Tweetin’ in the Rain: Exploring Societal-scale Effects of Weather on Mood

Publication: Research - peer-reviewArticle in proceedings – Annual report year: 2012

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There has been significant recent interest in using the aggregate sentiment from social media sites to understand and predict real-world phenomena. However, the data from social media sites also offers a unique and—so far—unexplored opportunity to study the impact of external factors on aggregate sentiment, at the scale of a society. Using a Twitterspecific sentiment extraction methodology, we the explore patterns of sentiment present in a corpus of over 1.5 billion tweets. We focus primarily on the effect of the weather and time on aggregate sentiment, evaluating how clearly the wellknown individual patterns translate into population-wide patterns. Using machine learning techniques on the Twitter corpus correlated with the weather at the time and location of the tweets, we find that aggregate sentiment follows distinct climate, temporal, and seasonal patterns.
Original languageEnglish
Title of host publicationProceedings of the Sixth International AAAI Conference on Weblogs and Social Media
PublisherAAAI Press
Publication date2012
StatePublished - 2012


Conference6th International AAAI Conference on Weblogs and Social Media (ICWSM 2012)
Period04/06/2012 → …
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ID: 51173727