IDEAS home Printed from https://ideas.repec.org/a/bcy/issued/cognitivesustainabilityv2y2023i4p42-54.html
   My bibliography  Save this article

Exploring Cognitive Sustainability Concerns in Public Responses to Extreme Weather Events: An NLP Analysis of Twitter Data

Author

Listed:
  • Rihem Berbère

    (National Engineering School of Tunis, University of Tunis ElManar, Tunis, Tunisia)

  • Safa Elkefi
  • Safa Bhar Layeb
  • Achraf Tounsi

Abstract

The United States has a long history of experiencing extreme weather events. Hurricanes are among the most devastating natural disasters that have significant economic and physical impacts on the country. By applying Natural Language Processing (NLP) to Twitter data for sentiment analysis, emotion detection, and topic modelling, this study provides a more thorough understanding of public response and concerns during five study cases of hurricanes that hit the United States: Harvey, Irma, Maria, Ida, and Ian. The findings on sentiment analysis revealed that 64.75% of the tweets were classified as Negative and 35.25% as Positive. For emotion detection, the predominant emotion was anger, with 39.91%. These results were centred around the main public concerns shown by the topic modelling: hurricane management, donation and support, and disaster impacts. Our future work will focus on understanding people’s responses to extreme weather events through the evolving concept of Cognitive Sustainability.

Suggested Citation

  • Rihem Berbère & Safa Elkefi & Safa Bhar Layeb & Achraf Tounsi, 2023. "Exploring Cognitive Sustainability Concerns in Public Responses to Extreme Weather Events: An NLP Analysis of Twitter Data," Cognitive Sustainability, Cognitive Sustainability Ltd., vol. 2(4), pages 42-54, December.
  • Handle: RePEc:bcy:issued:cognitivesustainability:v:2:y:2023:i:4:p:42-54
    DOI: 10.55343/CogSust.80
    as

    Download full text from publisher

    File URL: https://www.cogsust.com/index.php/real/article/view/80
    Download Restriction: -

    File URL: https://libkey.io/10.55343/CogSust.80?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
    ---><---

    More about this item

    Keywords

    Hurricane; people response; Sentiment Analysis; Emotion detection; Topic modeling; Natural Language Processing;
    All these keywords.

    JEL classification:

    • D71 - Microeconomics - - Analysis of Collective Decision-Making - - - Social Choice; Clubs; Committees; Associations
    • Z13 - Other Special Topics - - Cultural Economics - - - Economic Sociology; Economic Anthropology; Language; Social and Economic Stratification

    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:bcy:issued:cognitivesustainability:v:2:y:2023:i:4:p:42-54. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Maria SZALMANE CSETE (email available below). General contact details of provider: http://www.CogSust.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.