IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v103y2020i1d10.1007_s11069-020-04024-6.html
   My bibliography  Save this article

Dietary pattern recognition on Twitter: a case example of before, during, and after four natural disasters

Author

Listed:
  • Gabrielle Turner-McGrievy

    (University of South Carolina)

  • Amir Karami

    (University of South Carolina)

  • Courtney Monroe

    (University of South Carolina)

  • Heather M. Brandt

    (University of South Carolina)

Abstract

Little is known about what foods/beverages (F&B) are common during natural disasters. The goal of this study was to track high-frequency F&B mentions during four hurricanes affecting the coast of South Carolina for quantifying dietary patterns in Twitter. A listing of common F&B (n = 173) was created from the top food sources of energy, fat, protein, and carbohydrate in the USA. A sampling of > 500,000 tweets containing hashtag names (e.g., #HurricaneFlorence) or actual names (e.g., “Hurricane Florence”) of the four hurricanes was collected using Crimson Hexagon. ANOVA was used to examine differences in number of mentions in each food group pre- (6 days before), during (48 h of the hurricane), and post-hurricane (6 days after). Descriptive statistics were used to examine the most frequently mentioned F&B (threshold defined as ≥ 4 mentions/day for each F&B item or 10% of the foods mentioned) and whether F&B were top sources of energy/macronutrients. More than 5000 mentions of F&B were collected in our sample. Grains were the most frequently mentioned food group pre-hurricane, and dairy was most frequently mentioned during the hurricanes. The top five most commonly mentioned F&B overall were milk (n = 517), pizza (n = 511), turkey (n = 425), oranges (n = 384), and waffles (n = 346). Foods mentioned were commonly energy and protein dense. Five foods (pizza, waffles, milk, rolls, and bread) were categorized as a top contributor across energy and all three macronutrients. Social media may be a unique way to detect dietary patterns and help inform public health social media campaigns to advise people about stocking up on healthy, non-perishable foods ahead of natural disasters.

Suggested Citation

  • Gabrielle Turner-McGrievy & Amir Karami & Courtney Monroe & Heather M. Brandt, 2020. "Dietary pattern recognition on Twitter: a case example of before, during, and after four natural disasters," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(1), pages 1035-1049, August.
  • Handle: RePEc:spr:nathaz:v:103:y:2020:i:1:d:10.1007_s11069-020-04024-6
    DOI: 10.1007/s11069-020-04024-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-020-04024-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11069-020-04024-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Bairong Wang & Jun Zhuang, 2018. "Rumor response, debunking response, and decision makings of misinformed Twitter users during disasters," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 93(3), pages 1145-1162, September.
    2. Yu Xiao & Qunying Huang & Kai Wu, 2015. "Understanding social media data for disaster management," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 79(3), pages 1663-1679, December.
    3. Bairong Wang & Jun Zhuang, 2017. "Crisis information distribution on Twitter: a content analysis of tweets during Hurricane Sandy," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 89(1), pages 161-181, October.
    4. Sinnenberg, L. & Buttenheim, A.M. & Padrez, K. & Mancheno, C. & Ungar, L. & Merchant, R.M., 2017. "Twitter as a tool for health research: A systematic review," American Journal of Public Health, American Public Health Association, vol. 107(1), pages 1-8.
    5. Zheye Wang & Xinyue Ye & Ming-Hsiang Tsou, 2016. "Spatial, temporal, and content analysis of Twitter for wildfire hazards," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(1), pages 523-540, August.
    6. Xiangyang Guan & Cynthia Chen, 2014. "Using social media data to understand and assess disasters," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 74(2), pages 837-850, November.
    7. repec:aph:ajpbhl:10.2105/ajph.2016.303512_4 is not listed on IDEAS
    8. Kathryn C. Finch & Kassandra R. Snook & Carmen H. Duke & King-Wa Fu & Zion Tsz Ho Tse & Atin Adhikari & Isaac Chun-Hai Fung, 2016. "Public health implications of social media use during natural disasters, environmental disasters, and other environmental concerns," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(1), pages 729-760, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Simandjuntak, Daniel P. & Jaenicke, Edward C. & Wrenn, Douglas H., 2022. "Heterogeneity in Consumer Food Stockpiling and Retailer Experiences During Hurricane Sandy," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322183, Agricultural and Applied Economics Association.
    2. Zhijie Sasha Dong & Lingyu Meng & Lauren Christenson & Lawrence Fulton, 2021. "Social media information sharing for natural disaster response," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 107(3), pages 2077-2104, July.
    3. Amir Karami & Morgan Lundy & Frank Webb & Gabrielle Turner-McGrievy & Brooke W. McKeever & Robert McKeever, 2021. "Identifying and Analyzing Health-Related Themes in Disinformation Shared by Conservative and Liberal Russian Trolls on Twitter," IJERPH, MDPI, vol. 18(4), pages 1-16, February.
    4. Huiyun Zhu & Kecheng Liu, 2021. "Temporal, Spatial, and Socioeconomic Dynamics in Social Media Thematic Emphases during Typhoon Mangkhut," Sustainability, MDPI, vol. 13(13), pages 1-17, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lida Huang & Panpan Shi & Haichao Zhu & Tao Chen, 2022. "Early detection of emergency events from social media: a new text clustering approach," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 111(1), pages 851-875, March.
    2. Rachel Samuels & John E. Taylor & Neda Mohammadi, 2020. "Silence of the Tweets: incorporating social media activity drop-offs into crisis detection," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(1), pages 1455-1477, August.
    3. Martínez-Rojas, María & Pardo-Ferreira, María del Carmen & Rubio-Romero, Juan Carlos, 2018. "Twitter as a tool for the management and analysis of emergency situations: A systematic literature review," International Journal of Information Management, Elsevier, vol. 43(C), pages 196-208.
    4. Yan Wang & John E. Taylor, 2018. "Coupling sentiment and human mobility in natural disasters: a Twitter-based study of the 2014 South Napa Earthquake," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 92(2), pages 907-925, June.
    5. Bevaola Kusumasari & Nias Phydra Aji Prabowo, 2020. "Scraping social media data for disaster communication: how the pattern of Twitter users affects disasters in Asia and the Pacific," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(3), pages 3415-3435, September.
    6. Alekh Gour & Shikha Aggarwal & Subodha Kumar, 2022. "Lending ears to unheard voices: An empirical analysis of user‐generated content on social media," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2457-2476, June.
    7. Ji-Wan Lee & Chung-Gil Jung & Jee-Hun Chung & Seong-Joon Kim, 2019. "The relationship among meteorological, agricultural, and in situ news-generated big data on droughts," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 98(2), pages 765-781, September.
    8. Sarah Gardiner & Jinyan Chen & Margarida Abreu Novais & Karine Dupré & J. Guy Castley, 2023. "Analyzing and Leveraging Social Media Disaster Communication of Natural Hazards: Community Sentiment and Messaging Regarding the Australian 2019/20 Bushfires," Societies, MDPI, vol. 13(6), pages 1-20, May.
    9. Wu, Chunying & Xiong, Xiong & Gao, Ya & Zhang, Jin, 2022. "Does social media distort price discovery? Evidence from rumor clarifications," Research in International Business and Finance, Elsevier, vol. 62(C).
    10. Faxi Yuan & Rui Liu, 2018. "Crowdsourcing for forensic disaster investigations: Hurricane Harvey case study," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 93(3), pages 1529-1546, September.
    11. Mingyun Gu & Haixiang Guo & Jun Zhuang & Yufei Du & Lijin Qian, 2022. "Social Media User Behavior and Emotions during Crisis Events," IJERPH, MDPI, vol. 19(9), pages 1-21, April.
    12. Umar Ali Bukar & Fatimah Sidi & Marzanah A. Jabar & Rozi Nor Haizan Nor & Salfarina Abdullah & Iskandar Ishak & Mustafa Alabadla & Ali Alkhalifah, 2022. "How Advanced Technological Approaches Are Reshaping Sustainable Social Media Crisis Management and Communication: A Systematic Review," Sustainability, MDPI, vol. 14(10), pages 1-26, May.
    13. Xiaoxue Cheng & Guifeng Han & Yifan Zhao & Lin Li, 2019. "Evaluating Social Media Response to Urban Flood Disaster: Case Study on an East Asian City (Wuhan, China)," Sustainability, MDPI, vol. 11(19), pages 1-18, September.
    14. Kyle Hunt & Bairong Wang & Jun Zhuang, 2020. "Misinformation debunking and cross-platform information sharing through Twitter during Hurricanes Harvey and Irma: a case study on shelters and ID checks," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(1), pages 861-883, August.
    15. Agarwal, Puneet & Aziz, Ridwan Al & Zhuang, Jun, 2022. "Interplay of rumor propagation and clarification on social media during crisis events - A game-theoretic approach," European Journal of Operational Research, Elsevier, vol. 298(2), pages 714-733.
    16. Bianca E. Lopez & Nicholas R. Magliocca & Andrew T. Crooks, 2019. "Challenges and Opportunities of Social Media Data for Socio-Environmental Systems Research," Land, MDPI, vol. 8(7), pages 1-18, July.
    17. Sungyoon Kim & Wanyun Shao & Jonghun Kam, 2019. "Spatiotemporal patterns of US drought awareness," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-9, December.
    18. Luis-Millán González & José Devís-Devís & Maite Pellicer-Chenoll & Miquel Pans & Alberto Pardo-Ibañez & Xavier García-Massó & Fernanda Peset & Fernanda Garzón-Farinós & Víctor Pérez-Samaniego, 2021. "The Impact of COVID-19 on Sport in Twitter: A Quantitative and Qualitative Content Analysis," IJERPH, MDPI, vol. 18(9), pages 1-20, April.
    19. Sandulika Abesinghe & Nayomi Kankanamge & Tan Yigitcanlar & Surabhi Pancholi, 2023. "Image of a City through Big Data Analytics: Colombo from the Lens of Geo-Coded Social Media Data," Future Internet, MDPI, vol. 15(1), pages 1-21, January.
    20. Yandong Wang & Teng Wang & Xinyue Ye & Jianqi Zhu & Jay Lee, 2015. "Using Social Media for Emergency Response and Urban Sustainability: A Case Study of the 2012 Beijing Rainstorm," Sustainability, MDPI, vol. 8(1), pages 1-17, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:nathaz:v:103:y:2020:i:1:d:10.1007_s11069-020-04024-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.