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The Online Dissemination of Nature–Health Concepts: Lessons from Sentiment Analysis of Social Media Relating to “Nature-Deficit Disorder”

Author

Listed:
  • Marco Palomino

    (School of Computing and Digital Media, Robert Gordon University, Aberdeen, Scotland AB10 7GE, UK
    Research started while working for the University of Exeter Medical School.)

  • Tim Taylor

    (European Centre for Environment and Human Health, University of Exeter Medical School, Truro, Cornwall TR1 3HD, UK)

  • Ayse Göker

    (School of Computing and Digital Media, Robert Gordon University, Aberdeen, Scotland AB10 7GE, UK)

  • John Isaacs

    (School of Computing and Digital Media, Robert Gordon University, Aberdeen, Scotland AB10 7GE, UK)

  • Sara Warber

    (European Centre for Environment and Human Health, University of Exeter Medical School, Truro, Cornwall TR1 3HD, UK
    Department of Family Medicine, University of Michigan Medical School, Ann Arbor, MI 48104-1213, USA)

Abstract

Evidence continues to grow supporting the idea that restorative environments, green exercise, and nature-based activities positively impact human health. Nature-deficit disorder , a journalistic term proposed to describe the ill effects of people’s alienation from nature, is not yet formally recognized as a medical diagnosis. However, over the past decade, the phrase has been enthusiastically taken up by some segments of the lay public. Social media, such as Twitter , with its opportunities to gather “big data” related to public opinions, offers a medium for exploring the discourse and dissemination around nature-deficit disorder and other nature–health concepts. In this paper, we report our experience of collecting more than 175,000 tweets, applying sentiment analysis to measure positive, neutral or negative feelings, and preliminarily mapping the impact on dissemination. Sentiment analysis is currently used to investigate the repercussions of events in social networks, scrutinize opinions about products and services, and understand various aspects of the communication in Web-based communities. Based on a comparison of nature-deficit-disorder “hashtags” and more generic nature hashtags, we make recommendations for the better dissemination of public health messages through changes to the framing of messages. We show the potential of Twitter to aid in better understanding the impact of the natural environment on human health and wellbeing.

Suggested Citation

  • Marco Palomino & Tim Taylor & Ayse Göker & John Isaacs & Sara Warber, 2016. "The Online Dissemination of Nature–Health Concepts: Lessons from Sentiment Analysis of Social Media Relating to “Nature-Deficit Disorder”," IJERPH, MDPI, vol. 13(1), pages 1-23, January.
    • Handle: RePEc:gam:jijerp:v:13:y:2016:i:1:p:142-:d:62462
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    References listed on IDEAS

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    Cited by:

    1. Carlos de las Heras-Pedrosa & Pablo Sánchez-Núñez & José Ignacio Peláez, 2020. "Sentiment Analysis and Emotion Understanding during the COVID-19 Pandemic in Spain and Its Impact on Digital Ecosystems," IJERPH, MDPI, vol. 17(15), pages 1-22, July.
    2. Donghua Chen & Runtong Zhang & Kecheng Liu & Lei Hou, 2018. "Knowledge Discovery from Posts in Online Health Communities Using Unified Medical Language System," IJERPH, MDPI, vol. 15(6), pages 1-16, June.
    3. 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.
    4. Tie Hua Zhou & Gong Liang Hu & Ling Wang, 2019. "Psychological Disorder Identifying Method Based on Emotion Perception over Social Networks," IJERPH, MDPI, vol. 16(6), pages 1-17, March.
    5. Xiaodong Cao & Piers MacNaughton & Zhengyi Deng & Jie Yin & Xi Zhang & Joseph G. Allen, 2018. "Using Twitter to Better Understand the Spatiotemporal Patterns of Public Sentiment: A Case Study in Massachusetts, USA," IJERPH, MDPI, vol. 15(2), pages 1-15, February.
    6. Laia Subirats & Natalia Reguera & Antonio Miguel Bañón & Beni Gómez-Zúñiga & Julià Minguillón & Manuel Armayones, 2018. "Mining Facebook Data of People with Rare Diseases: A Content-Based and Temporal Analysis," IJERPH, MDPI, vol. 15(9), pages 1-13, August.

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