@inproceedings{harsley-etal-2016-hit,
title = "Hit Songs' Sentiments Harness Public Mood {\&} Predict Stock Market",
author = "Harsley, Rachel and
Gupta, Bhavesh and
Di Eugenio, Barbara and
Li, Huayi",
editor = "Balahur, Alexandra and
van der Goot, Erik and
Vossen, Piek and
Montoyo, Andres",
booktitle = "Proceedings of the 7th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis",
month = jun,
year = "2016",
address = "San Diego, California",
publisher = "Association for Computational Linguistics",
url = "https://preview.aclanthology.org/fix-sig-urls/W16-0406/",
doi = "10.18653/v1/W16-0406",
pages = "17--25"
}
Markdown (Informal)
[Hit Songs’ Sentiments Harness Public Mood & Predict Stock Market](https://preview.aclanthology.org/fix-sig-urls/W16-0406/) (Harsley et al., WASSA 2016)
ACL
- Rachel Harsley, Bhavesh Gupta, Barbara Di Eugenio, and Huayi Li. 2016. Hit Songs’ Sentiments Harness Public Mood & Predict Stock Market. In Proceedings of the 7th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, pages 17–25, San Diego, California. Association for Computational Linguistics.