Advertisement

Springer Nature is making Coronavirus research free. View research | View latest news | Sign up for updates

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

Abstract

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.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

References

  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 449–454

  2. Acar A, Muraki Y (2011) Twitter for crisis communication: lessons learned from Japan’s tsunami disaster. Int J Web Based Communities 7(3):392–402

  3. Alexander DE (2014) Social media in disaster risk reduction and crisis management. Sci Eng Ethics 20(3):717–733

  4. Al-Saggaf Y, Simmons P (2015) Social media in Saudi Arabia: exploring its use during two natural disasters. Technol Forecast Soc Chang 95:3–15

  5. Barabási A-L (2009) Scale-free networks: a decade and beyond. Science 325(5939):412–413

  6. Barbier G, Zafarani R, Gao H, Fung G, Liu H (2012) Maximizing benefits from crowdsourced data. Comput Math Organ Theory 18(3):257–279

  7. Berg BL, Lune H, Lune H (2004) Qualitative research methods for the social sciences, 5th edn. Pearson, Boston

  8. Berger J, Milkman KL (2012) What makes online content viral? J Mark Res 49(2):192–205

  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 2013

  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 373–384

  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 675–684

  12. Clifton B (2012) Advanced web metrics with Google analytics, 3rd edn. Wiley, Hoboken, NJ

  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):6–28

  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 354–359

  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]

  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 101–110

  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 2:2–2:8

  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 Proceedings

  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):1–22

  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):1–5

  21. Huberman BA, Romero DM, Wu F (2009) Social networks that matter: twitter under the microscope. First Monday 4(1). http://rstmonday.org/ojs/index.php/fm/article/view/2317/2063

  22. Humanity Road (2012) [image] from goes-east satellite on Oct. 25. https://twitter.com/HumanityRoad/status/261479343308537856

  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):592–604

  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 185–196

  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):737–761

  26. Lindsay BR (2011) Social media and disasters: current uses, future options, and policy considerations. Technical report, Washington, DC, USA

  27. Lundgren RE, McMakin AH (2013) Risk communication: a handbook for communicating environmental, safety, and health risks, 5th edn. IEEE, Piscataway, NJ

  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 1641–1644

  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):175–177

  30. (1979) Comprehensive emergency management: a governor’s guide. Department of Defense, Defense Civil Preparedness Agency, Washington

  31. Neuendorf KA (1990) Qualitative evaluation and research methods, 2nd edn. SAGE, Newbury Park

  32. Neuendorf KA (2002) The content analysis guidebook. Sage, Thousand Oaks

  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):58–62

  34. Parmenter D (2015) Key performance indicators: developing, implementing, and using winning KPIs, 3rd edn. Wiley, Hoboken, NJ

  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):29–38

  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 919–925

  37. Rourke L, Anderson T (2004) Validity in quantitative content analysis. Educ Technol Res Develop 52(1):5–18

  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 605–613

  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):911–928

  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 597–598

  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):171–186

  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 50:392–398

  43. Twitter Help Center (2017a) FAQs about retweets (RT). https://support.twitter.com/articles/77606

  44. Twitter Help Center (2017b) What are replies and mentions? https://support.twitter.com/articles/14023

  45. Twitter Support Center (2017) Tweet activity dashboard. https://support.twitter.com/articles/20171990

  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 1079–1088

  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):369–382

  48. Williams R, Williams G, Burton D (2012) The use of social media for disaster recovery. University of Missouri Extension, Joplin

  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):6–13

  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):240–247

  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 1841–1845

Download references

Author information

Correspondence to Jun Zhuang.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Wang, B., Zhuang, J. Crisis information distribution on Twitter: a content analysis of tweets during Hurricane Sandy. Nat Hazards 89, 161–181 (2017). https://doi.org/10.1007/s11069-017-2960-x

Download citation

Keywords

  • Crisis communication
  • Social media
  • Hurricane Sandy
  • Content analysis