Abstract
During humanitarian crises, people face dangers and need a large amount of information in a short period of time. Such need creates the base for misinformation such as rumors, fake news or hoaxes to spread within and outside the affected community. It could be unintended misinformation with unconfirmed details, or intentional disinformation created to trick people for benefits. It results in information harms that can generate serious short term or long-term consequences. Although some researchers have created misinformation detection systems and algorithms, examined the roles of involved parties, examined the way misinformation spreads and convinces people, very little attention has been paid to the types of misinformation harms. In the context of humanitarian crises, we propose a taxonomy of information harms and assess people’s perception of risk regarding the harms. Such a taxonomy can act as the base for future research to quantitatively measure the harms in specific contexts. Furthermore, perceptions of related people were also investigated in four specifically chosen scenarios through two dimensions: Likelihood of occurrence and Level of impacts of the harms.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Agrafiotis, I., Nurse, J.R., Goldsmith, M., Creese, S., Upton, D.: A taxonomy of cyber-harms: defining the impacts of cyber-attacks and understanding how they propagate. J. Cybersecur. 4, tyy006, 1–15 (2018)
Alexander, K.: What caused nearly 20,000 quakes at Oroville Dam? Scientists weigh in on mystery (2018). https://www.sfchronicle.com/news/article/What-caused-nearly-20-000-quakes-at-Oroville-Dam-13473254.php. Accessed 25 Aug 2019
Berman, M.: Risk assessments 101: the role of probability & impact in measuring risk (2018). https://ncontracts.com/articles/risk-assessments-101-the-role-of-probability-impact-in-measuring-risk/. Accessed 01 Sept 2019
Bostrom, N.: Information hazards: a typology of potential harms from knowledge. Rev. Contemporary Philosophy 10, 44–79 (2011). http://search.proquest.com/docview/920893069/. Accessed 01 July 2019
Buhrmester, D.M., Kwang, N.T., Gosling, D.S.: Amazon’s mechanical turk: a new source of inexpensive, yet high-quality, data? Perspect. Psychol. Sci. 6(1), 3–5 (2011). https://doi.org/10.1177/1745691610393980
Casler, K., Bickel, L., Hackett, E.E.: Separate but equal? A comparison of participants and data gathered via Amazon’s MTurk, social media, and face-to-face behavioral testing. Comput. Hum. Behav. 29(6), 2156–2160 (2013)
Cheung, H.J., Burns, K.D., Sinclair, R., Sliter, M.: Amazon mechanical turk in organizational psychology: an evaluation and practical recommendations. J. Bus. Psychol. 32(4), 347–361 (2017). https://doi.org/10.1007/s10869-016-9458-5
Chokshi, N., McPHate, M.: Flood risk near Oroville Dam causes thousands to evacuate in California (2017). https://www.nytimes.com/2017/02/12/us/california-oroville-dam-spillway-evacuate.html. Accessed 25 Aug 2019
Curtis, P., Carey, M.: Risk Assessment in Practice. Thought leadership in ERM. By Deloitte & Touche LLP, and COSO (Committee of Sponsoring Organizations of the Treadway Commission) (2012). https://www2.deloitte.com/content/dam/Deloitte/global/Documents/Governance-Risk-Compliance/dttl-grc-riskassessmentinpractice.pdf. Accessed 27 Aug 2019
Elliott, D.: Concept unwrapped – causing harms. Copyright © 2019 ethics unwrapped - McCombs School of Business – The University of Texas at Austin (2019). https://ethicsunwrapped.utexas.edu/video/causing-harm. Accessed 15 Feb 2019
FTC Informational Injury Workshop Report. FTC staff perspective (2018). https://www.ftc.gov/system/files/documents/reports/ftc-informational-injury-workshop-be-bcp-staff-perspective/inform’ational_injury_workshop_staff_report_-_oct_2018_0.pdf. Accessed 20 Apr 2019
Ghenai, A., Mejova, Y.: Catching zika fever: application of crowdsourcing and machine learning for tracking health misinformation on Twitter. arXiv.org (2017)
Gupta, A., Lamba, H., Kumaraguru, P., Joshi, A.: Faking Sandy: characterizing and identifying fake images on Twitter during Hurricane Sandy. In: Proceedings of the 22nd International Conference on World Wide Web (WWW 2013 Companion), pp. 729–736. ACM, New York (2013)
Heen, M.S., Lieberman, J.D., Miethe, T.D.: A comparison of different online sampling approaches for generating national samples. UNLV – Center Crime Justice Policy 1, 1–8 (2014). Research In Brief. September 2014, CCJP 2014-01
Holdeman, E.: BLOG: disaster zone: how to counter fake news during a disaster. TCA Regional News, Chicago, 27 February 2018
Homeland Security Report. Countering false information on social media in disasters and emergencies. Department of Homeland Security – Science and Technology (2018). https://www.dhs.gov/sites/default/files/publications/SMWG_Countering-False-Info-Social-Media-Disasters-Emergencies_Mar2018-508.pdf. Accessed 20 Apr 2019
Human Coalition. What is a humanitarian emergency? (2018). https://www.humanitariancoalition.ca/info-portal/factsheets/what-is-a-humanitarian-crisis. Accessed 07 Dec 2018
Maddock, J., Starbird, K., Al-Hassani, H., Sandoval, D., Orand, M., Mason, R.: Characterizing online rumoring behavior using multi-dimensional signatures. In: Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing, pp. 228–241. ACM (2015)
Madrigal, C.A.: #BostonBombing: the anatomy of a misinformation disaster (2013). https://www.theatlantic.com/technology/archive/2013/04/-bostonbombing-the-anatomy-of-a-misinformation-disaster/275155/. Accessed 14 June 2019
Majima, Y., Nishiyama, K., Nishihara, A., Hata, R.: Conducting online behavioral research using crowdsourcing services in Japan. Front. Psychol. 8 (2017) https://doi.org/10.3389/fpsyg.2017.00378
McNamara, A.: Facebook announces plan to combat anti-vaccine misinformation (2019). https://www.thedailybeast.com/facebook-announces-plan-to-combat-vaccine-misinformation. Accessed 14 June 2019
Miller, C.A.: Viral misinformation: rise of ‘anti-vaxxer’ movement requires news literacy inoculation. USA Today (2019). https://www.usatoday.com/story/opinion/2019/05/03/measles-spread-viral-anti-vaxxer-misinformation-internet-literacy-news-column/3650914002/. Accessed 14 June 2019
Nealon: False tweets during Harvey, Irma under scrutiny by University at Buffalo Researchers. US Fed News Service, Including US State News, Washington, D.C, 29 September 2017. http://www.buffalo.edu/news/releases/2017/09/044.html. Accessed 15 Feb 2019
Newton, C.: Instagram will begin blocking hashtags that return anti-vaccination misinformation (2019). https://www.theverge.com/2019/5/9/18553821/instagram-anti-vax-vaccines-hashtag-blocking-misinformation-hoaxes. Accessed 14 June
Oh, O., Agrawal, M., Rao, H.: Community intelligence and social media services: a rumor theoretic analysis of tweets during social crises. MIS Q. 37(2), 407–426 (2013)
Ohlhausen, M.K.: Informational injury in FTC privacy and data security cases, 19 September 2017. https://www.ftc.gov/system/files/documents/public_statements/1255113/privacy_speech_mkohlhausen.pdf. Accessed 15 Feb 2019
Pang, N., Ng, J.: Misinformation in a riot: a two-step flow view. Online Inf. Rev. 41(4), 438–453 (2017)
Peretti-Watel, P., Raude, J., Sagaon-Teyssier, L., Constant, A., Verger, P., Beck, F.: Attitudes toward vaccination and the H1N1 vaccine: poor people’s unfounded fears or legitimate concerns of the elite? Soc. Sci. Med. 109, 10–18 (2014)
Rajdev, M., Lee, K.: Fake and spam messages: detecting misinformation during natural disasters on social media. In: 2015 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), vol. 1, pp. 17–20. IEEE (2015)
Rogers, P.: Oroville Dam: Designer of failed spillway had almost no experience (2018). https://www.mercurynews.com/2018/01/05/oroville-dam-new-report-details-what-caused-the-near-disaster-last-year/. Accessed 25 Aug 2019
Sandvik, K., Jacobsen, K., McDonald, S.: Do no harm: a taxonomy of the challenges of humanitarian experimentation, 99(904), 319–344 (2017). https://doi.org/10.1017/S181638311700042X
Sheehan, B.K.: Crowdsourcing research: data collection with Amazon’s Mechanical Turk. Commun. Monogr. 85(1), 140–156 (2018). https://doi.org/10.1080/03637751.2017.1342043
Shih, G.: Boston marathon bombings: how Twitter and Reddit got it wrong (2013). https://www.independent.co.uk/news/world/americas/boston-marathon-bombings-how-twitter-and-reddit-got-it-wrong-8581167.html. Accessed 14 June
Speri, A.: FEMA Is Trying To Get Back $5.8M in Hurricane Sandy Aid Money (2014). https://news.vice.com/en_us/article/pa885v/fema-is-trying-to-get-back-58m-in-hurricane-sandy-aid-money. Accessed 15 Feb 2019
Starbird, K., Maddock, J., Orand, M., Achterman, P., Mason, R.M.: Rumors, false flags, and digital vigilantes: misinformation on Twitter after the 2013 Boston marathon bombing. In: iConference 2014 Proceedings, pp. 654–662 (2014). https://doi.org/10.9776/14308
Wardle, C., Derakhshan, H.: Information disorder: toward an interdisciplinary framework for research and policy making. Council of Europe report. DGI, September 2017
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Tran, T., Valecha, R., Rad, P., Rao, H.R. (2020). An Investigation of Misinformation Harms Related to Social Media During Humanitarian Crises. In: Sahay, S., Goel, N., Patil, V., Jadliwala, M. (eds) Secure Knowledge Management In Artificial Intelligence Era. SKM 2019. Communications in Computer and Information Science, vol 1186. Springer, Singapore. https://doi.org/10.1007/978-981-15-3817-9_10
Download citation
DOI: https://doi.org/10.1007/978-981-15-3817-9_10
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-3816-2
Online ISBN: 978-981-15-3817-9
eBook Packages: Computer ScienceComputer Science (R0)