Journal of Korean Library and Information Science Society (한국도서관정보학회지)

Korean Library and Information Science Society (한국도서관정보학회)
권호 표지
DOI QR코드

DOI QR Code

An Exploratory Factor Analysis on the Collaborative Information Behaviors of an Online Community Responding to the MV Sewol Tragedy

세월호 비극에 대한 온라인 커뮤니티의 협력적 정보행동에 관한 탐색적 요인 분석 연구

  • Jisue Lee (Chonnam National University, Department of Library & Information Science)
  • Received : 2023.02.27
  • Accepted : 2023.03.18
  • Published : 2023.03.30
Download PDF
⟨ Previous Next ⟩

Abstract

This research attempts to identify how members of an online community collaboratively engaged with particular social information behaviors and accomplished a defined collective action. While responding to the Sewol Ferry tragedy, MissyUSA members quickly communicated and mobilized a collective action, a full-page ad campaign in The New York Times. As a follow up study, this secondary analysis quantitatively analyzes the primary data from a previous study to explore potential relationships or underlying factors among the various identified information behaviors. In this study, nineteen of the previously identified information behaviors were analyzed using exploratory factor analysis, yielding a total of eight factors. The two major factors of shared representation/collective identification and mobilizing resources verified the findings of the previous study and are in line with the findings typical of political science. The three factors of collaborative decision-making, reaction to tension, and brainstorming were factors that maximized communication and mobilization online, without any face-to-face communication or physical organization. Three emergent factors of outburst of dissent, boycott, and planning explained how members used negative emotions of anger, referential information for boycott, and incubated next collective actions. Through exploratory factor analysis, this study verifies and expands on the findings of the previous study by identifying several emergent factors that relate to the collaborative information behaviors of an online community engaged in a collective action.

이 연구는 특정 온라인 커뮤니티 회원들이 어떤 사회적 정보행동을 통해 성공적인 집단행동을 이루어 가는지 탐구하고자 하였다. 세월호 비극에 대한 대답으로서, MissyUSA 회원들은 커뮤니티를 통해 빠르게 정보를 공유하고 자원을 동원함으로써, NYT 광고 캠페인을 성공으로 이끌었다. 이전 연구의 후속연구인 이 연구는 이차분석을 통해 이전 연구에서 밝혀진 다양한 정보행동 사이의 관계를 파악하고자 하였다. 탐색적 요인분석을 통해 19개의 정보행동들은 8가지 요인으로 범주화되었다. 집단적 정체성 확인과 자원동원과 같은 2가지 요인은 전통적인 정치학에서 강조하는 요인이자 이전 연구에서 밝혀진 결과와 상통함을 보여준다. 협력적 의사결정, 긴장의 처리, 브레인스토밍 등 3가지 요인은 온라인상에서 집단행동에 나서는 이용자들에게 물리적 조직이나 대면 의사소통 없이도 의사소통과 자원동원을 극대화하는데 중요한 요인으로 나타났다. 분노의 표출, 보이콧, 계획 등 새롭게 보고된 3가지 요인은 커뮤니티 회원들이 분노의 감정을 어떻게 사용하고 참고적 정보를 활용하여 보이콧 행동에 나서는지, 후속 집단행동을 어떻게 계획하고 준비하는지를 보여주었다. 본 연구는 탐색적 요인 분석 기법을 통해 이전 연구 결과를 입증하고 협력적 정보행동과 관련한 새로운 요인들을 발견함으로써 이전 연구 결과를 확장하였다는 점에 의의가 있다.

Keywords

References

  1. Ahern, K. (2002). Developmental coordination disorder: Validation of a qualitative analysis using statistical factor analysis. International Journal of Qualitative Methods, 1(3), 70-82. https://doi.org/10.1177/160940690200100305
  2. Alberici, A. I. & Milesi, P. (2016). Online discussion, politicized identity, and collective action. Group Processes & Intergroup Relations, 19(1), 43-59. https://doi.org/10.1177/1368430215581430
  3. Almeida, P. D. & Lichbach, M. I. (2003). To the internet, from the internet: comparative media coverage of transnational protest. Mobilization, 8(3), 249-272. https://doi.org/10.17813/maiq.8.3.9044l650652801xl
  4. Anduiza, E., Cristancho, C., & Sabucedo, J. M. (2014). Mobilization through online social networks: the political protest of the indignados in Spain. Information, Communication & Society, 17(6), 750-764. https://doi.org/10.1080/1369118X.2013.808360
  5. Beavers, A. S., Lounsbury, J. W., Richards, J. K., Huck, S. W., Skolits, G. J., & Esquivel, S. L. (2013). Practical considerations for using exploratory factor analysis in educational research. Practical Assessment, Research, and Evaluation, 18(6), 1-13. https://doi.org/10.7275/qv2q-rk76
  6. Bouvin, J. & Ng, S. (2003, July). Are more data always better for factor analysis? (National Bureau of Economic Research Working Paper No. 9829). https://doi.org/10.3386/w9829
  7. Burnett, G. (2000). Information exchange in virtual communities: a typology. Information Research, 5(4). http://www.informationr.net/ir/5-4/paper82.html
  8. Cardoso, A., Boudreau, M.-C., & Carvalho, J. A. (2019). Organizing collective action: Does information and communication technology matter? Information and Organization, 29(3), 100256. https://doi.org/10.1016/j.infoandorg.2019.100256
  9. Chae, S. H. (2017, March 22). South Korea raises ferry that sank in 2014 disaster. New York Times. https://www.nytimes.com/2017/03/22/world/asia/south-korea-ferry-sewol.html
  10. Cheng, H. G. & Phillips, M. R. (2014). Secondary analysis of existing data: opportunities and implementation. Shanghai Archives of Psychiatry, 26(6), 371-375.
  11. Child, D. (2006). The Essentials of Factor Analysis (3rd ed.). New York, NY: Continuum International Publishing Group.
  12. Chung, J. Y. & Buhalis, D. (2008). Information needs in online social networks. Information Technology & Tourism, 10, 267-281.
  13. Clarke, S. E. & Cossette, S. (2000). Secondary analysis: Theoretical, methodological, and practical considerations. Canadian Journal of Nursing Research, 32(3), 109-129.
  14. Comrey, A. L. (1973). A First Course in Factor Analysis. New York, NY: Academic Press.
  15. Conrado, S. P., Neville, K., Woodworth, S., & O'Riordan, S. (2016). Managing social media uncertainty to support the decision making process during emergencies. Journal of Decision Systems, 25, 171-181.
  16. Costello, A. B., & Osborne, J. (2005). Best practices in exploratory factor analysis: four recommendations for getting the most from your analysis. Practical Assessment, Research, and Evaluation, 10, Article 7, 1-9.
  17. Counts, S. & Fisher, K. E. (2010). Mobile social networking as information ground: a case study. Library & Information Science Research (07408188), 32(2), 98-115. https://doi.org/10.1016/j.lisr.2009.10.003
  18. Creswell, J. W. & Plano Clark, V. L. (2011). Designing and Conducting Mixed Methods Research (2nd ed.). Thousand Oaks, CA: Sage Publications, Inc.
  19. Denzin, N. K. (1978). The Research Act: A theoretical introduction of sociological methods. New York: McGraw-Hill.
  20. Diani, M. (2000). Social movement networks: Virtual and real. Information, Communication and Society, 3(3), 386-401. https://doi.org/10.1080/13691180051033333
  21. Earl, J., Hurwitz, H. M., Mesinas, A. M., Tolan, M., & Arlotti, A. (2013). This protest will be tweeted. Information, Communication & Society, 16(4), 459-478. https://doi.org/10.1080/1369118X.2013.777756
  22. Ebrahimzadeh, S., Rezaei Sharifabadi, S., Karbala Aghaie Kamran, M., & Dalkir, K. (2020). Triggers and strategies related to the collaborative information-seeking behaviour of researchers in ResearchGate. Online Information Review, 44(5), 1077-1096. https://doi.org/10.1108/OIR-12-2019-0380
  23. Faraj, S., Jarvenpaa, S. L., & Majchrzak, A. (2011). Knowledge collaboration in online communities. Organization Science, 22(5), 1224-1239. https://doi.org/10.1287/orsc.1100.0614
  24. Fisher, K. E., Landry, C. F., & Naumer, C. (2007). Social spaces, casual interactions, meaningful exchanges: 'information ground' characteristics based on the college student experience. Information Research, 12(2), paper 291. http://www.informationr.net/ir/12-2/paper291.html
  25. Gooden, R. J. & Winefield, H. R. (2007). Breast and prostate cancer online discussion boards: A thematic analysis of gender differences and similarities. Journal of Health Psychology, 12(1), 103-114. https://doi.org/10.1177/1359105307071744
  26. Hagen, L., Keller, T., Neely, S., Depaula, N., & Robert-Cooperman, C. (2018). Crisis Communications in the age of social media: a network analysis of Zika-related tweets. Social Science Computer Review, 36(5), 523-541.
  27. Han, J. (2014, May 16). Sewol ad to run in Washington Post. The Korea Times. https://www.koreatimes.co.kr/www/nation/2022/11/113_157358.html
  28. Hara, N. & Hew, K. F. (2007). Knowledge-sharing in an online community of health-care professionals. Information Technology & People, 20(3), 235-261. https://doi.org/10.1108/09593840710822859
  29. Hara, N. & Huang, B. (2011). Online social movements. In B. Cronin (Eds.), Annual Review of Information Science and Technology. Medford, NJ: Information Today, 489-522.
  30. Heaton, J. (2008). Secondary analysis of qualitative data: an overview. Historical Social Research, 33(3), 33-45. https://doi.org/10.12759/hsr.33.2008.3.33-45
  31. Henson, R. K. & Roberts, J. K. (2006). Use of exploratory factor analysis in published research: Common errors and some comment on improved practice. Educational and Psychological Measurement, 66(3), 392-416.
  32. Hollister, J. M. (2019). An ethnographic study on the digital literacy practices of role-players in a massively multiplayer online role-playing game. Journal of the Korean Library and Information Science Society, 50(4), 429-467. https://doi.org/10.16981/kliss.50.4.201912.429
  33. Hollister, J. M. (2020). The information worlds of online role-players. Journal of the Korean Biblia Society for Library and Information Science, 31(2), 223-266. https://doi.org/10.14699/kbiblia.2020.31.2.223
  34. Hotelling, H. (1933). Analysis of a complex if statistical variables into principal components. Journal of Educational Psychology, 24, 417-441. https://doi.org/10.1037/h0071325
  35. IBM Corp. (2021). IBM SPSS Statistics for Windows (Version 28.0) [Computer software]. IBM Corp.
  36. Jenkins, J. C. (1981). Sociopolitical movements. In S. Long (Ed.), The Handbook of Political Behavior (Vol. 4). New York: Plenum Press, 81-153.
  37. Jenkins, J. C. (1983). Resource mobilization theory and the study of social movements. Annual Review of Sociology, 9, 527-553. https://doi.org/10.1146/annurev.so.09.080183.002523
  38. Jick, T. D. (1979). Mixing qualitative and quantitative methods: Triangulation in action. Administrative Science Quarterly, 24(4), Qualitative Methodology, 602-611. https://doi.org/10.2307/2392366
  39. Joyce, E. & Kraut, R. E. (2006). Predicting continued participation in newsgroups. Journal of Computer-Mediated Communication, 11(3), 723-747. https://doi.org/10.1111/j.1083-6101.2006.00033.x
  40. Kaiser, H. F. (1960). The application of electronic computers to factor analysis. Educational and Psychological Measurement, 20, 141-151. https://doi.org/10.1177/001316446002000116
  41. Kee, D., Jun, G. T., Waterson, P., & Haslam, R. (2017). A systemic analysis of South Korea Sewol ferry accident - striking a balance between learning and accountability. Applied Ergonomics, 59(Part B), 504-516.
  42. Kelly, C. & Breinlinger, S. (1996). The social psychology of collective action: Identity, injustice and gender. Taylor & Francis US.
  43. Khazaee-Pool, M., Majlessi, F., Montazeri, A., Pashaei, T., Gholami, A., & Ponnet, K. (2016). Development and psychometric testing of a new instrument to measure factors influencing women's breast cancer prevention behaviors (ASSISTS). BMC Women's Health, 16 (article no. 40). https://doi.org/10.1186/s12905-016-0318-2
  44. Kim, B. J. (2014, May 18). Another Sewol Ferry advertisement criticizing the South Korean government in the Washington Post followed by NYT Advertisement. SBS News. https://news.sbs.co.kr/news/endPage.do?news_id=N1002394311
  45. Kim, D. S. (2017, June 20). Ministry wraps up first part of search for Sewol victims. The Korea Herald. http://www.koreaherald.com/view.php?ud=20170620000824
  46. Kim, S. K. (2015). The Sewol ferry disaster in Korea and maritime safety management. Ocean Development & International Law, 46(4), 345-358. https://doi.org/10.1080/00908320.2015.1089748
  47. Larana, E., Johnston, H., & Gustfield, J. R. (1994). New social movements: from ideology to identity. Philadelphia: Temple University Press.
  48. Leach, C. W., Iyer, A., & Pedersen, A. (2006). Anger and guilt about ingroup advantage explain the willingness for political action. Personality and Social Psychology Bulletin, 32, 1232-1245. https://doi.org/10.1177/0146167206289729
  49. Lee, E. (2013). Formation of a talking space and gender discourses in digital diaspora space: case of a female Korean immigrants online community in the USA. Asian Journal of Communication, 23(5), 472-488. https://doi.org/10.1080/01292986.2013.772216
  50. Lee, F. L. F. & Chan, J. M. (2016). Digital media activities and mode of participation in a protest campaign: a study of the Umbrella Movement. Information, Communication & Society, 19(1), 4-22. https://doi.org/10.1080/1369118X.2015.1093530
  51. Lee, J. & Kang, J. H. (2018). Crying mothers mobilise for a collective action: Collaborative information behavior in an online community, Information Research, 23(2). http://informationr.net/ir/23-2/paper792.html
  52. Lee, J. & Kang, J. H. (2020). A study on the factor analysis of the collaborative information behaviors of users in an online community. In Proceedings of 2020 K-LISS / 3rd I-LISS International Conference, 125-133.
  53. Lee, J. S. (2016, February 5). The happiest journalist in Korea. Hankyoreh. https://www.hani.co.kr/arti/society/media/729559.html
  54. MacCallum, R. C., Widaman, K. F., Zhang, S., & Hong, S. (1999). Sample size in factor analysis. Psychological Methods, 4(1), 84-99. https://doi.org/10.1037/1082-989X.4.1.84
  55. McCarthy, J. D. & Zald, M. N. (1977). Resource mobilization and social movements: a partial theory. The American Journal of Sociology, 82(6), 1212-1241. https://doi.org/10.1086/226464
  56. Montesi, M. (2021). Human information behavior during the Covid-19 health crisis. A literature review. Library & Information Science Research, 43(4), 101122. https://doi.org/10.1016/j.lisr.2021.101122
  57. Mvududu, N. H. & Sink, C. A. (2013). Factor analysis in counseling research and practice. Counseling Outcome Research & Evaluation, 4, 75-98. https://doi.org/10.1177/2150137813494766
  58. Narayan, B., Talip, B. A., Watson, J., & Edwards, S. (2013). Social media as online information grounds: a preliminary conceptual framework. In: Urs, S.R., Na, JC., Buchanan, G. (eds) Digital Libraries: Social Media and Community Networks. ICADL 2013. Lecture Notes in Computer Science, vol 8279. Springer. https://doi.org/10.1007/978-3-319-03599-4_15
  59. Olson, M. (1965). The Logic of Collective Action: Public goods and the theory of groups. Cambridge, MA: Harvard University Press.
  60. Pang, N. & Goh, D. P. C. (2016). Are we all here for the same purpose? Social media and individualized collective action. Online Information Review, 40(4), 544-559. https://doi.org/10.1108/OIR-10-2015-0337
  61. Paul, S. A. & Morris, M. R. (2011). Sensemaking in collaborative web search. Human - Computer Interaction, 26(1-2), 72-122.
  62. Pearson, K. (1901). On lines and planes of closest fit to systems of points in space. Philosophical Magazine, 2, 559-572. https://doi.org/10.1080/14786440109462720
  63. Peters, M. A. (2012). Anger and political culture: a time for outrage! Policy Futures in Education, 10(5), 563-568. https://doi.org/10.2304/pfie.2012.10.5.563
  64. Postmes, T. & Brunsting, S. (2002). Collective action in the age of the Internet: mass communication and online mobilization. Social Science Computer Review, 20(3), 290-301. https://doi.org/10.1177/089443930202000306
  65. Prabhat, S., Motwani, A., & Rangaswamy, N. (2019). Longitudinal analysis of a# boycott movement on Indian online platforms: Case of collective action and online boycott. In Proceedings of 17th European Conference on Computer-Supported Cooperative Work. European Society for Socially Embedded Technologies (EUSSET).
  66. Qu, Y. & Hansen, D. L. (2008, April). Building shared understanding in collaborative sensemaking. In Proceedings of CHI 2008 Sensemaking Workshop. ACM.
  67. Ranjit, Y. S., Lachlan, K. A., Basaran, A.-M. B., Snyder, L. B., & Houston, J. B. (2020). Needing to know about the crisis back home: Disaster information seeking and disaster media effects following the 2015 Nepal earthquake among Nepalis living outside of Nepal. International Journal of Disaster Risk Reduction, 50, 101725. https://doi.org/10.1016/j.ijdrr.2020.101725
  68. Reio, T. G., Jr. & Shuck, B. (2015). Exploratory factor analysis: Implications for theory, research, and practice. Advances in Developing Human Resources, 17(1), 12-25. https://doi.org/10.1177/1523422314559804
  69. Shklovski, I., Palen, L., & Sutton, J. (2008, November). Finding community through information and communication technology in disaster response. In Proceedings of the 2008 ACM conference on Computer supported cooperative work. ACM, 127-136
  70. Skinner, J. (2011). Social media and revolution: The Arab Spring and the Occupy Movement as seen through three information studies paradigms. Sprouts: Working Papers on Information Systems, 11(169). http://sprouts.aisnet.org/11-169
  71. Starbird, K. (2011, May). Digital volunteerism during disaster: Crowdsourcing information processing. In Conference on human factors in computing systems. ACM, 7-12
  72. Stevens, J. (1996). Applied Multivariate Statistics for the Social Sciences (3rd ed.). Mahwah, NJ: Lawrence Erlbaum.
  73. Sturmer, S. & Simon, B. (2009). Pathways to collective protest: Calculation, identification, or emotion? A critical analysis of the role of group=based anger in social movement participation. Journal of Social Issues, 65(4), 681-705. https://doi.org/10.1111/j.1540-4560.2009.01620.x
  74. Suhr, D. (2006). Exploratory or confirmatory factor analysis? Proceedings of the 31st Annual SAS Users Group International Conference (Paper no. 200-31). Cary, NC: SAS Institute Inc.
  75. Tabachnick, B. G. & Fidell, L. S. (2007). Using Multivariate Statistics (5th ed.). Boston, MA: Allyn & Bacon.
  76. Theocharis, Y., Lowe, W., Van Deth, J. W., & Garcia-Albacete, G. (2015). Using Twitter to mobilize protest action: Online mobilization patterns and action repertoires in the Occupy Wall Street, Indignados, and Aganaktismenoi movements. Information, Communication & Society, 18(2), 202-220. https://doi.org/10.1080/1369118X.2014.948035
  77. Thomas, E. F. & McGarty, C. (2009). The role of efficacy and moral outrage norms in creating the potential for international development activism through group-based interaction. British Journal of Social Psychology, 48, 115-134.
  78. Thorson, K., Driscoll, K., Ekdale, B., Degerly, S., Thompson, L. G., Schrock, A., Swartz, L., Vraga, E. K., & Wells, C. (2013). YouTube, Twitter and the Occupy Movement: connecting content and circulation practices. Information, Communication & Society, 16(3), 421-451. https://doi.org/10.1080/1369118X.2012.756051
  79. Tilly, C. (1978). From Mobilization to Revolution. London: Addison-Wesley.
  80. Watson, B., Clarke, C., Swallow, V., & Forster, S. (2005). Exploratory factor analysis of the research and development culture index among qualified nurses. Journal of Clinical Nursing, 14(9), 1042-1047. https://doi.org/10.1111/j.1365-2702.2005.01214.x
  81. Yong, A. G. & Pearce, S. (2013). A beginner's guide to factor analysis: focusing on exploratory factor analysis. Tutorials in Quantitative Methods for Psychology, 9(2), 79-94. https://doi.org/10.20982/tqmp.09.2.p079
  82. Yun, H. (2006). The creation and validation of a perceived anonymity scale based on the social information processing model and its nomological network test in an online social support community. Unpublished doctoral dissertation, Michigan State University, East Lansing, MI, USA.