An emerging online social network and disaster-induced collective stress

References

• Alawad, N. A., Anagnostopoulos, A., Leoardi, S., Mele, I., & Silvestri, F. (2016). Network-Aware Recommendations of Novel Tweets. In R. Perego, F. Sebastiani, J. A. Aslam, I. Ruthven, & J. Zobel (Eds.), Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, SIGIR 2016, Pisa, Italy, July 17-21, (pp. 913–916). doi:10.1145/2911451.2914760.
   Google Scholar
• Aldwin, C. (2007). Stress, coping, and development: An integrative perspective. New York, NY: Guilford Press.
   Google Scholar
• Althoff, T., Jindal, P., & Leskovec, J. (2017). Online Actions with Offline Impact: How Online Social Networks Influence Online and Offline User Behavior. In M. de Rijke, M. Shokouhi, A. Tomkins, & M. Zhang (Eds.), Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, WSDM 2017, Cambridge, United Kingdom, February 6-10, (pp. 537–546). Retrieved from http://dl.acm.org/citation.cfm?id=3018672.
   Google Scholar
• Ansell, C., Boin, A., & Keller, A. (2010). Managing transboundary crises: Identifying the building blocks of an effective response system. Journal of Contingencies and Crisis Management, 18(4), 195–207. doi:10.1111/jccm.2010.18.issue-4
   Google Scholar
• Barton, A. H. (1969). Communities in disaster: A sociological analysis of collective stress situations. New York, NY: Doubleday.
   Google Scholar
• Becker, J. C., Barreto, M., Kahn, K. B., & de Oliveira Laux, S. H. (2015). The collective value of “me” (and its limitations): Towards a more nuanced understanding of individual and collective coping with prejudice. Journal of Social Issues, 71(3), 497–516. doi:10.1111/josi.12125
   Web of Science ®Google Scholar
• Bellini, C. G. P., & Vargas, L. M. (2003). Rationale for internet-mediated communities. CyberPsychology & Behavior, 6(1), 3–14. doi:10.1089/109493103321167929
   PubMedGoogle Scholar
• Boyd, D., Golder, S., & Lotan, G. (2010). Tweet, Tweet, Retweet: Conversational Aspects of Retweeting on Twitter. 43rd Hawaii International International Conference on Systems Science (HICSS-43 2010), Proceedings, 5-8 January 2010, Koloa, Kauai, HI, USA, 1–10. doi:10.1109/HICSS.2010.412.
   Google Scholar
• Bradberry, C., & Salam, A. (2014). Communities of sentiment around man-made disasters: Lessons from the West Virginia chemical leak. In Twentieth Americas conference on information systems (pp. 1–11). Savannah, GA: Association for Information Systems.
   Google Scholar
• Branscombe, N. R., Ellemers, N., Spears, R., & Doosje, B. (1999). The context and content of social identity threat. In N. Ellemers, R. Spears, & B. Doosje (Eds.), Social identity: Context, commitment, content (pp. 35–58). Oxford, UK: Blackwell Science.
   Google Scholar
• Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3, 77–101. doi:10.1191/1478088706qp063oa
   Google Scholar
• Brett, M. R. (2012). Topic modeling: A basic introduction. Journal of Digital Humanities, 2(1), 12–16.
   Google Scholar
• Brissette, I., Scheier, M. F., & Carver, C. S. (2002). The role of optimism in social network development, coping, and psychological adjustment during a life transition. Journal of Personality and Social Psychology, 82(1), 102–111. doi:10.1037/0022-3514.82.1.102
   PubMed Web of Science ®Google Scholar
• Brown, R. (2000). Social identity theory: Past achievements, current problems and future challenges. European Journal of Social Psychology, 30(6), 745–778. doi:10.1002/1099-0992(200011/12)30:6<>1.0.CO;2-U
   Web of Science ®Google Scholar
• Calvard, T. S. (2015). Integrating organization studies and community psychology: A process model of an organizing sense of place in working lives. Journal of Community Psychology, 43(6), 654–686. doi:10.1002/jcop.2015.43.issue-6
   Web of Science ®Google Scholar
• Carstensen, L. L. (2006). The influence of a sense of time on human development. Science, 312(5782), 1913–1915. doi:10.1126/science.1127488
   PubMed Web of Science ®Google Scholar
• Cha, E. (2010). The Twitter ties that retweet: Information diffusion in social movements. Stanford, CA: Department of Communication, Stanford University.
   Google Scholar
• Chamlee-Wright, E. (2010). The cultural and political economy of recovery: Social learning in a post-disaster environment. London, UK: Routledge.
   Google Scholar
• Chavez-Dueñas, N. Y., & Adames, H. Y. (2018). # Neotericracism: Exploring race-based content in social media during racially charged current events. Revista Interamericana de Psicología, 52(1), 3–14.
   Google Scholar
• Cherepnalkoski, D., & Mozetic, I. (2015). A Retweet Network Analysis of the European Parliament. In K. Yétongnon & A. Dipanda (Eds.), 11th International Conference on Signal-Image Technology & Internet-Based Systems, SITIS 2015, Bangkok, Thailand, November 23–27, 2015 (pp. 350–357). doi:10.1109/SITIS.2015.8.
   Google Scholar
• Choo, C. W. (1998). The knowing organization: How organizations use information to construct meaning, create knowledge, and make decisions. New York, NY: Oxford University Press.
   Google Scholar
• Christophe, V., & Rime, B. (1997). Exposure to the social sharing of emotion: Emotional impact, listener responses and secondary social sharing. European Journal of Social Psychology, 27(1), 37–54. doi:10.1002/(SICI)1099-0992(199701)27:1<37::AID-EJSP806>3.0.CO;2-1
   Web of Science ®Google Scholar
• Cliff, N. (1988). The eigenvalues-greater-than-one rule and the reliability of components. Psychological Bulletin, 103(2), 276–279. doi:10.1037/0033-2909.103.2.276
   Web of Science ®Google Scholar
• Colville, I., Pye, A., & Carter, M. (2013). Organizing to counter terrorism: Sensemaking amidst dynamic complexity. Human Relations, 66(9), 1201–1223. doi:10.1177/0018726712468912
   Web of Science ®Google Scholar
• Davies, H., & Walters, M. (1998). Do all crises have to become disasters? Risk and risk mitigation. Property Management, 16(1), 5–9. doi:10.1108/02637479810202883
   Google Scholar
• de Zúñiga, H. G., Copeland, L., & Bimber, B. (2014). Political consumerism: Civic engagement and the social media connection. New Media & Society, 16(3), 488–506. doi:10.1177/1461444813487960
   Web of Science ®Google Scholar
• Deetz, S. (2001). Conceptual foundations. The new handbook of organizational communication: Advances in theory, research, and methods. Thousand Oaks, CA: Sage.
   Google Scholar
• Den Ouden, M. D., & Russell, G. W. (1997). Sympathy and altruism in response to disasters: A Dutch and Canadian comparison. Social Behavior and Personality: an International Journal, 25(3), 241–247. doi:10.2224/sbp.1997.25.3.241
   Web of Science ®Google Scholar
• Evangelopoulos, N., Zhang, X., & Prybutok, V. R. (2012). Latent semantic analysis: Five methodological recommendations. European Journal of Information Systems, 21, 70–86. doi:10.1057/ejis.2010.61
   Web of Science ®Google Scholar
• Festinger, L. (1950). Informal social communication. Psychological Review, 57(5), 271–282. doi:10.1037/h0056932
   PubMed Web of Science ®Google Scholar
• Folger, R. (2001). Fairness and deonance. In S. W. Gilliland, D. D. Steiner, & D. P. Skarlicki (Eds.), Research in social issues in management (pp. 3–31). Charlotte, NC: Information Age.
   Google Scholar
• Folkman, S., Lazarus, R. S., Dunkel-Schetter, C., DeLongis, A., & Gruen, R. J. (1986). Dynamics of a stressful encounter: Cognitive appraisal, coping, and encounter outcomes. Journal of Personality and Social Psychology, 50(5), 992–1003. doi:10.1037/0022-3514.50.5.992
   PubMed Web of Science ®Google Scholar
• García, S., Luengo, J., & Herrera, F. (2015). Data Preprocessing in Data Mining. Switzerland: Springer International Publishing. doi:10.1007/978-3-319-10247-4.
   Google Scholar
• Garrison, D. R., Anderson, T., & Archer, W. (1999). Critical inquiry in a text-based environment: Computer conferencing in higher education. The Internet and Higher Education, 2(2), 87–105. doi:10.1016/S1096-7516(00)00016-6
   Google Scholar
• Gephi. (2011). The open graph viz platform. Retrieved from http://gephi.org/
   Google Scholar
• Gultom, D. I. (2016). Community-based disaster communication: How does it become trustworthy? Disaster Prevention and Management: an International Journal, 25(4), 478–491. doi:10.1108/DPM-02-2016-0026
   Web of Science ®Google Scholar
• Gurman, T. A., & Ellenberger, N. (2015). Reaching the global community during disasters: Findings from a content analysis of the organizational use of Twitter after the 2010 Haiti earthquake. Journal of Health Communication, 20(6), 687–696. doi:10.1080/10810730.2014.927034
   PubMed Web of Science ®Google Scholar
• Guttman, L. (1954). A new approach to factor analysis: The radex. In P. Lazerfeld (Ed.), Mathematical thinking in the social sciences (pp. 258–348). Glencoe, IL: Free Press.
   Google Scholar
• Halinen, A., Törnroos, J.-Å., & Elo, M. (2013). Network process analysis: An event-based approach to study business network dynamics. Industrial Marketing Management, 42(8), 1213–1222. doi:10.1016/j.indmarman.2013.05.001
   Web of Science ®Google Scholar
• Halse, S. E., Tapia, A. H., Squicciarini, A. C., & Caragea, C. (2016). Tweet factors influencing trust and usefulness during both man-made and natural disasters. In Proceedings of the Information Systems for Crisis Response and Management (ISCRAM) 2016 conference, Rio de Janeiro, Brazil.
   Google Scholar
• Harlow, S. (2012). Social media and social movements: Facebook and an online Guatemalan justice movement that moved offline. New Media & Society, 14(2), 225–243. doi:10.1177/1461444811410408
   Web of Science ®Google Scholar
• Haslam, S. A., Jetten, J., Postmes, T., & Haslam, C. (2009). Social identity, health and well‐being: An emerging agenda for applied psychology. Applied Psychology, 58(1), 1–23. doi:10.1111/apps.2009.58.issue-1
   Web of Science ®Google Scholar
• Herring, S. C. (1996). Computer-mediated communication: Linguistic, social, and cross-cultural perspectives. Philadelphia, PA: John Benjamins Publishing Company.
   Google Scholar
• Himelboim, I., Smith, M. A., Rainie, L., Shneiderman, B., & Espina, C. (2017). Classifying Twitter topic-networks using social network analysis. Social Media + Society, 3(1), 2056305117691545. doi:10.1177/2056305117691545
   Web of Science ®Google Scholar
• Hofmann, T. (2001). Unsupervised learning by probabilistic latent semantic analysis. Machine Learning, 42(1–2), 177–196. doi:10.1023/A:1007617005950
   Web of Science ®Google Scholar
• Houston, J. B., Hawthorne, J., Perreault, M. F., Park, E. H., Hode, M. G., Halliwell, M. R., … Griffith, S. A. (2015). Social media and disasters: A functional framework for social media use in disaster planning, response, and research. Disasters, 39(1), 1–22. doi:10.1111/disa.12092
   PubMed Web of Science ®Google Scholar
• Hsieh, H.-F., & Shannon, S. E. (2005). Three approaches to qualitative content analysis. Qualitative Health Research, 15(9), 1277–1288. doi:10.1177/1049732305276687
   PubMed Web of Science ®Google Scholar
• Kavoura, A., & Stavrianea, A. (2014). Economic and social aspects from social media‘s implementation as a strategic innovative marketing tool in the tourism industry. Procedia Economics and Finance, 14, 303–312. doi:10.1016/S2212-5671(14)00717-5
   Google Scholar
• Kim, K. H., Jang, S., Lee, J. A., Jang, B.-H., Go, H.-Y., Park, S., … Ko, S.-G. (2017). Experiences providing medical assistance during the sewol ferry disaster using traditional Korean medicine. Evidence-Based Complementary and Alternative Medicine, (2017(2), 1–7.
   Google Scholar
• Kim, M.-J. (2002). Does Korean have adjectives. MIT Working Papers in Linguistics, 43, 71–89. doi:10.3349/ymj.2002.43.5.613
   Google Scholar
• Kossinets, G., & Watts, D. J. (2006). Empirical analysis of an evolving social network. Science, 311(5757), 88–90. doi:10.1126/science.1116869
   PubMed Web of Science ®Google Scholar
• L‘Huillier, G., Ríos, S. A., Alvarez, H., & Aguilera, F. (2010). Topic-based social network analysis for virtual communities of interests in the dark web. In ACM SIGKDD workshop on intelligence and security informatics (pp. 1–99). New York, NY: ACM.
   Google Scholar
• Lazarus, R., & Folkman, S. (1984). Stress, coping, and adaptation. New York, NY: Springer-Verlag.
   Google Scholar
• Lazarus, R. S. (1991). Emotion and adaptation. New York, NY: Oxford University Press.
   Google Scholar
• Lewis, S. C., Zamith, R., & Hermida, A. (2013). Content analysis in an era of big data: A hybrid approach to computational and manual methods. Journal of Broadcasting & Electronic Media, 57(1), 34–52. doi:10.1080/08838151.2012.761702
   Web of Science ®Google Scholar
• Lin, X., Lachlan, K. A., & Spence, P. R. (2016). Exploring extreme events on social media: A comparison of user reposting/retweeting behaviors on Twitter and Weibo. Computers in Human Behavior, 65, 576–581. doi:10.1016/j.chb.2016.04.032
   Web of Science ®Google Scholar
• Locher, D. A. (2002). Collective behavior. Upper Saddle, NJ: Prentice Hall.
   Google Scholar
• Locke, E. A., & Latham, G. P. (1990). Work motivation and satisfaction: Light at the end of the tunnel. Psychological Science, 1(4), 240–246. doi:10.1111/j.1467-9280.1990.tb00207.x
   Web of Science ®Google Scholar
• Manning, C. D., Raghavan, P., & Schütze, H. (2008). Introduction to information retrieval. Cambridge, MA: Cambridge University Press.
   Google Scholar
• 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. doi:10.1177/1461444810365313
   Web of Science ®Google Scholar
• Miller, B. M., & Horsley, J. S. (2009). Digging deeper: Crisis management in the coal industry. Journal of Applied Communication Research, 37, 298–316. doi:10.1080/00909880903025903
   Web of Science ®Google Scholar
• Moody, J., McFarland, D., & Bender-deMoll, S. (2005). Dynamic network visualization. American Journal of Sociology, 110(4), 1206–1241. doi:10.1086/421509
   Web of Science ®Google Scholar
• Mullen, J., Vladi, N., & Mills, A. J. (2006). Making sense of the Walkerton crisis. Culture and Organization, 12(3), 207–220. doi:10.1080/14759550600865933
   Google Scholar
• Muter, B. A., Gore, M. L., & Riley, S. J. (2013). Social contagion of risk perceptions in environmental management networks. Risk Analysis, 33(8), 1489–1499. doi:10.1111/risa.2013.33.issue-8
   PubMed Web of Science ®Google Scholar
• Oh, O., Eom, C., & Rao, H. R. (2015). Research note—Role of social media in social change: An analysis of collective sense making during the 2011 egypt revolution. Information Systems Research, 26(1), 210–223. doi:10.1287/isre.2015.0565
   Web of Science ®Google Scholar
• Opsahl, T., Agneessens, F., & Skvoretz, J. (2010). Node centrality in weighted networks: Generalizing degree and shortest paths. Social Networks, 32(3), 245–251. doi:10.1016/j.socnet.2010.03.006
   Web of Science ®Google Scholar
• Oussalah, M., Bhat, F., Challis, K., & Schnier, T. (2013). A software architecture for Twitter collection, search and geolocation services. Knowledge-Based Systems, 37, 105–120. doi:10.1016/j.knosys.2012.07.017
   Web of Science ®Google Scholar
• Owens, D. J. (2003). Does belief have an aim?. Philosophical Studies, 115(3), 283–305. doi:10.1023/A:1025157101089
   Web of Science ®Google Scholar
• Patterson, O., Weil, F., & Patel, K. (2010). The role of community in disaster response: Conceptual models. Population Research and Policy Review, 29(2), 127–141. doi:10.1007/s11113-009-9133-x
   Web of Science ®Google Scholar
• Pearlin, L. I., & Schooler, C. (1978). The structure of coping. Journal of Health and Social Behavior, 19, 2–21. doi:10.2307/2136319
   PubMed Web of Science ®Google Scholar
• Pennebaker, J. W., & Harber, K. D. (1993). A social stage model of collective coping: The loma prieta earthquake and the persian gulf war. Journal of Social Issues, 49(4), 125–145. doi:10.1111/josi.1993.49.issue-4
   Web of Science ®Google Scholar
• Perry, R. W. (2007). What is a disaster?. In H. Rodriguez, E. L. Quarantelli, & R. R. Dynes (Eds.), Handbook of disaster research (pp. 1–15). New York, NY: Springer.
   Google Scholar
• Petrovic, S., Osborne, M., & Lavrenko, V. (2011). Rt to win! predicting message propagation in Twitter. Icwsm, 11, 586–589.
   Google Scholar
• Piedrahita, P., Borge-Holthoefer, J., Moreno, Y., & González-Bailón, S. (2018). The contagion effects of repeated activation in social networks. Social Networks, 54, 326–335. doi:10.1016/j.socnet.2017.11.001
   Web of Science ®Google Scholar
• Potter, W. J., & Levine‐Donnerstein, D. (1999). Rethinking validity and reliability in content analysis. Journal of Applied Communication Research, 27(3), 258–284. doi:10.1080/00909889909365539
   Web of Science ®Google Scholar
• Quarantelli, E. L., & Dynes, R. R. (1977). Response to social crisis and disaster. Annual Review of Sociology, 3(1), 23–49. doi:10.1146/annurev.so.03.080177.000323
   Web of Science ®Google Scholar
• Salton, G., & Buckley, C. (1988). Term-weighting approaches in automatic text retrieval. Information Processing & Management, 24(5), 513–523. doi:10.1016/0306-4573(88)90021-0
   Web of Science ®Google Scholar
• Salton, G., Wong, A., & Yang, C.-S. (1975). A vector space model for automatic indexing. Communications of the ACM, 18(11), 613–620. doi:10.1145/361219.361220
   Web of Science ®Google Scholar
• Shaluf, I. M., Ahmadun, F. L.-R., & Said, A. M. (2003). A review of disaster and crisis. Disaster Prevention and Management: an International Journal, 12(1), 24–32. doi:10.1108/09653560310463829
   Google Scholar
• Shi, J., Lai, K. K., Hu, P., & Chen, G. (2017). Understanding and predicting individual retweeting behavior: Receiver perspectives. Applied Soft Computing, 60, 844–857. doi:10.1016/j.asoc.2017.08.044
   Web of Science ®Google Scholar
• Sidorova, A., Evangelopoulos, N., Valacich, J. S., & Ramakrishnan, T. (2008). Uncovering the intellectual core of the information systems discipline. MIS Quarterly, 32, 467–482. doi:10.2307/25148852
   Web of Science ®Google Scholar
• Skinner, E. A., Edge, K., Altman, J., & Sherwood, H. (2003). Searching for the structure of coping: A review and critique of category systems for classifying ways of coping. Psychological Bulletin, 129(2), 216–269. doi:10.1037/0033-2909.129.2.216
   PubMed Web of Science ®Google Scholar
• Smith, C. A., & Lazarus, R. S. (1993). Appraisal components, core relational themes, and the emotions. Cognition & Emotion, 7(3–4), 233–269. doi:10.1080/02699939308409189
   Web of Science ®Google Scholar
• Smith, E. R., & Mackie, D. M. (2006). It’s about time: Intergroup emotions as time-dependent phenomena. In D. Capozza & R. Brown (Eds.), Social identities: Motivational, emotional, and cultural influences (pp. 173–187). Oxford, UK: Blackwell.
   Google Scholar
• Smith, M. A., Rainie, L., Shneiderman, B., & Himelboim, I. (2014). Mapping Twitter topic networks: From polarized crowds to community clusters. Washington, DC: Pew Research Center.
   Google Scholar
• Snyder, M., & Omoto, A. (2007). Social action. In A. Kruglanski & E. T. Higgins (Eds.), Social psychology: A handbook of basic principles (pp. 940–961). New York, NY: Guilford.
   Google Scholar
• Spence, P. R., Lachlan, K. A., Lin, X., & Del Greco, M. (2015). Variability in Twitter content across the stages of a natural disaster: Implications for crisis communication. Communication Quarterly, 63, 171–186. doi:10.1080/01463373.2015.1012219
   Web of Science ®Google Scholar
• Starbird, K., & Palen, L. (2010). Pass it on? Retweeting in mass emergency. In S. French, B. Tomaszewski, & C. Zobel (Eds.), ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings (pp. 1–10). Seattle, WA: Information Systems for Crisis Response and Management. Retrieved from http://idl.iscram.org/files/starbird/2010/970_Starbird+Palen2010.pdf.
   Google Scholar
• Stemler, S. (2001). An overview of content analysis. Practical Assessment, Research & Evaluation, 7(17), 137–146.
   Google Scholar
• Stigliani, I., & Ravasi, D. (2012). Organizing thoughts and connecting brains: Material practices and the transition from individual to group-level prospective sensemaking. Academy of Management Journal, 55(5), 1232–1259. doi:10.5465/amj.2010.0890
   Web of Science ®Google Scholar
• Stone, L. D., & Pennebaker, J. W. (2002). Trauma in real time: Talking and avoiding online conversations about the death of Princess Diana. Basic and Applied Social Psychology, 24, 173–183. doi:10.1207/S15324834BASP2403_1
   Web of Science ®Google Scholar
• Suh, B., Hong, L., Pirolli, P., & Chi, E. H. (2010). Want to be Retweeted? Large Scale Analytics on Factors Impacting Retweet in Twitter Network. In A. K. Elmagarmid & D. Agrawal (Eds.), Proceedings of the 2010 IEEE Second International Conference on Social Computing, SocialCom / IEEE International Conference on Privacy, Security, Risk and Trust, PASSAT 2010, Minneapolis, Minnesota, USA, August 20-22, 2010 (pp. 177–184). doi:10.1109/SocialCom.2010.33.
   Google Scholar
• Taatgen, N. A., van Rijn, H., & Anderson, J. (2007). An integrated theory of prospective time interval estimation: The role of cognition, attention, and learning. Psychological Review, 114(3), 577–598. doi:10.1037/0033-295X.114.3.577
   PubMed Web of Science ®Google Scholar
• Tang, X., Wang, J., Zhong, J., & Pan, Y. (2014). Predicting essential proteins based on weighted degree centrality. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 11(2), 407–418. doi:10.1109/TCBB.2013.2295318
   PubMed Web of Science ®Google Scholar
• Uysal, A. K., & Gunal, S. (2014). The impact of preprocessing on text classification. Information Processing & Management, 50(1), 104–112. doi:10.1016/j.ipm.2013.08.006
   Web of Science ®Google Scholar
• Van Liere, D. (2010). How far does a tweet travel?: Information brokers in the twitterverse. In A. Chin, A. Hotho, & M. Strohmaier (Eds.), Proceedings of the International Workshop on Modeling Social Media, MSM 2010, Toronto, ON, Canada, June 13, 2010 (pp. 6:1–6:4). doi:10.1145/1835980.1835986.
   Google Scholar
• Wasko, M. M., & Faraj, S. (2000). “It is what one does”: Why people participate and help others in electronic communities of practice. The Journal of Strategic Information Systems, 9(2), 155–173. doi:10.1016/S0963-8687(00)00045-7
   Web of Science ®Google Scholar
• Webberley, W. M., Allen, S. M., & Whitaker, R. M. (2016). Retweeting beyond expectation: Inferring interestingness in Twitter. Computer Communications, 73, 229–235. doi:10.1016/j.comcom.2015.07.016
   Web of Science ®Google Scholar
• Weick, K. (1969). Communities in disaster: A sociological analysis of collective stress situations. New York, NY: Doubleday.
   Google Scholar
• Weick, K. E. (1979). Cognitive processes in organizations. Research in Organizational Behavior, 1, 41–74.
   Google Scholar
• Weick, K. E. (1995). Sensemaking in organizations. Thousand Oaks, CA: Sage Publications.
   Google Scholar
• Weick, K. E. (2012). Organized sensemaking: A commentary on processes of interpretive work. Human Relations, 65(1), 141–153. doi:10.1177/0018726711424235
   Web of Science ®Google Scholar
• Weick, K. E., Sutcliffe, K. M., & Obstfeld, D. (2005). Organizing and the process of sensemaking. Organization Science, 16, 409–421. doi:10.1287/orsc.1050.0133
   Web of Science ®Google Scholar
• Woo, H., Cho, Y., Shim, E., Lee, K., & Song, G. (2015). Public trauma after the sewol ferry disaster: The role of social media in understanding the public mood. International Journal of Environmental Research and Public Health, 12(9), 10974–10983. doi:10.3390/ijerph120910974
   PubMed Web of Science ®Google Scholar
• Yin, R. K. (1994). Discovering the future of the case study method in evaluation research. Evaluation Practice, 15(3), 283–290. doi:10.1016/0886-1633(94)90023-X
   Google Scholar
• Zakay, D., & Block, R. A. (2004). Prospective and retrospective duration judgments: An executive-control perspective. Acta Neurobiologiae Experimentalis, 64(3), 319–328.
   PubMed Web of Science ®Google Scholar
• Zarbafi, E. M. (2011). Responsible investment and the claim of corporate change-making sense of institutional investors as drivers of corporate social responsibility. Heidelberg, Germany: Springer.
   Google Scholar
• Zhao, Z., Feng, S., Wang, Q., Huang, J. Z., Williams, G. J., & Fan, J. (2012). Topic oriented community detection through social objects and link analysis in social networks. Knowledge-Based Systems, 26, 164–173. doi:10.1016/j.knosys.2011.07.017
   Web of Science ®Google Scholar