoria.org/thoughts/archives/2010/04/17/big-data-opportunities-for-computational-and-social-sciences.html
  • boyd, D. (2010b). Social network sites as networked publics: Affordances, dynamics, and implications. In Z. Papacharissi (Ed.), Networked self: Identity, community, and culture on social network sites (Vol. 39). New York, NY: Routledge.
  • boyd, D., Golder, S., & Lotan, G. (2010). Tweet, tweet, retweet: Conversational aspects of retweeting on twitter. Paper presented at the 2010 43rd Hawaii international conference on system sciences. [https://doi.org/10.1109/HICSS.2010.412]
  • boyd, D., & Ellison, N. B. (2007). Social network sites: Definition, history, and scholarship. Journal of Computer-Mediated Communication, 13, 210-230. [https://doi.org/10.1111/j.1083-6101.2007.00393.x]
  • Brake, D. R. (2012). Who do they think they’re talking to? Framings of the audience by social media users. International Journal of Communication, 6, 1056-1076.
  • Brown, J. J., & Reingen, P. H. (1987). Social ties and word-of-mouth referral behavior. Journal of Consumer Research, 14(3), 350-362. [https://doi.org/10.1086/209118]
  • Campo, S., Askelson, N. M., Spies, E. L., Boxer, C., Scharp, K. M., & Losch, M. E. (2013). “Wow, That Was Funny”: The value of exposure and humor in fostering campaign message sharing. Social Marketing Quarterly, 19(2), 84-96. [https://doi.org/10.1177/1524500413483456]
  • Cappella, J. N. (2017). Vectors into the future of mass and interpersonal communication research: Big data, social media, and computational social science. Human Communication Research, 43(4), 545-558. [https://doi.org/10.1111/hcre.12114]
  • Chen, Z., & Berger, J. (2013). When, why, and how controversy causes conversation. Journal of Consumer Research, 40(3), 580-593. [https://doi.org/10.1086/671465]
  • Chiou, W.-B., & Lee, C.-C. (2013). Enactment of one-to-many communication may induce self-focused attention that leads to diminished perspective taking: The case of Facebook. Judgment & Decision Making, 8(3), 372–380.
  • Choi, B., & Lee, I. (2017). Trust in open versus closed social media: The relative influence of user- and marketer-generated content in social network services on customer trust. Telematics and Informatics, 34(5), 550-559. [https://doi.org/10.1016/j.tele.2016.11.005]
  • Chu, S.-C., & Kim, Y. (2011). Determinants of consumer engagement in electronic word-of-mouth (eWOM) in social networking sites. International journal of Advertising, 30(1), 47-75. [https://doi.org/10.2501/IJA-30-1-047-075]
  • Clemente, M., & Roulet, T. J. (2015). Public opinion as a source of deinstitutionalization: A “spiral of silence” approach. Academy of Management Review, 40(1), 96-114. [https://doi.org/10.5465/amr.2013.0279]
  • Cook, E. C., & Teasley, S. D. (2011). Beyond promotion and protection: Creators, audiences and common ground in user-generated media. Paper presented at the 2011 iConference. [https://doi.org/10.1145/1940761.1940767]
  • Correa, T., & Jeong, S. H. (2011). Race and online content creation: Why minorities are actively participating in the Web. Information, Communication & Society, 14(5), 638-659. [https://doi.org/10.1080/1369118X.2010.514355]
  • Davis, J. L., & Jurgenson, N. (2014). Context collapse: Theorizing context collusions and collisions. Information, Communication & Society, 17, 476–485. [https://doi.org/10.1080/1369118X.2014.888458]
  • Dellande, S., Gilly, M. C., & Graham, J. L. (2004). Gaining compliance and losing weight: The role of the service provider in health care services. Journal of Marketing, 68(3), 78-91. [https://doi.org/10.1509/jmkg.68.3.78.34764]
  • Deng, S., Lin, Y., Liu, Y., Chen, X., & Li, H. (2017). How do personality traits shape information-sharing behaviour in social media? Exploring the mediating effect of generalized trust. Information Research: An International Electronic Journal, 22(3), n3.
  • DeVito, M. A., Birnholtz, J., & Hancock, J. T. (2017, February). Platforms, people, and perception: Using affordances to understand self-presentation on social media. Proceedings of the 2017 ACM conference on computer supported cooperative work and social computing (pp. 740-754). [https://doi.org/10.1145/2998181.2998192]
  • DeVito, M. A., Walker, A. M., & Birnholtz, J. (2018). ‘Too Gay for Facebook’ Presenting LGBTQ+ identity throughout the personal social media ecosystem. Proceedings of the ACM on Human-Computer Interaction, 2(CSCW), 1-23. [https://doi.org/10.1145/3274313]
  • Dunbar, R. I. (1993). Coevolution of neocortical size, group size and language in humans. Behavioral and brain sciences, 16(4), 681-694. [https://doi.org/10.1017/S0140525X00032325]
  • Ellison, N., Lampe, C., & Steinfield, C. (2008). Changes in participation and perception of Facebook. CSCW2008, 721-730.
  • Eveland, W. P., & Hively, M. H. (2009). Political discussion frequency, network size, and “heterogeneity” of discussion as predictors of political knowledge and participation. Journal of Communication, 59(2), 205-224. [https://doi.org/10.1111/j.1460-2466.2009.01412.x]
  • Federico, C. M., & Hunt, C. V. (2013). Political information, political involvement, and reliance on ideology in political evaluation. Political Behavior, 35(1), 89-112. [https://doi.org/10.1007/s11109-011-9184-7]
  • Ferrucci, P., Hopp, T., & Vargo, C. J. (2020). Civic engagement, social capital, and ideological extremity: Exploring online political engagement and political expression on Facebook. New Media & Society, 22(6), 1095-1115. [https://doi.org/10.1177/1461444819873110]
  • Gayo-Avello, D. (2013). A meta-analysis of state-of-the-art electoral prediction from Twitter data. Social Science Computer Review, 31(6), 649-679. [https://doi.org/10.1177/0894439313493979]
  • Gil de Zúñiga, H., Jung, N., & Valenzuela, S. (2012). Social media use for news and individuals’ social capital, civic engagement and political participation. Journal of Computer-Mediated Communication, 17(3), 319-336. [https://doi.org/10.1111/j.1083-6101.2012.01574.x]
  • Gil de Zúñiga, H., Molyneux, L., & Zheng, P. (2014). Social media, political expression, and political participation: Panel analysis of lagged and concurrent relationships. Journal of Communication, 64(4), 612-634. [https://doi.org/10.1111/jcom.12103]
  • Granovetter, M. (1973). The strength of weak ties. American Journal of Sociology, 78(6), 1360-1380. [https://doi.org/10.1086/225469]
  • Grinberg, N., Joseph, K., Friedland, L., Swire-Thompson, B., & Lazer, D. (2019). Fake news on Twitter during the 2016 US presidential election. Science, 363(6425), 374-378. [https://doi.org/10.1126/science.aau2706]
  • Gudykunst, W. B., & Shapiro, R. B. (1996). Communication in everyday interpersonal and intergroup encounters. International journal of intercultural relations, 20(1), 19-45. [https://doi.org/10.1016/0147-1767(96)00037-5]
  • Guess, A., Nagler, J., & Tucker, J. (2019). Less than you think: Prevalence and predictors of fake news dissemination on Facebook. Science advances, 5(1), eaau4586. [https://doi.org/10.1126/sciadv.aau4586]
  • Hampton, K. N., Goulet, L. S., Marlow, C., & Rainie, L. (2012). Why most Facebook users get more than they give. Retrieved from https://www.pewresearch.org/internet/2012/02/03/why-most-facebook-users-get-more-than-they-give, /
  • Hanna, A., Wells, C., Maurer, P., Friedland, L., Shah, D., & Matthes, J. (2013). Partisan alignments and political polarization online: A computational approach to understanding the French and US presidential elections. Paper presented at the 2nd Workshop on Politics, Elections and Data. [https://doi.org/10.1145/2508436.2508438]
  • Harcup, T., & O’Neill, D. (2017). What is News?: News values revisited (again). Journalism Studies, 18(12), 1470-1488. [https://doi.org/10.1080/1461670X.2016.1150193]
  • Hopp, T., Ferrucci, P., & Vargo, C. J. (2020). Why do people share ideologically extreme, false, and misleading content on social media? A self-report and trace data–based analysis of countermedia content dissemination on Facebook and Twitter. Human Communication Research, 46(4), 357-384. [https://doi.org/10.1093/hcr/hqz022]
  • Ihm, J., & Kim, E.-m. (2018). The hidden side of news diffusion: Understanding online news sharing as an interpersonal behavior. New Media & Society, 20(11), 4346-4365. [https://doi.org/10.1177/1461444818772847]
  • James, W. (1890). The principles of psychology. New York: Holt. [https://doi.org/10.1037/10538-000]
  • Katz, C., & Baldassare, M. (1992). Using the “L-word” in public: A test of the spiral of silence in conservative Orange County, California. The Public Opinion Quarterly, 56(2), 232-235. [https://doi.org/10.1086/269313]
  • Kim, C., & Lee, J. K. (2016). Social media type matters: Investigating the relationship between motivation and online social network heterogeneity. Journal of Broadcasting and Electronic Media, 60(4), 676-693. [https://doi.org/10.1080/08838151.2016.1234481]
  • Kim, E.-m., & Ihm, J. (2020). More than virality: Online sharing of controversial news with activated audience. Journalism & Mass Communication Quarterly, 97(1), 118-140. [https://doi.org/10.1177/1077699019836950]
  • Kim, E.-m., Ihm, J., & Park, H. (2017). News sharing as relational communication: Focusing on self-presentation tendency and characteristics of sharing audiences. Korean Journal of Broadcasting and Telecommunication Studies, 31(3), 114-151.
  • Kim, E.-m., Rhee, J. W., & Jang, H. M. (2011). The effects of blog motivations and the perception toward the size of audience on blogging and the intention to continue blogging focusing on bloggers as interactive media users. Korean Journal of Broadcasting and Telecommunication Studies, 25(6), 162-203.
  • Kim, J., & Kim, E. J.(2008). Theorizing dialogic deliberation: Everyday political talk as communicative action and dialogue. Communication Theory, 18, 51-70. [https://doi.org/10.1111/j.1468-2885.2007.00313.x]
  • Kwon, H. (2018). A study on the effect of the perceived climate of opinion and the willingness to express an opinion on the political participation. Journal of Communication Science, 17(3), 5-36. [https://doi.org/10.14696/jcs.2017.09.17.3.5]
  • Lampe, C., Ellison, N., & Steinfield, C. (2006). A face(book) in the crowd: Social Searching vs. social browsing. Paper presented at the ACM conference on Computer Supported Cooperative Work. [https://doi.org/10.1145/1180875.1180901]
  • Lane, D. S., Lee, S. S., Liang, F., Kim, D. H., Shen, L., Weeks, B. E., & Kwak, N. (2019). Social media expression and the political self. Journal of Communication, 69(1), 49-72. [https://doi.org/10.1093/joc/jqy064]
  • Laumann, E. O., & Guttman, L. (1966). The relative associational contiguity of occupations in an urban setting. American Sociological Review, 169-178. [https://doi.org/10.2307/2090902]
  • Lee, C. S., & Ma, L. (2012). News sharing in social media: The effect of gratifications and prior experience. Computers in Human Behavior, 28(2), 331-339. [https://doi.org/10.1016/j.chb.2011.10.002]
  • Lee, J. K. (2011). A study on resistant (alternative) political participation on-line and off-line: With a focus on the influences of media usage, media credibility, political trust, and political efficacy on the experiences and intentions of resistant (alternative) political participation. Media, Gender & Culture, 18, 73-109.
  • Lee, J. K., & Choi, Y. (2015). Why people use social media?: A comparison of open and closed SNSs. Korean Journal of Journalism & Communication Studies, 59(1), 115-148.
  • Lee, J. K., & Kim, E. (2017). Incidental exposure to news: Predictors in the social media setting and effects on information gain online. Computers in Human Behavior, 75, 1008-1015. [https://doi.org/10.1016/j.chb.2017.02.018]
  • Lee. W. T., Cha. M. Y., & Yang, H. R. (2011). Network properties of social media influentials: Focusing on the Korean twitter community. Journal of Communication Research, 48(2), 44-79. [https://doi.org/10.22174/jcr.2011.48.2.44]
  • Levy, R. e. (2021). Social media, news consumption, and polarization: Evidence from a field experiment. American Economic Review, 111(3), 831-870. [https://doi.org/10.2139/ssrn.3653388]
  • Lin, K.-Y., & Lu, H.-P. (2011). Why people use social networking sites: An empirical study integrating network externalities and motivation theory. Computers in Human Behavior, 27(3), 1152-1161. [https://doi.org/10.1016/j.chb.2010.12.009]
  • Litt, E. (2012). Knock, knock. Who’s there? The imagined audience. Journal of Broadcasting & Electronic Media, 56(3), 330-345. [https://doi.org/10.1080/08838151.2012.705195]
  • Litt, E., & Hargittai, E. (2016). The imagined audience on social network sites. Social Media+ Society, 2(1), 2056305116633482. [https://doi.org/10.1177/2056305116633482]
  • Liu, J., Rau, P.-L. P., & Wendler, N. (2015). Trust and online information-sharing in close relationships: A cross-cultural perspective. Behaviour & Information Technology, 34(4), 363-374. [https://doi.org/10.1080/0144929X.2014.937458]
  • Livingstone, S. (2008). Taking risky opportunities in youthful content creation: Teenagers’ use of social networking sites for intimacy, privacy and self-expression. New Media & Society, 10(3), 393-411. [https://doi.org/10.1177/1461444808089415]
  • Ma, L., Lee, C. S., & Goh, D. H.-L. (2014). Understanding news sharing in social media: An explanation from the diffusion of innovations theory. Online Information Review, 38(5), 598-615. [https://doi.org/10.1108/OIR-10-2013-0239]
  • Malthouse, E. C., & Peck, A. (2011). An introduction. In E. C. Malthouse & A. Peck (Eds.), Medill on media engagement. Cresskill, NJ: Hampton Press.
  • Marwick, A. E., & boyd, D. (2011). I tweet honestly, I tweet passionately: Twitter users, context collapse, and the imagined audience. New Media & Society, 13(1), 114-133. [https://doi.org/10.1177/1461444810365313]
  • Matsa, K. E., & Mitchell, A. (2014). 8 key takeaways about social media and news. Pew Research Center. Retrieved from https://www.journalism.org/2014/03/26/8-key-takeaways-about-social-media-and-news, /
  • Mccord, M., & Chuah, M. (2011). Spam detection on twitter using traditional classifiers. Paper presented at the international conference on Autonomic and trusted computing. [https://doi.org/10.1007/978-3-642-23496-5_13]
  • McGregor, S. C. (2019). Social media as public opinion: How journalists use social media to represent public opinion. Journalism, 20(8), 1070-1086. [https://doi.org/10.1177/1464884919845458]
  • McLeod, J. M., Scheufele, D. A., & Moy, P. (1999). Community, communication, and participation: The role of mass media and interpersonal discussion in local political participation. Political Communication, 16(3), 315-336. [https://doi.org/10.1080/105846099198659]
  • McPherson, M., Smith-Lovin, L., & Cook, J. M. (2001). Birds of a feather: Homophily in social networks. Annual Review of Sociology, 27(1), 415-444. [https://doi.org/10.1146/annurev.soc.27.1.415]
  • Möller, J., van de Velde, R. N., Merten, L., & Puschmann, C. (2019). Explaining online news engagement based on browsing behavior: Creatures of habit? Social Science Computer Review, 38(5), 616-632. [https://doi.org/10.1177/0894439319828012]
  • Moy, P., Domke, D., & Stamm, K. (2001). The spiral of silence and public opinion on affirmative action. Journalism & Mass Communication Quarterly, 78(1), 7-25. [https://doi.org/10.1177/107769900107800102]
  • Neubaum, G., & Krämer, N. C. (2017). Opinion climates in social media: Blending mass and interpersonal communication. Human Communication Research, 43(4), 464-476. [https://doi.org/10.1111/hcre.12118]
  • Neuwirth, K., Frederick, E., & Mayo, C. (2007). The spiral of silence and fear of isolation. Journal of Communication, 57(3), 450-468. [https://doi.org/10.1111/j.1460-2466.2007.00352.x]
  • Newman, N., Fletcher, R., Schulz, A., Andi, S., Robertson, C. T., & Nielsen, R. K. (2021). Digital news report 2021. Retrieved from United Kingdom: https://reutersinstitute.politics.ox.ac.uk/digital-news-report/2021
  • Noelle-Neumann, E. (1974). Spiral of silence: A theory of public opinion. Journal of Communication, 24, 43-51. [https://doi.org/10.1111/j.1460-2466.1974.tb00367.x]
  • O’Sullivan, P. B., & Carr, C. T. (2018). Masspersonal communication: A model bridging the mass-interpersonal divide. New Media & Society, 20(3), 1161-1180. [https://doi.org/10.1177/1461444816686104]
  • Oh, J., & Sundar, S. S. (2016). User engagement with interactive media: A communication perspective. In Why Engagement Matters (pp. 177-198): Springer. [https://doi.org/10.1007/978-3-319-27446-1_8]
  • Ong, W. J. (1975). The writer’s audience is always a fiction. Publications of the Modern Language Association of America, 90(1), 9-21. [https://doi.org/10.2307/461344]
  • Palazon, M., Sicilia, M., & Lopez, M. (2015). The influence of “Facebook friends” on the intention to join brand pages. Journal of Product & Brand Management, 24(6), 580-595. [https://doi.org/10.1108/JPBM-08-2014-0696]
  • Papacharissi, Z. (2002). The virtual sphere: The internet as a public sphere. New Media & Society, 4(1), 9-27. [https://doi.org/10.1177/14614440222226244]
  • Papacharissi, Z. (2011). A networked self. In A networked self: Identity, community, and culture on social network sites, (pp. 304-318). [https://doi.org/10.4324/9780203876527]
  • Park, C. S., & Zúñiga, H. G. D. (2019). The impact of mobile communication uses on civic engagement: Moderating effects of exposure to politically diverse and weak-tie networks. International Journal of Mobile Communications, 17(3), 298-325. [https://doi.org/10.1504/IJMC.2019.098608]
  • Park, S. H. (2012). SNS news communication: Multiplicity and orality. Journal of Communication Research, 49(2), 37-73. [https://doi.org/10.22174/jcr.2012.49.2.37]
  • Parks, M. (2007). Personal networks and personal relationships. Mahwah, NJ.
  • Pempek, T. A., Yermolayeva, Y. A., & Calvert, S. L. (2009). College students’ social networking experiences on Facebook. Journal of Applied Developmental Psychology, 30(3), 227-238. [https://doi.org/10.1016/j.appdev.2008.12.010]
  • Petrocelli, J. V., Tormala, Z. L., & Rucker, D. D. (2007). Unpacking attitude certainty: Attitude clarity and attitude correctness. Journal of Personality and Social Psychology, 92(1), 30. [https://doi.org/10.1037/0022-3514.92.1.30]
  • Rainie, L., & Smith, A. (2012). Social networking sites and politics. Retrieved from https://www.pewresearch.org/internet/2012/03/12/social-networking-sites-and-politics, /
  • Rogers, E. M., & Bhowmik, D. K. (1970). Homophily-heterophily: Relational concepts for communication research. Public Opinion Quarterly, 34(4), 523-538. [https://doi.org/10.1086/267838]
  • Rojas, H. (2010). “Corrective” actions in the public sphere: How perceptions of media and media effects shape political behaviors. International Journal of Public Opinion Research, 22(3), 343-363. [https://doi.org/10.1093/ijpor/edq018]
  • Rojas, H., Barnidge, M., & Abril, E. P. (2016). Egocentric publics and corrective action. Communication and the Public, 1(1), 27-38. [https://doi.org/10.1177/2057047315619421]
  • Ruths, D., & Pfeffer, J. (2014). Social media for large studies of behavior. Science, 346(6213), 1063-1064. [https://doi.org/10.1126/science.346.6213.1063]
  • Salmon, C. T., & Kline, F. G. (1983). The spiral of silence ten years later: An examination and evaluation. Paper presented at the annual meeting of the International Communication Association, Dallas, TX.
  • Schäfer, S., Sülflow, M., & Müller, P. (2017). The special taste of snack news: An application of niche theory to understand the appeal of Facebook as a news source. First Monday. [https://doi.org/10.5210/fm.v22i4.7431]
  • Schlenker, B. R., Britt, T. W., & Pennington, J. (1996). Impression regulation and management: Highlights of a theory of self-identification. In Handbook of motivation and cognition, Vol. 3: The interpersonal context. (pp. 118-147). New York: The Guilford Press.
  • Shin, J., & Thorson, K. (2017). Partisan selective sharing: The biased diffusion of fact-checking messages on social media. Journal of Communication, 67(2), 233-255. [https://doi.org/10.1111/jcom.12284]
  • Simons, H. W., Berkowitz, N. N., & Moyer, R. J. (1970). Similarity, credibility, and attitude change: A review and a theory. Psychological Bulletin, 73(1), 1. [https://doi.org/10.1037/h0028429]
  • Smith, K. (2019). 126 amazing social media statistics and facts. Retrieved from https://www.brandwatch.com/blog/amazing-social-media-statistics-and-facts, /
  • Steffes, E. M., & Burgee, L. E. (2009). Social ties and online word of mouth. Internet Research, 19(1), 42-59. [https://doi.org/10.1108/10662240910927812]
  • Stutzman, F., & Hartzog, W. (2012, February). Boundary regulation in social media. Proceedings of the ACM 2012 conference on computer supported cooperative work (pp. 769-778).
  • Sundar, S. S., & Limperos, A. M. (2013). Uses and grats 2.0: New gratifications for new media. Journal of Broadcasting & Electronic Media, 57(4), 504-525. [https://doi.org/10.1080/08838151.2013.845827]
  • Thorson, E. (2014). Beyond opinion leaders: How attempts to persuade foster political awareness and campaign learning. Communication Research, 41(3), 353-374. [https://doi.org/10.1177/0093650212443824]
  • Tormala, Z. L., & Rucker, D. D. (2007). Attitude certainty: A review of past findings and emerging perspectives. Social and Personality Psychology Compass, 1(1), 469-492. [https://doi.org/10.1111/j.1751-9004.2007.00025.x]
  • Ulbig, S. G., & Funk, C. L. (1999). Conflict avoidance and political participation. Political Behavior, 21(3), 265-282. [https://doi.org/10.1023/A:1022087617514]
  • Valenzuela, S. (2013). Unpacking the use of social media for protest behavior: The roles of information, opinion expression, and activism. American Behavioral Scientist, 57(7), 920-942. [https://doi.org/10.1177/0002764213479375]
  • Valeriani, A., & Vaccari, C. (2016). Accidental exposure to politics on social media as online participation equalizer in Germany, Italy, and the United Kingdom. New Media & Society, 18(9), 1857-1874. [https://doi.org/10.1177/1461444815616223]
  • Vitak, J. (2012). The impact of context collapse and privacy on social network site disclosures. Journal of Broadcasting & Electronic Media, 56, 451–470. [https://doi.org/10.1080/08838151.2012.732140]
  • Vosoughi, S., Roy, D., & Aral, S. (2018). The spread of true and false news online. Science, 359(6380), 1146-1151. [https://doi.org/10.1126/science.aap9559]
  • Walther, J. B. (1996). Computer-mediated communication: Impersonal, interpersonal, and hyperpersonal interaction. Communication Research, 23, 3–43. [https://doi.org/10.1177/009365096023001001]
  • Walther, J. B. (2017). The merger of mass and interpersonal communication via new media: Integrating metaconstructs. Human Communication Research, 43(4), 559-572. [https://doi.org/10.1111/hcre.12122]
  • Walther, J. B., Heide, B. V. D., Kim, S.-Y., Westerman, D., & Tong, S. T. (2008). The role of friends’ behavior on evaluations of individuals’ Facebook profiles: Are we known by the company we keep? Human Communication Research, 34, 28-49. [https://doi.org/10.1111/j.1468-2958.2007.00312.x]
  • Waterloo, S. F., Baumgartner, S. E., Peter, J., & Valkenburg, P. M. (2018). Norms of online expressions of emotion: Comparing Facebook, Twitter, Instagram, and WhatsApp. New Media & Society, 20, 1813-1831. [https://doi.org/10.1177/1461444817707349]
  • Wells, C., & Thorson, K. (2017). Combining big data and survey techniques to model effects of political content flows in Facebook. Social Science Computer Review, 35, 33–52. [https://doi.org/10.1177/0894439315609528]
  • Wojcieszak, M. E., & Mutz, D. C. (2009). Online groups and political discourse: Do online discussion spaces facilitate exposure to political disagreement? Journal of Communication, 59(1), 40-56. [https://doi.org/10.1111/j.1460-2466.2008.01403.x]
  • Xu, C., Li, J., Abdelzaher, T., Ji, H., Szymanski, B. K., & Dellaverson, J. (2020). The paradox of information access: On modeling social-media-induced polarization. arXiv preprint arXiv:2004.01106.
  • Yarchi, M., Baden, C., & Kligler-Vilenchik, N. (2020). Political polarization on the digital sphere: A cross-platform, over-time analysis of interactional, positional, and affective polarization on social media. Political Communication, 38, 1-42. [https://doi.org/10.1080/10584609.2020.1785067]
  • Yoo, S. W., Kim, J. W., & Gil de Zúñiga, H. (2017). Cognitive benefits for senders: Antecedents and effects of political expression on social media. Journalism & Mass Communication Quarterly, 94(1), 17-37. [https://doi.org/10.1177/1077699016654438]
  • Yun, G. W., Park, S.-Y., & Lee, S. (2016). Inside the spiral: Hostile media, minority perception, and willingness to speak out on a weblog. Computers in Human Behavior, 62, 236-243. [https://doi.org/10.1016/j.chb.2016.03.086]
  • Zamith, R., & Lewis, S. C. (2014). From public spaces to public sphere: Rethinking systems for reader comments on online news sites. Digital Journalism, 2(4), 558-574. [https://doi.org/10.1080/21670811.2014.882066]
  • Zhang, R., N. Bazarova, N., & Reddy, M. (2021, May). Distress disclosure across social media platforms during the COVID-19 pandemic: Untangling the effects of platforms, affordances, and audiences. Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (pp. 1-15). [https://doi.org/10.1145/3411764.3445134]
  • Zhao, X., Lampe, C., & Ellison, N. B. (2016, May). The social media ecology: User perceptions, strategies and challenges. Proceedings of the 2016 CHI conference on human factors in computing systems (pp. 89-100). [https://doi.org/10.1145/2858036.2858333]

Appendix

부록. 참고문헌

  • 권혁남 (2018). 이슈 특성과 지각된 의견분위기 상황에 따른 침묵의 나선효과. <사회과학연구>, 29권 4호, 61-82.
  • 김은미·이준웅·장현미 (2011). 블로그 동기와 이용자 규모에 대한 인식이 블로그 운영과 지속의사에 미치는 영향: 상호작용적 매체 이용자로서의 블로거 연구. <한국방송학보>, 25권 6호, 162-203.
  • 김은미·임소영·박현아 (2017). 관계적 커뮤니케이션으로서의 뉴스 공유: 자기제시 성향과 뉴스 공유 대상의 특성을 중심으로. <한국방송학보>, 31권 3호, 114-151.
  • 박선희 (2012). SNS 뉴스 소통: 다중성과 구술성. <언론정보연구>, 49권 2호, 33-73.
  • 이원태·차미영·양해륜 (2011). 소셜미디어 유력자의 네트워크 특성-한국의 트위터 공동체를 중심으로. <언론정보연구>, 48권 2호, 44-79.
  • 이정권·최영 (2015). 소셜미디어 이용 동기 연구. <한국언론학보>, 59권 1호, 115-147.
  • 이정기 (2011). 온·오프라인 공간에서의 ‘저항적 (대안적) 정치참여’에 관한 연구: 미디어 이용량, 미디어 신뢰도, 정치신뢰도, 정치효능감이 저항적 (대안적) 정치참여 경험과 의도에 미치는 영향을 중심으로. <미디어, 젠더 & 문화>, 18호, 73-109.