The Language of Weather: Social Media Reactions to Weather Accounting for Climatic and Linguistic Baselines
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Abstract (arXiv)
This study explores how different weather conditions influence public sentiment on social media, focusing on Twitter data from the UK. By considering climate and linguistic baselines, we improve the accuracy of weather-related sentiment analysis. Our findings show that emotional responses to weather are complex, influenced by combinations of weather variables and regional language differences. The results highlight the importance of context-sensitive methods for better understanding public mood in response to weather, which can enhance impact-based forecasting and risk communication in the context of climate change.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 12 of its 57 references that are in the map. First posted on arXiv 10 Jul 2024.
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References · 12
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
- 2019Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AIcited by 1,543
- 2024Linguistic Bias in ChatGPT: Language Models Reinforce Dialect Discriminationcited by 55
- 2020Investigating Gender Bias in BERTcited by 40
- 2018SemAxis: A Lightweight Framework to Characterize Domain-Specific Word Semantics Beyond Sentimentcited by 25
- 2016Inducing Domain-Specific Sentiment Lexicons from Unlabeled Corporacited by 19
- 2017Social Sensing of Floods in the UKcited by 3
- 2018The Human Geography of Twittercited by 2
- 2014What a Nasty day: Exploring Mood-Weather Relationship from Twittercited by 1
- 2017Weather impacts expressed sentimentcited by 1
- 2023Adverse weather amplifies social media activitycited by 1
- 2023Short text classification with machine learning in the social sciences: The case of climate change on Twittercited by 1
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