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FIRE Semester 1 Team 2 Presentation

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Natural Language Processing & Temperature Change

Team 2

Kavi Chen, Aniket Chityala

Saanchi Desai, Meghana Paireddy

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Research Question & Significance

Q: How can natural language processing be used to reveal people’s responses to daily temperature changes?

Relevancy:

  • Detecting people’s mentality
  • Time and money saving to study and predict
  • Helps to solve and predict people’s emotion according to the temperature
  • Business use study the behavior of customers

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Result 1:Heatwave exposures affects the sentiment of Twitter users negatively.

  • The paper investigates the proposed questions by reviewing 44 indicators on different domains and compiling an overall summary of the effect of climate change on human health.
  • The graph talks about the annual effect of heatwaves on human sentiments. A box graph is used to depict change in sentiment relative to median temperature.
  • In 2020 negative sentiment increased by 115% compared to the 2015-19 average. There was also an observed reduction in positive sentiment.

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Romanello, Marina. et al. “The 2021 Report of the Lancet Countdown on Health and Climate Change: Code Red for a Healthy Future.” The Lancet, 30 Oct. 2021

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Result 2: Temperature change affects people’s willingness to pay.

  • The quality of life in comparison to temperature for thousands of families across 48 US states. However, desired temperatures do vary from city to city.
  • In this figure, consider the panels.

Albouy, David, et al. “Climate Amenities, Climate Change, and American Quality of Life.” Journal of the Association of Environmental and Resource Economists, vol. 3, no. 1, 2016, pp. 205–246., https://doi.org/10.1086/684573.

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Discussion & Conclusions

  • Natural language processing can be used to understand why people react the way they do when there are changes in the environment and temperatures change.
  • Can be relevant for governments and businesses to gauge reactions from audiences