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Traditional and Social Media Coverage and Charitable Giving Following the 2010 Earthquake in Haiti

Published online by Cambridge University Press:  05 July 2012

Ano Lobb ,
Nancy Mock  and
Paul L. Hutchinson
Ano Lobb*
Affiliation:
Master of Health Care Delivery Science Program, Dartmouth College, Hanover, New Hampshire USA
Nancy Mock
Affiliation:
Department of Global Health Systems and Development, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana USA
Paul L. Hutchinson
Affiliation:
Department of Global Health Systems and Development, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana USA
*
Correspondence: Ano Lobb, MPH 80 Lepage Road Barre, Vermont 05641 USA E-mail ano.lobb@gmail.com
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Abstract

Introduction

Media reports on disasters may play a role in inspiring charitable giving to fund post-disaster recovery, but few analyses have attempted to explore the potential link between the intensity of media reporting and the amount of charitable donations made. The purposes of this study were to explore media coverage during the first four weeks of the 2010 earthquake in Haiti in order to assess changes in media-intensity, and to link this information to data on contributions for emergency assistance to determine the impact of media upon post-disaster charitable giving.

Methods

Data on newspaper and newswire coverage of the 2010 earthquake in Haiti were gathered from the NexisLexis database, and traffic on Twitter and select Facebook sites was gathered from social media analyzers. The aggregated measure of charitable giving was gathered from the Center for Philanthropy at Indiana University. The intensity of media reporting was compared with charitable giving over time for the first month following the event, using regression modeling.

Results

Post-disaster coverage in traditional media and Twitter was characterized by a rapid rise in the first few days following the event, followed by a gradual but consistent decline over the next four weeks. Select Facebook sites provided more sustained coverage. Both traditional and new media coverage were positively correlated with donations: every 10% increase in Twitter messages relative to the peak percentage was associated with an additional US $236,540 in contributions, while each additional ABC News story was associated with an additional US $963,800 in contributions.

Conclusions

While traditional and new media coverage wanes quickly after disaster-causing events, new and social media platforms may allow stories, and potentially charitable giving, to thrive for longer periods of time.

Lobb A, Mock N, Hutchinson PL. Traditional and social media coverage and charitable giving following the 2010 earthquake in Haiti. Prehosp Disaster Med. 2012; 27(4):1-6.

Keywords

charitable donationsdisastersearthquakeHaitinews coveragenews mediasocial media
Type
Original Research
Information
Prehospital and Disaster Medicine , Volume 27 , Issue 4 , August 2012 , pp. 319 - 324
Copyright
Copyright © World Association for Disaster and Emergency Medicine 2012

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References

1. Network for Good. Impulse on the Internet: how crisis compels donors to give on the Internet. http://www.networkforgood.org/downloads/pdf/Whitepaper/20061009_crisis_compels_donors.pdf. Accessed February 13, 2010.Google Scholar
2. Brown, PH, Minty, JH. Media coverage and charitable giving after the 2004 tsunami. Southern Economic Journal. 2008;75(1):9-25.CrossRefGoogle Scholar
3. Grilli, R, Ramsay, C, Minozzi, S. Mass media interventions: effects on health services utilisation. Cochrane Database Syst Rev. 2002; 1 Art. No.CD000389.CrossRefGoogle Scholar
4. Danovaro-Holliday, MC, Wood, AL, LeBaron, CW. Rotavirus vaccine and the news media, 1987-2001. JAMA. 2002;287(11):1455-1462.CrossRefGoogle ScholarPubMed
5. Mason, BW, Donnelly, PD. Impact of a local newspaper campaign on the uptake of the measles mumps and rubella vaccine. J Epidemiol Community Health. 2000;54(6):473-474.Google Scholar
6. Petty, RE, Cacioppo, JT. Communication and Persuasion: Central and Peripheral Routes to Attitude Change. New York, NY, USA: Springer-Verlag; 1986.Google Scholar
7. Social Media for Life Sciences: Trick or Tweet? In: Deloitte Debates. 2010. http://www.deloitte.com/assets/Dcom-UnitedStates/Local%20Assets/Documents/us_consulting_TrickorTweet_021910.pdf. Accessed November 21, 2010.Google Scholar
8. Lobb, A, Mock, N. Dialogue is destiny: Managing the message in humanitarian action. Prehosp Disaster Med. 2007;22(5):425-430.CrossRefGoogle ScholarPubMed
9. Voorhees, CCW, Vick, J, Perkins, DD. ‘Came Hell and High Water’: The Intersection of Hurricane Katrina, the News Media, Race and Poverty. Journal of Community & Applied Social Psychology. 2007;17(6):415-429.CrossRefGoogle Scholar
10. Sherlock, MF. Charitable contributions for Haiti's earthquake victims. In: Congressional Research Service Report R41036. 2010. http://www.fas.org/sgp/crs/misc/R41036.pdf. Accessed April 14, 2010.Google Scholar
11. Lütkepohl, H. New Introduction to Multiple Time Series Analysis. New York, NY, USA: Springer; 2005.Google Scholar
12. Granger, CWJ. Investigating causal relations by econometric models and cross-sectral methods. Econometrica. 1969;37(3):424-438.Google Scholar
13. Proudlock, K, Ramalingam, B. Don't Chase Headlines, Chase Good Quality News … Don't Be First, Be Accountable. In: A New Agenda for News Media and Humanitarian Aid. Report of the 23rd ALNAP Biannual Meeting 4th June 2008, Madrid. Active Learning Network for Accountability and Performance in Humanitarian Action. http://www.alnap.org/pool/files/23_media.pdf. Accessed June 28, 2010.Google Scholar
14. Chew, C, Eysenbach, G. Pandemics in the age of Twitter: content analysis of Tweets during the 2009 H1N1 outbreak. PLoS One. 2010;5(11):e14118.Google Scholar
15. Internet 2010 in numbers. 2011. http://royal.pingdom.com/2011/01/12/internet-2010-in-numbers/. Accessed January 15, 2011.Google Scholar
16. Smith, A, Rainie, L. 8% of Online Americans use Twitter. 2010. Pew Internet and American Life Web site. http://pewinternet.org/Reports/2010/Twitter-update-2010.aspx. Accessed December 20, 2011.Google Scholar
17. Smith, A. Mobile Access 2010. Pew Internet and American Life Web site. http://pewinternet.org/Reports/2010/Mobile-Access-2010.aspx. Accessed July 10, 2010.Google Scholar
18. Facebook statistics. http://www.facebook.com/press/info.php?statistics. Accessed February 14, 2011.Google Scholar