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World Environment Day: Understanding Environmental Programs Impact on Society Using Twitter Data Mining

Author

Listed:
  • Enara Zarrabeitia-Bilbao

    (University of the Basque Country)

  • Rosa-María Rio-Belver

    (University of the Basque Country)

  • Izaskun Alvarez-Meaza

    (University of the Basque Country)

  • Itziar Martínez de Alegría-Mancisidor

    (University of the Basque Country)

Abstract

Environmental sustainability awareness has encouraged the promotion of a number of environmental programs and initiatives and, accordingly, the use of social networks for the dissemination and support of these initiatives has grown significantly. Thus, the purpose of the work is to understand United Nations World Environment Day (WED) programs impact on the digital public debate using Twitter data mining. For that, an ad hoc methodology is designed to provide it to authorities and organizations that wish to analyze the impact of different initiatives or programs on society. All in all, the research carried out analyzes more than 400,000 tweets sent during the 2021 edition of the WED. The tweets have been processed using Big Data techniques and Social Network Analysis. The research reveals that the WED was a trending topic initiative that was discussed in positive terms, where collective sentiment was shown. The topics covered dealt with the event day and the different initiatives related to restoration of ecosystems. However, it is noted that: there is no coordinated action by the institutions, groups or individuals involved in the conversation and the initiative tends towards homophily; digital mobilization is mostly centered in the host country (Pakistan) and, above all, in the neighboring country (India) and, the conspicuous absence of the business sphere in the discussion.

Suggested Citation

  • Enara Zarrabeitia-Bilbao & Rosa-María Rio-Belver & Izaskun Alvarez-Meaza & Itziar Martínez de Alegría-Mancisidor, 2022. "World Environment Day: Understanding Environmental Programs Impact on Society Using Twitter Data Mining," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 164(1), pages 263-284, November.
    • Handle: RePEc:spr:soinre:v:164:y:2022:i:1:d:10.1007_s11205-022-02957-y
    DOI: 10.1007/s11205-022-02957-y
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    References listed on IDEAS

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    1. Ana Reyes-Menendez & José Ramón Saura & Cesar Alvarez-Alonso, 2018. "Understanding #WorldEnvironmentDay User Opinions in Twitter: A Topic-Based Sentiment Analysis Approach," IJERPH, MDPI, vol. 15(11), pages 1-18, November.
    2. Andrew Peplow & Justin Thomas & Aamna AlShehhi, 2021. "Noise Annoyance in the UAE: A Twitter Case Study via a Data-Mining Approach," IJERPH, MDPI, vol. 18(4), pages 1-9, February.
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    Cited by:

    1. Javier Jiménez-Cabas & Lizeth Torres & Jorge de J. Lozoya-Santos, 2023. "Twitter Data Mining for the Diagnosis of Leaks in Drinking Water Distribution Networks," Sustainability, MDPI, vol. 15(6), pages 1-16, March.

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