IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2307.01404.html
   My bibliography  Save this paper

Social media use among American Indians in South Dakota: Preferences and perceptions

Author

Listed:
  • Deepthi Kolady
  • Amrit Dumre
  • Weiwei Zhang
  • Kaiqun Fu
  • Marcia O'Leary
  • Laura Rose

Abstract

Social media use data is widely being used in health, psychology, and marketing research to analyze human behavior. However, we have very limited knowledge on social media use among American Indians. In this context, this study was designed to assess preferences and perceptions of social media use among American Indians during COVID-19. We collected data from American Indians in South Dakota using online survey. Results show that Facebook, YouTube, TikTok, Instagram and Snapchat are the most preferred social media platforms. Most of the participants reported that the use of social media increased tremendously during COVID-19 and had perceptions of more negative effects than positive effects. Hate/harassment/extremism, misinformation/made up news, and people getting one point of view were the top reasons for negative effects.

Suggested Citation

  • Deepthi Kolady & Amrit Dumre & Weiwei Zhang & Kaiqun Fu & Marcia O'Leary & Laura Rose, 2023. "Social media use among American Indians in South Dakota: Preferences and perceptions," Papers 2307.01404, arXiv.org.
    • Handle: RePEc:arx:papers:2307.01404
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2307.01404
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yates, Dave & Paquette, Scott, 2011. "Emergency knowledge management and social media technologies: A case study of the 2010 Haitian earthquake," International Journal of Information Management, Elsevier, vol. 31(1), pages 6-13.
    2. David A Broniatowski & Michael J Paul & Mark Dredze, 2013. "National and Local Influenza Surveillance through Twitter: An Analysis of the 2012-2013 Influenza Epidemic," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-1, December.
    Full references (including those not matched with items on IDEAS)

    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. Hyekyung Woo & Youngtae Cho & Eunyoung Shim & Kihwang Lee & Gilyoung Song, 2015. "Public Trauma after the Sewol Ferry Disaster: The Role of Social Media in Understanding the Public Mood," IJERPH, MDPI, vol. 12(9), pages 1-10, September.
    2. HeeChel Kim & Hong-Woo Chun & Seonho Kim & Byoung-Youl Coh & Oh-Jin Kwon & Yeong-Ho Moon, 2017. "Longitudinal Study-Based Dementia Prediction for Public Health," IJERPH, MDPI, vol. 14(9), pages 1-16, August.
    3. Deborah Kanda & Jingjing Yin & Xinyan Zhang & Hani Samawi, 2025. "Efficient regression analyses with zero-augmented models based on ranking," Computational Statistics, Springer, vol. 40(2), pages 601-632, February.
    4. Paolo BRUNORI & Giuliano RESCE, 2020. "Searching for the peak Google Trends and the Covid-19 outbreak in Italy," Working Papers - Economics wp2020_05.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    5. Fernando Arias & Ariel Guerra-Adames & Maytee Zambrano & Efraín Quintero-Guerra & Nathalia Tejedor-Flores, 2022. "Analyzing Spanish-Language Public Sentiment in the Context of a Pandemic and Social Unrest: The Panama Case," IJERPH, MDPI, vol. 19(16), pages 1-19, August.
    6. Fantazzini, Dean, 2020. "Short-term forecasting of the COVID-19 pandemic using Google Trends data: Evidence from 158 countries," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 59, pages 33-54.
    7. Ira Puspitasari & Alia Firdauzy, 2019. "Characterizing Consumer Behavior in Leveraging Social Media for E-Patient and Health-Related Activities," IJERPH, MDPI, vol. 16(18), pages 1-17, September.
    8. David A. Broniatowski, 2018. "Building the tower without climbing it: Progress in engineering systems," Systems Engineering, John Wiley & Sons, vol. 21(3), pages 259-281, May.
    9. Muhammad Ashraf Fauzi, 2023. "Social media in disaster management: review of the literature and future trends through bibliometric analysis," 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. 118(2), pages 953-975, September.
    10. Ni, Zi-jian & Rong, Lili & Wang, Ning & Cao, Shuo, 2019. "Knowledge model for emergency response based on contingency planning system of China," International Journal of Information Management, Elsevier, vol. 46(C), pages 10-22.
    11. Zhao, Dingtao & Wang, Feng & Wei, Jiuchang & Liang, Liang, 2013. "Public reaction to information release for crisis discourse by organization: Integration of online comments," International Journal of Information Management, Elsevier, vol. 33(3), pages 485-495.
    12. S M Nadim Sultan & Keshav Lall Maharjan, 2022. "Cyclone-Induced Disaster Loss Reduction by Social Media: A Case Study on Cyclone Amphan in Koyra Upazila, Khulna District, Bangladesh," Sustainability, MDPI, vol. 14(21), pages 1-17, October.
    13. Samuel V Scarpino & James G Scott & Rosalind M Eggo & Bruce Clements & Nedialko B Dimitrov & Lauren Ancel Meyers, 2020. "Socioeconomic bias in influenza surveillance," PLOS Computational Biology, Public Library of Science, vol. 16(7), pages 1-19, July.
    14. Hongying Dai & Brian R. Lee & Jianqiang Hao, 2017. "Predicting Asthma Prevalence by Linking Social Media Data and Traditional Surveys," The ANNALS of the American Academy of Political and Social Science, , vol. 669(1), pages 75-92, January.
    15. Zeynep Ertem & Dorrie Raymond & Lauren Ancel Meyers, 2018. "Optimal multi-source forecasting of seasonal influenza," PLOS Computational Biology, Public Library of Science, vol. 14(9), pages 1-16, September.
    16. Kim, Jooho & Hastak, Makarand, 2018. "Social network analysis: Characteristics of online social networks after a disaster," International Journal of Information Management, Elsevier, vol. 38(1), pages 86-96.
    17. Jose L Herrera & Ravi Srinivasan & John S Brownstein & Alison P Galvani & Lauren Ancel Meyers, 2016. "Disease Surveillance on Complex Social Networks," PLOS Computational Biology, Public Library of Science, vol. 12(7), pages 1-16, July.
    18. Ibrahim Musa & Hyun Woo Park & Lkhagvadorj Munkhdalai & Keun Ho Ryu, 2018. "Global Research on Syndromic Surveillance from 1993 to 2017: Bibliometric Analysis and Visualization," Sustainability, MDPI, vol. 10(10), pages 1-20, September.
    19. Muhammad Imran & Umair Qazi & Ferda Ofli, 2022. "TBCOV: Two Billion Multilingual COVID-19 Tweets with Sentiment, Entity, Geo, and Gender Labels," Data, MDPI, vol. 7(1), pages 1-27, January.
    20. Siqing Shan & Tenglong Xin & Li Wang & You Li & Ling Li, 2013. "Identifying Influential Factors of Knowledge Sharing in Emergency Events: A Virtual Community Perspective," Systems Research and Behavioral Science, Wiley Blackwell, vol. 30(3), pages 367-382, May.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:arx:papers:2307.01404. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.