Sense‐Making in Social Media During Extreme Events

During an extreme event, individuals use social media to communicate, self-organize, manage, and mitigate risks (crisis-related communications) but also to make sense of the event (commentary-related communications). This study focuses on commentary-based social media communication practices of Twitter users to understand the processes and patterns of inter-subjective sense-making during an extreme event. We analyse Twitter communication generated during three events: The Sydney Lindt Cafe Siege (2014), the Germanwings plane crash (2015), and the Brussels Terror Attacks (2016). We focus on the (i) communication structure, (ii) emotionality of the content via sentiment analyses, and (iii) influence of Twitter users on communications via social network analyses. We identified differences in the communication structures between the three events, which suggests a research agenda focussed on inter-subjective sense-making through the use of social media platforms, would make a significant contribution to knowledge about social media adoption and use in extreme events.

[1]  B. Dervin.  AN OVERVIEW OF SENSE-MAKING RESEARCH: CONCEPTS, METHODS AND RESULTS TO DATE , 1983 .

[2]  Brenda Dervin,et al.  From the mind’s eye of the user: The sense-making qualitative-quantitative methodology. , 1992 .

[3]  E. Wenger.  Communities of Practice: Learning, Meaning, and Identity , 1998 .

[4]  M. Grant,et al.  Communities of practice. , 2020, Health progress.

[5]  K. Weick,et al.  Organizing and the Process of Sensemaking , 2005 .

[6]  Conan C. Albrecht,et al.  Motivating Content Contributions to Online Communities: Toward a More Comprehensive Theory , 2005, Proceedings of the 38th Annual Hawaii International Conference on System Sciences.

[7]  Daniel D. Suthers,et al.  Technology affordances for intersubjective meaning making: A research agenda for CSCL , 2006, Int. J. Comput. Support. Collab. Learn..

[8]  Gary Klein,et al.  Making Sense of Sensemaking 1: Alternative Perspectives , 2006, IEEE Intelligent Systems.

[9]  E. D. Paolo,et al.  Participatory sense-making , 2007 .

[10]  H. D. Jaegher,et al.  Enactive intersubjectivity: Participatory sense-making and mutual incorporation , 2009 .

[11]  Leysia Palen,et al.  Twitter adoption and use in mass convergence and emergency events , 2009 .

[12]  O-Kab Kwon,et al.  Enhanced supersymmetry of nonrelativistic ABJM theory , 2010, 1001.1598.

[13]  Hosung Park,et al.  What is Twitter, a social network or a news media? , 2010, WWW '10.

[14]  Tung Bui,et al.  An Exploration of Physical-Virtual Convergence Behaviors in Crisis Situations , 2010, 2010 43rd Hawaii International Conference on System Sciences.

[15]  Rebecca Goolsby,et al.  Social media as crisis platform: The future of community maps/crisis maps , 2010, TIST.

[16]  E. Wenger.  Communities of Practice and Social Learning Systems: the Career of a Concept , 2010 .

[17]  Kyounghee Hazel Kwon,et al.  An Exploration of Social Media in Extreme Events: Rumor Theory and Twitter during the Haiti Earthquake 2010 , 2010, ICIS.

[18]  Qiang Yang.  Introduction to ACM TIST , 2010, TIST.

[19]  T. Nakamura,et al.  Anti-apoptotic function of Xbp1 as an IL-3 signaling molecule in hematopoietic cells , 2011, Cell Death and Disease.

[20]  J. Crump.  What Are the Police Doing on Twitter? Social Media, the Police and the Public , 2011 .

[21]  Sean Fitzhugh,et al.  Connected communications: Network structures of official communications in a technological disaster , 2012, ISCRAM.

[22]  Kristina Lerman,et al.  Social Contagion: An Empirical Study of Information Spread on Digg and Twitter Follower Graphs , 2012, ArXiv.

[23]  Brooke Fisher Liu,et al.  Social media use during disasters: a review of the knowledge base and gaps. , 2012 .

[24]  Stefan Stieglitz,et al.  Quantitative Approaches to Comparing Communication Patterns on Twitter , 2012 .

[25]  Axel Bruns,et al.  Tools and methods for capturing Twitter data during natural disasters , 2012, First Monday.

[26]  Frank Schweitzer,et al.  Emotional Divergence Influences Information Spreading in Twitter , 2012, ICWSM.

[27]  D. Bunker,et al.  Social Media in Disaster Response:Queensland Police Service - Public Engagement During the 2011 Floods , 2012 .

[28]  H. Raghav Rao,et al.  Community Intelligence and Social Media Services: A Rumor Theoretic Analysis of Tweets During Social Crises , 2013, MIS Q..

[29]  D. Bunker,et al.  The Impact of Disaster Typology on Social Media Use by Emergency Services Agencies: The Case of the Boston Marathon Bombing , 2013, ACIS.

[30]  Daniel Dajun Zeng,et al.  An Empirical Study of Information Diffusion in Micro-blogging Systems during Emergency Events , 2013, WAIM Workshops.

[31]  H. Raghav Rao,et al.  An Exploration of Collaboration over Time in Collective Crisis Response during the Haiti 2010 Earthquake , 2013, ICIS.

[32]  Mohammad Ali Abbasi,et al.  Measuring User Credibility in Social Media , 2013, SBP.

[33]  Jutta Geldermann,et al.  Combining Real and Virtual Volunteers through Social Media , 2013 .

[34]  Mike Thelwall,et al.  Topic-based sentiment analysis for the social web: The role of mood and issue-related words , 2013, J. Assoc. Inf. Sci. Technol..

[35]  Stefan Stieglitz,et al.  Communication Roles in Public Events - A Case Study on Twitter Communication , 2014, IS&O.

[36]  Brandon Van Der Heide,et al.  Social Media as Information Source: Recency of Updates and Credibility of Information , 2014, J. Comput. Mediat. Commun..

[37]  Howard Rosenbaum,et al.  Effects of reading proficiency on embedded stem priming in primary school children , 2021 .

[38]  Andrea H. Tapia,et al.  Good Enough is Good Enough: Overcoming Disaster Response Organizations’ Slow Social Media Data Adoption , 2014, Computer Supported Cooperative Work (CSCW).

[39]  Gregory D. Saxton,et al.  Tweeting Social Change , 2014 .

[40]  Xin Ma,et al.  Optimizing social media message dissemination problem for emergency communication , 2014, Comput. Ind. Eng..

[41]  Monideepa Tarafdar,et al.  From "information" to "knowing": Exploring the role of social media in contemporary news consumption , 2014, Comput. Hum. Behav..

[42]  Fang Liu,et al.  Rumors on Social Media in disasters: Extending Transmission to Retransmission , 2014, PACIS.

[43]  Mark Rhinard,et al.  Making Sense of Sense-Making : the EU’s Role in Collecting, Analysing, and Disseminating Information in Times of Crisis , 2014 .

[44]  William H. Sanders,et al.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , 2014 .

[45]  Alexander Zipf,et al.  Does the spatiotemporal distribution of tweets match the spatiotemporal distribution of flood phenomena? A study about the River Elbe Flood in June 2013 , 2014, ISCRAM.

[46]  Kambale Vanty Muhongya,et al.  Visualising and analysing online social networks , 2015, 2015 International Conference on Computing, Communication and Security (ICCCS).

[47]  Janek Benthaus,et al.  Investigating Consumer Information Search Behavior and Consumer Emotions to Improve Sales Forecasting , 2015, AMCIS.

[48]  Asim Karim,et al.  Bias-aware lexicon-based sentiment analysis , 2015, SAC.

[49]  Roman Beck,et al.  Disaster Management and Social Media Use for Decision Making by Humanitarian Organizations , 2016, 2016 49th Hawaii International Conference on System Sciences (HICSS).

[50]  Sarbani Roy,et al.  A Comparative Analysis of Different Social Network Parameters Derived from Facebook Profiles , 2016 .

[51]  Arash Joorabchi,et al.  Text mining stackoverflow: An insight into challenges and subject-related difficulties faced by computer science learners , 2016, J. Enterp. Inf. Manag..

[52]  Patric R. Spence,et al.  Exploring extreme events on social media: A comparison of user reposting/retweeting behaviors on Twitter and Weibo , 2016, Comput. Hum. Behav..

[53]  Mark Kröll,et al.  Sentiment Analysis for German Facebook Pages , 2016, NLDB.

[54]  Gareth W. Peters,et al.  Participatory Sensing Data Tweets for Micro-Urban Real-Time Resiliency Monitoring and Risk Management , 2016, IEEE Access.

[55]  Deborah Lupton,et al.  Toward a manifesto for the ‘public understanding of big data’ , 2016, Public understanding of science.

[56]  Stefan Stieglitz,et al.  Sensemaking and Communication Roles in Social Media Crisis Communication , 2017, Wirtschaftsinformatik.