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

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

Standard

Tweetin’ in the Rain: Exploring Societal-scale Effects of Weather on Mood. / Hannak, Aniko; Jørgensen, Sune Lehmann; Anderson, Eric; Mislove, Alan; Feldman Barrett, Lisa; Riedewald, Mirek.

Proceedings of the Sixth International AAAI Conference on Weblogs and Social Media. AAAI Press, 2012. p. 479-482.

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

Harvard

Hannak, A, Jørgensen, SL, Anderson, E, Mislove, A, Feldman Barrett, L & Riedewald, M 2012, 'Tweetin’ in the Rain: Exploring Societal-scale Effects of Weather on Mood'. in Proceedings of the Sixth International AAAI Conference on Weblogs and Social Media. AAAI Press, pp. 479-482.

APA

Hannak, A., Jørgensen, S. L., Anderson, E., Mislove, A., Feldman Barrett, L., & Riedewald, M. (2012). Tweetin’ in the Rain: Exploring Societal-scale Effects of Weather on Mood. In Proceedings of the Sixth International AAAI Conference on Weblogs and Social Media. (pp. 479-482). AAAI Press.

CBE

Hannak A, Jørgensen SL, Anderson E, Mislove A, Feldman Barrett L, Riedewald M. 2012. Tweetin’ in the Rain: Exploring Societal-scale Effects of Weather on Mood. In Proceedings of the Sixth International AAAI Conference on Weblogs and Social Media. AAAI Press. pp. 479-482.

MLA

Hannak, Aniko et al. "Tweetin’ in the Rain: Exploring Societal-scale Effects of Weather on Mood". Proceedings of the Sixth International AAAI Conference on Weblogs and Social Media. AAAI Press. 2012. 479-482.

Vancouver

Hannak A, Jørgensen SL, Anderson E, Mislove A, Feldman Barrett L, Riedewald M. Tweetin’ in the Rain: Exploring Societal-scale Effects of Weather on Mood. In Proceedings of the Sixth International AAAI Conference on Weblogs and Social Media. AAAI Press. 2012. p. 479-482.

Author

Hannak, Aniko; Jørgensen, Sune Lehmann; Anderson, Eric; Mislove, Alan; Feldman Barrett, Lisa; Riedewald, Mirek / Tweetin’ in the Rain: Exploring Societal-scale Effects of Weather on Mood.

Proceedings of the Sixth International AAAI Conference on Weblogs and Social Media. AAAI Press, 2012. p. 479-482.

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

Bibtex

@inbook{48faa41afd0548f5a4622c263298a74b,
title = "Tweetin’ in the Rain: Exploring Societal-scale Effects of Weather on Mood",
publisher = "AAAI Press",
author = "Aniko Hannak and Jørgensen, {Sune Lehmann} and Eric Anderson and Alan Mislove and {Feldman Barrett}, Lisa and Mirek Riedewald",
year = "2012",
pages = "479-482",
booktitle = "Proceedings of the Sixth International AAAI Conference on Weblogs and Social Media",

}

RIS

TY - GEN

T1 - Tweetin’ in the Rain: Exploring Societal-scale Effects of Weather on Mood

A1 - Hannak,Aniko

A1 - Jørgensen,Sune Lehmann

A1 - Anderson,Eric

A1 - Mislove,Alan

A1 - Feldman Barrett,Lisa

A1 - Riedewald,Mirek

AU - Hannak,Aniko

AU - Jørgensen,Sune Lehmann

AU - Anderson,Eric

AU - Mislove,Alan

AU - Feldman Barrett,Lisa

AU - Riedewald,Mirek

PB - AAAI Press

PY - 2012

Y1 - 2012

N2 - 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.

AB - 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.

BT - Proceedings of the Sixth International AAAI Conference on Weblogs and Social Media

T2 - Proceedings of the Sixth International AAAI Conference on Weblogs and Social Media

SP - 479

EP - 482

ER -