線上災難傳播的議題設定效果：高雄氣爆事件中媒體臉書粉絲專頁主文與回應文的互動影響

Agenda-Setting Effect of Online Disaster Communication: Interactions through Facebook Posts and Comments during the Kaohsiung Gas Explosions

10.30386/MCR.201901_(138).0005

譚躍(Yue Tan)；蕭蘋(Ping Shaw)

社群媒體 ； 電腦內容分析 ； 議題設定 ； 災難報導 ； 高雄氣爆 ； 情感動員 ； social media ； computerized content analysis ； agenda-setting effect ； disaster report ； Kaohsiung gas explosions ； emotional mobilization

新聞學研究

138期（2019 / 01 / 01）

163 - 224

繁體中文

本研究探討在高雄氣爆發生後的兩個月期間，臺灣新聞媒體的臉書粉絲專頁上，媒體和網友的互動過程和內容。本研究以議題設定理論為基礎，使用電腦內容分析方法，針對臺灣的三大報紙《蘋果日報》、《聯合報》、《自由時報》、與四個新興網路新聞媒體《新頭殼》、《天下獨立評論》、《關鍵新聞》、《風傳媒》，一共七個媒體的臉書粉絲專頁上796則的媒體主文和40,911則回應文，探討兩者的數量和內容（主題、正負面情感和認知處理）、以及之間的互動關係和變化趨勢。結果發現，網友對氣爆事件的關注程度（回應文的數量）和對該事件的正負面情感和認知處理水平（回應文的內容）都受到媒體主文的影響。在各種影響中，每則主文對它的回應文，以認知活動的影響為主，情感表達為輔。正面情感是人們經常用來表達快樂、良好和甜美等正面情感的詞語；負面情感是人們經常用來表達恨、醜、焦慮、害怕和可怕等負面情感的詞語；而認知處理是人們經常用來表達與推理、思考和理性有關的詞語，例如：原因、知道、想等，來建立因果解釋和有效地組織思緒。粉絲團中的發文雖然監督了政府的災難管理，但網友總體的認知程度卻無法隨時間的推移有所累積，使用關於推理、思考和理性的詞語數量越來越少。跟傳統內容分析的方法相比較，電腦內容分析的方法用比較客觀的方式分析了社群媒體中媒體和網友大量的帖文內容。本研究所考察的粉絲團中媒體和網友的互動過程和效果類似傳統準實驗的研究方法，一方面在自然的環境中進行，有較高的外部效度；另一方面又可以從發文的時間前後直接推論媒體主文對網友回應文的影響力。

This study examines interactions between the news media and internet users in Facebook groups during the two months following the 2014 Kaohsiung gas explosions. The news media samples include three major newspapers in Taiwan (Apple Daily, United Daily, and Liberty Times) and four internet-based news outlets (New Talk, Independent Comments of Commonwealth, News Lens, and Storm Media). We conduct a computerized content analysis, which unlike a traditional content analysis, allows us to more objectively deal with a large amount of content. Using this method, we studied posts and comments related to the gas explosions in terms of their volume and content (i.e., topics, positive and negative emotions, and cognitive processing). We find that these posts and comments paid more attention to the cognitive aspect of the disaster than to positive and negative emotions. Further, while both the media and audience paid close attention to the government’s disaster management, in contrast with the news media, the audience’s cognitive processing diminished over time and thus, related knowledge could not be accumulated. This study also examines the impact of media posts on Facebook fans' comments while controlling for time sequence in a natural environment, which is similar to a quasi-experiment, and doing so improved both external and internal validities.

1. Tan, Y.,Shaw, P.(2018).Attributes Priming Effects on Presidential Approval: The Role of Risk Perception and Trust in Government Regulation.Issues & Studies,54(3),1-34.
   連結：
2. 林照真(2013)。台灣電視新聞之災難報導：以莫拉克風災為例。新聞學研究，115，141-185。
   連結：
3. 施琮仁(2017)。從雙路徑模型探討風險訊息的包裝與呈現對環境友善行為意圖的影響。傳播研究與實踐，7(1)，5-36。
   連結：
4. 黃俊儒,簡妙如(2006)。科技新聞文本的論述層次及結構分佈。新聞學研究，86，135-170。
   連結：
5. 黃厚銘(2013)。流動的群聚（mob-ility）：網路起網路起鬨的社會心理基礎。新聞學研究，115，1-50。
   連結：
6. 劉蕙苓(2014)。匯流下的變貌：網路素材使用對電視新聞常規的影響。新聞學研究，121，41-87。
   連結：
7. 謝君蔚,徐美苓(2011)。媒體再現科技發展與風險的框架與演變：以基因改造食品新聞為例。中華傳播學刊，20，143-179。
   連結：
8. Baden, C.,Springer, N.(2014).Com(ple)menting the news on the financial crisis: The contribution of news users’ commentary to the diversity of viewpoints in the public debate.European Journal of Communication,29(5),529-548.
9. Barnes, M. D.,Hanson, C. L.,Novilla, L. M.,Meacham, A. T.,McIntyre, E.,Erickson, B. C.(2008).Analysis of media agenda setting during and after Hurricane Katrina: Implications for emergency preparedness, disaster response, and disaster policy.American Journal of Public Health,98(4),604-610.
10. Beck, U.(1992).Risks society: Towards a new modernity.London, UK:Sage.
11. Boholm, M.(2009).Risk and causality in newspaper reporting.Risk Analysis,29(11),1566-1577.
12. Bostner, F. J.(Ed.),Barnett, G.(Ed.)(1997).Progress in communication sciences.Greenwich, CT:Ablex.
13. Boyle, M. P.,Schmierbach, M.,Armstrong, C. L.,McLeod, D. M.,Shah, D. V.,Pan, Z.(2004).Information seeking and emotional reactions to the September 11 terrorist attacks.Journalism & Mass Communication Quarterly,81(1),155-167.
14. Chaffee, S. H.,Metzger, M. J.(2001).The end of mass communication?.Mass Communication & Society,4(4),365-379.
15. Cohn, M. A.,Mehl, M. R.,Pennebaker, J. W.(2004).Linguistic markers of psychological change surrounding September 11, 2001.Psychological Science,15(10),687-693.
16. Coppola, D. P.(2007).Introduction to international disaster management.Boston, MA:Butterworth-Heinemann.
17. Correa, T.,Scherman, A.,Arriagada, A.(2016).Audiences and disasters: Analyses of media diaries before and after an earthquake and a massive fire.Journal of Communication,66(4),519-541.
18. Desai, D. (2012). Discursive narratives about nuclear power in the aftermath of Fukushima: A media analysis on the New York Times and the Wall Street Journal. Retrieved from http://nature.berkeley.edu/classes/es196/projects/2012final/DesaiD _2012.pdf
19. Doyle, J.(2011).Acclimatizing nuclear? Climate change, nuclear power and the reframing of risk in the UK news media.The International Communication Gazette,73(1-2),107-125.
20. Gamson, W.A.,Modigliani, A.(1989).Media discourse and public opinion on nuclear power: A constructionist approach.American Journal of Sociology,95(1),1-37.
21. Grimmer, J.(2015).We are all social scientists now: How big data, machine learning, and causal inference work together.PS: Political Science & Politics,48(1),80-83.
22. Grimmer, J.,Stewart, B. M.(2013).Text as data: The promise and pitfalls of automatic content analysis methods for political texts.Political Analysis,21(3),267-297.
23. Guo, L.,Vargo, C. J.,Pan, Z. X.,Ding, W. C.,Ishwar, P.(2016).Big social data analytics in journalism and mass communication: Comparing dictionary-based text analysis and unsupervised topic modeling.Journalism & Mass Communication Quarterly,93(2),332-359.
24. Guo, Y.,Barnes, S. J.,Jia, Q.(2017).Mining meaning from online ratings and reviews: Tourist satisfaction analysis using latent dirichlet allocation.Tourism Management,59,467-483.
25. Himelboim, I.,McCreery, S.(2012).New technology, old practices: Examining news websites from a professional perspective.Convergence,18(4),427-444.
26. Hodkinson, P.(2010).Media, culture and society: An introduction.Thousand Oaks, CA:Sage.
27. Höppner, C.,Bründl, M.,Buchecker, M.(2010).CapHaz-Net WP5 ReportCapHaz-Net WP5 Report,Swiss Federal Research Institute WSL.
28. Humphreys, A.,Wang, R. J.-H.(2018).Automated text analysis for consumer research.Journal of Consumer Research,44(6),1274-1306.
29. Kim, S.,Scheufele, D.,Shanahan, J.(2002).Think about it this way: Attribute agenda-setting function of the press and the public's evaluation of a local issue.Journalism & mass communication quarterly,79(1),7-25.
30. Kitzinger, J.(1999).Researching risk and the media.Health, risk & society,1(1),55-69.
31. Kruikemeier, S.(2014).How political candidates use Twitter and the impact on votes.Computers in Human Behavior,34,131-139.
32. Kubey, R. W.,Peluso, T.(1990).Emotional response as a cause of interpersonal news diffusion: The case of the space shuttle tragedy.Journal of Broadcasting & Electronic Media,34(1),69-76.
33. Lazic, D.(2013).News analysis of the Fukushima accident: lack of information disclosure, radiation fears and accountability issues.Journal of Contemporary Eastern Asia,12(2),19-34.
34. McCombs, M.(2004).Setting the agenda: The mass media and public opinion.Oxford, UK:Polity Press.
35. McCombs, M. E.,Shaw, D. L.(1972).The agenda-setting function of mass media.Public Opinion Quarterly,36(2),176-187.
36. Miller, J,Krosnick, J.(2000).News media impact on the ingredients of presidential evaluations: Politically knowledgeable citizens are guided by a trusted source.American Journal of Political Science,44(2),301-315.
37. Mohr, J. W.,Bogdanov, P.(2013).Introduction-Topic models: What they are and why they matter.Poetics,41(6),545-569.
38. Neuman, R. W.,Guggenheim, L.,Mo Jang, S.,Bae, S. Y.(2014).The dynamics of public attention: Agenda­setting theory meets big data.Journal of Communication,64(2),193-214.
39. Newman, N.,Dutton, W. H.,Blank, G.(2012).Social media in the changing ecology of news: The fourth and fifth estates in Britain.International Journal of Internet Science,7(1),6-22.
40. Orgad, S.(2012).Media representation and the global imagination.Cambridge, UK:Polity Press.
41. Paul, M. J.(2001).Interactive disaster communication on the Internet: A content analysis of sixty-four disaster relief home pages.Journalism & Mass Communication Quarterly,78(4),739-753.
42. Reed, D. P.(2001).The law of the pack.Harvard business review,79(2),23.
43. Reese, S. D.(Ed.),Gandy, O. H., Jr.(Ed.),Grant, A. E.(Ed.)(2001).Framing public life.Mahwah, NJ:Lawrence Erlbaum.
44. Rim, H.,Ha, J. H.,Kiousis, S.(2014).The evidence of compelling arguments in agenda building: Relationships among public information subsidies, media coverage, and risk perceptions during a pandemic outbreak.Journal of Communication Management,18(1),101-116.
45. Scheufele, D.(2014).Science communication as political communication.Proceedings of the National Academy of Sciences,111(4),13585-13592.
46. Sheafer, T.(2007).How to evaluate it: The role of story­evaluative tone in agenda setting and priming.Journal of Communication,57(1),21-39.
47. Silge, J.,Robinson, D.(2017).Text Mining with R: A tidy approach.Sebastopol, CA:O’Reilly Media.
48. Song, Y.,Dai, X. Y.,Wang, J.(2016).Not all emotions are created equal: Expressive behavior of the networked public on China's social media site.Computers in Human Behavior,60,525-533.
49. Tanner, A.,Friedman, D. B.,Koskan, A.,Barr, D.(2009).Disaster communication on the Internet: A focus on mobilizing information.Journal of Health Communication,14(8),741-755.
50. Tirunillai, S.,Tellis, G. J.(2014).Mining marketing meaning from online chatter: Strategic brand analysis of big data using latent dirichlet allocation.Journal of Marketing Research,51(4),463-479.
51. Tumasjan, A.,Sprenger, T. O.,Sandner, P. G.,Welpe, I. M.(2011).Election forecasts with Twitter: How 140 characters reflect the political landscape.Social Science Computer Review,29(4),402-418.
52. van der Meer, T. G.(2016).Public frame building: The role of source usage in times of Crisis.Communication Research
53. Veil, S. R.,Buehner, T.,Palenchar, M. J.(2011).A work­in­process literature review: Incorporating social media in risk and crisis communication.Journal of Contingencies and Crisis Management,19(2),110-122.
54. Verroen, S.,Gutteling, J. M.,Vries, P. W.(2013).Enhancing self­protective behavior: Efficacy beliefs and peer Feedback in risk communication.Risk Analysis,33(7),1252-1264.
55. Weimann, G.,Weiss-Blatt, N.,Mengistu, G.,Tregerman, M. M.,Oren, R.(2014).Reevaluating "The end of mass communication?".Mass Communication and Society,17(6),803-829.
56. Young, L.,Soroka, S. N.(2012).Affective news: The automated coding of sentiment in political texts.Political Communication,29(2),205-231.
57. Zhong, Z.,Lin, S.,Liu, X.,Yang, Y.(2017).New media event in collective memory (2002-2014): Aperspective on sentiment analysis.Communication & Society,40,105-134.
58. 中華民國監察院（2015）。《調查報告》。（調查案號：104 財調 0004）。取自https://www.cy.gov.tw/sp.asp?xdurl=./CyBsBox/CyBsR1.asp&ctNode=910
59. 張卿卿,陶振超(2017)。科技部補助專題研究計畫科技部補助專題研究計畫,未出版
60. 鄭宇君(2014)。災難傳播中的群體力量：社交媒體促成新型態的公民參與。傳播與社會學刊，27，179-205。
61. 蕭蘋,譚躍(2016)。網路與傳統新聞媒體災難報導框架之比較：以高雄氣爆事件為例。2017 電子商務與網路社會，高雄市:
62. 蘇蘅,張寶芳(2010)。部落格與競選傳播：以 2008 年台灣總統大選候選人為例。傳播與社會學刊，11，105-139。

1. 蘇婷,黃惠萍(2022)。網路熱點議題中黨媒、市場化媒體的媒體間議題設定效應：以2013-2020年微博熱點議題為例。新聞學研究，152，101-159。
2. (2021)。臺灣空污新聞在網路中的擴散、集體守門和議題設定。中華傳播學刊，39，147-193。