Natural Hazards

, Volume 89, Issue 1, pp 161–181 | Cite as

Crisis information distribution on Twitter: a content analysis of tweets during Hurricane Sandy

  • Bairong Wang
  • Jun Zhuang
Original Paper


Social media has been widely used for crisis communication during disasters, and its use during extreme events has drawn attention from both researchers and practitioners. Although crisis information coverage and distribution speed are important issues, both have not been studied extensively in the literature. This paper fills this gap by studying information distribution and coverage of social media during disasters. To this end, we searched and analyzed 986,579 tweets posted during Hurricane Sandy (October 22 to November 6, 2012). To learn about responses from official agents, we sampled 163 governmental organizations (GO), 31 non-governmental organizations (NGO) and 276 news agent accounts and their tweets for analysis. Specifically, five social media key performance indicators (KPIs) are studied in this paper, including impression, like, mention, re-tweet, and response time, and other variables such as hashtag, tweet frequency, and information type. We also test whether the five KPIs and other variables are different among different user types. Results show that total impression, re-tweet rate, hashtag, and tweet frequency are significantly \((P<0.05)\) different among different user types. Specifically, although news agent users generate a larger number of total impressions and tweet more frequently than GO and NGO users, their re-tweet rates and number of hashtags are lower than the GO and NGO users. Re-tweet rate based on mentioned users (5%) is significantly higher \((P=0.00)\) than that based on regular followers (0.01%). Nearly 89% of total impressions are generated from regular followers, with impressions from re-tweeting being a minority. This paper provides some new insights into how social media was used for crisis communication during disasters.


Crisis communication Social media Hurricane Sandy Content analysis 


  1. Abedin B, Babar A, Abbasi A (2014) Characterization of the use of social media in natural disasters: a systematic review. In: 2014 IEEE fourth international conference on big data and cloud computing (BdCloud), Sydney, NSW, pp 449–454Google Scholar
  2. Acar A, Muraki Y (2011) Twitter for crisis communication: lessons learned from Japan’s tsunami disaster. Int J Web Based Communities 7(3):392–402CrossRefGoogle Scholar
  3. Alexander DE (2014) Social media in disaster risk reduction and crisis management. Sci Eng Ethics 20(3):717–733CrossRefGoogle Scholar
  4. Al-Saggaf Y, Simmons P (2015) Social media in Saudi Arabia: exploring its use during two natural disasters. Technol Forecast Soc Chang 95:3–15CrossRefGoogle Scholar
  5. Barabási A-L (2009) Scale-free networks: a decade and beyond. Science 325(5939):412–413CrossRefGoogle Scholar
  6. Barbier G, Zafarani R, Gao H, Fung G, Liu H (2012) Maximizing benefits from crowdsourced data. Comput Math Organ Theory 18(3):257–279CrossRefGoogle Scholar
  7. Berg BL, Lune H, Lune H (2004) Qualitative research methods for the social sciences, 5th edn. Pearson, BostonGoogle Scholar
  8. Berger J, Milkman KL (2012) What makes online content viral? J Mark Res 49(2):192–205CrossRefGoogle Scholar
  9. Blake ES, Kimberlain TB, Berg RJ, John CP, Beven II JL (2012) Tropical cyclone report: Hurricane Sandy (AL182012), 22–29, Technical report. National Hurricane Center, Miami, FL, USA, p 2013Google Scholar
  10. Bruns A, Burgess J (2014) Crisis communication in natural disasters : the queensland floods and christchurch earthquakes. In: Weller K, Bruns A, Burgess J, Mahrt M, Puschmann C (eds) Twitter and society, digital formations. Peter Lang, New York, pp 373–384Google Scholar
  11. Castillo C, Mendoza M, Poblete B (2011) Information credibility on Twitter. In: Proceedings of the 20th international conference on world wide web, WWW’11, New York, NY, USA, ACM, pp 675–684Google Scholar
  12. Clifton B (2012) Advanced web metrics with Google analytics, 3rd edn. Wiley, Hoboken, NJGoogle Scholar
  13. De Wever B, Schellens T, Valcke M, Van Keer H (2006) Content analysis schemes to analyze transcripts of online asynchronous discussion groups: a review. Comput Educ 46(1):6–28CrossRefGoogle Scholar
  14. di Tada N, Large T (2010) Information system to assist survivors of disasters. In: 2010 4th IEEE international conference on digital ecosystems and technologies (DEST), pp 354–359Google Scholar
  15. Fraustino JD, Liu B, Jin Y (2012) Social media use during disasters: a review of the knowledge base and gaps. Technical report, National Consortium for the Study of Terrorism and Responses to Terrorism [START]Google Scholar
  16. Friggeri A, Adamic LA, Eckles D, Cheng J (2014) Rumor cascades. In: Proceedings of the 8th international conference on weblogs and social media, pp 101–110Google Scholar
  17. Gupta A, Kumaraguru P (2012) Credibility ranking of tweets during high impact events. In: Proceedings of the 1st workshop on privacy and security in online social media, PSOSM’12, New York, NY, USA, ACM, pp 2:2–2:8Google Scholar
  18. Ha S, Ahn JH (2011) Why are you sharing others tweets?: The impact of argument quality and source credibility on information sharing behavior. In: ICIS 2011 ProceedingsGoogle Scholar
  19. Houston JB, Hawthorne J, Perreault MF, Park EH, Hode MG, Halliwell MR, Turner McGowen SE, Davis R, Vaid S, McElderry JA, Griffith SA (2015) Social media and disasters: a functional framework for social media use in disaster planning, response, and research. Disasters 39(1):1–22CrossRefGoogle Scholar
  20. Huang C-M, Chan E, Hyder AA (2010) Web 2.0 and internet social networking: a new tool for disaster management?—lessons from Taiwan. BMC Med Inf Decis Mak 10(1):1–5CrossRefGoogle Scholar
  21. Huberman BA, Romero DM, Wu F (2009) Social networks that matter: twitter under the microscope. First Monday 4(1).
  22. Humanity Road (2012) [image] from goes-east satellite on Oct. 25.
  23. Jaeger PT, Shneiderman B, Fleischmann KR, Preece J, Yan Q, Philip Fei W (2007) Community response grids: e-government, social networks, and effective emergency management. Telecommun Policy 31(1011):592–604CrossRefGoogle Scholar
  24. Kostka J, Oswald YA, Wattenhofer R (2008) Word of mouth: rumor dissemination in social networks. In: Shvartsman AA, Felber P (eds) Structural information and communication complexity. Springer, Berlin, pp 185–196CrossRefGoogle Scholar
  25. Li H, Sakamoto Y (2015) Re-tweet count matters: social influences on sharing of disaster-related tweets. J Homel Secur Emerg Manag 12(3):737–761Google Scholar
  26. Lindsay BR (2011) Social media and disasters: current uses, future options, and policy considerations. Technical report, Washington, DC, USAGoogle Scholar
  27. Lundgren RE, McMakin AH (2013) Risk communication: a handbook for communicating environmental, safety, and health risks, 5th edn. IEEE, Piscataway, NJCrossRefGoogle Scholar
  28. McCarthy JF, Boyd DM (2005) Digital backchannels in shared physical spaces: experiences at an academic conference. In: CHI’05 extended abstracts on human factors in computing systems, CHI EA’05, New York, NY, USA, ACM, pp 1641–1644Google Scholar
  29. Muralidharan S, Rasmussen L, Patterson D, Shin J-H (2011) Hope for Haiti: an analysis of Facebook and Twitter usage during the earthquake relief efforts. Public Relat Rev 37(2):175–177CrossRefGoogle Scholar
  30. (1979) Comprehensive emergency management: a governor’s guide. Department of Defense, Defense Civil Preparedness Agency, WashingtonGoogle Scholar
  31. Neuendorf KA (1990) Qualitative evaluation and research methods, 2nd edn. SAGE, Newbury ParkGoogle Scholar
  32. Neuendorf KA (2002) The content analysis guidebook. Sage, Thousand OaksGoogle Scholar
  33. Okada A, Ogura K (2014) Japanese disaster management system: recent developments in information flow and chains of command. J Conting Crisis Manag 22(1):58–62CrossRefGoogle Scholar
  34. Parmenter D (2015) Key performance indicators: developing, implementing, and using winning KPIs, 3rd edn. Wiley, Hoboken, NJCrossRefGoogle Scholar
  35. Rimstad R, Njå O, Rake EL, Braut GS (2014) Incident command and information flows in a large-scale emergency operation. J Conting Crisis Manag 22(1):29–38CrossRefGoogle Scholar
  36. Robinson CD, Brown DE (2005) First responder information flow simulation: a tool for technology assessment. In: Proceedings of the 37th conference on winter simulation, winter simulation conference, WSC ’05, pp 919–925Google Scholar
  37. Rourke L, Anderson T (2004) Validity in quantitative content analysis. Educ Technol Res Develop 52(1):5–18CrossRefGoogle Scholar
  38. Sena A, Corvalan C, Ebi K (2014) Climate change, extreme weather and climate events, and health impacts. In: Freedman B (ed) Global environmental change. Springer Netherlands, Dordrecht, pp 605–613Google Scholar
  39. Shan L, Regan A, De Brun A, Barnett J, van der Sanden MCA, Wall P, McConnon A (2014) Food crisis coverage by social and traditional media: a case study of the 2008 Irish dioxin crisis. Public Underst Sci 23(8):911–928CrossRefGoogle Scholar
  40. Shuai X, Ding Y, Busemeyer J (2012) Multiple spreaders affect the indirect influence on Twitter. In: Proceedings of the 21st international conference on world wide web, WWW’12 Companion, New York, NY, USA, ACM, pp 597–598Google Scholar
  41. Spence PR, Lachlan KA, Lin X, del Greco M (2015) Variability in twitter content across the stages of a natural disaster: implications for crisis communication. Commun Q 63(2):171–186CrossRefGoogle Scholar
  42. Takahashi B, Tandoc EC Jr, Carmichael C (2015) Communicating on Twitter during a disaster: an analysis of tweets during typhoon Haiyan in the Philippines. Comput Human Behav 50:392–398CrossRefGoogle Scholar
  43. Twitter Help Center (2017a) FAQs about retweets (RT).
  44. Twitter Help Center (2017b) What are replies and mentions?
  45. Twitter Support Center (2017) Tweet activity dashboard.
  46. Vieweg S, Hughes AL, Starbird K, Palen L (2010) Microblogging during two natural hazards events: what twitter may contribute to situational awareness. In: Proceedings of the SIGCHI conference on human hactors in computing systems, ACM, pp 1079–1088Google Scholar
  47. White C, Plotnick L, Kushma J, Hiltz SR, Turoff M (2009) An online social network for emergency management. Int J Emerg Manag 6(3–4):369–382CrossRefGoogle Scholar
  48. Williams R, Williams G, Burton D (2012) The use of social media for disaster recovery. University of Missouri Extension, JoplinGoogle Scholar
  49. Yates D, Paquette S (2011) Emergency knowledge management and social media technologies: a case study of the 2010 Haitian earthquake. Int J Inf Manag 31(1):6–13CrossRefGoogle Scholar
  50. Yuan W, Guan D, Huh E-N, Lee S (2013) Harness human sensor networks for situational awareness in disaster reliefs: a survey. IETE Tech Rev 30(3):240–247CrossRefGoogle Scholar
  51. Zhang G, Yang Y, Mao X (2011) Disaster recovery evaluation PROC model framework based on information flow. In: IEEE 2011 International conference on computer science and network technology (ICCSNT), vol 3. pp 1841–1845Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  1. 1.Department of Industrial and Systems EngineeringUniversity at BuffaloBuffaloUSA

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