@inproceedings{gopalakrishna-pillai-etal-2018-makes,
title = "What Makes You Stressed? Finding Reasons From Tweets",
author = "Gopalakrishna Pillai, Reshmi and
Thelwall, Mike and
Orasan, Constantin",
editor = "Balahur, Alexandra and
Mohammad, Saif M. and
Hoste, Veronique and
Klinger, Roman",
booktitle = "Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis",
month = oct,
year = "2018",
address = "Brussels, Belgium",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W18-6239/",
doi = "10.18653/v1/W18-6239",
pages = "266--272",
abstract = "Detecting stress from social media gives a non-intrusive and inexpensive alternative to traditional tools such as questionnaires or physiological sensors for monitoring mental state of individuals. This paper introduces a novel framework for finding reasons for stress from tweets, analyzing multiple categories for the first time. Three word-vector based methods are evaluated on collections of tweets about politics or airlines and are found to be more accurate than standard machine learning algorithms."
}
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%0 Conference Proceedings
%T What Makes You Stressed? Finding Reasons From Tweets
%A Gopalakrishna Pillai, Reshmi
%A Thelwall, Mike
%A Orasan, Constantin
%Y Balahur, Alexandra
%Y Mohammad, Saif M.
%Y Hoste, Veronique
%Y Klinger, Roman
%S Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis
%D 2018
%8 October
%I Association for Computational Linguistics
%C Brussels, Belgium
%F gopalakrishna-pillai-etal-2018-makes
%X Detecting stress from social media gives a non-intrusive and inexpensive alternative to traditional tools such as questionnaires or physiological sensors for monitoring mental state of individuals. This paper introduces a novel framework for finding reasons for stress from tweets, analyzing multiple categories for the first time. Three word-vector based methods are evaluated on collections of tweets about politics or airlines and are found to be more accurate than standard machine learning algorithms.
%R 10.18653/v1/W18-6239
%U https://aclanthology.org/W18-6239/
%U https://doi.org/10.18653/v1/W18-6239
%P 266-272
Markdown (Informal)
[What Makes You Stressed? Finding Reasons From Tweets](https://aclanthology.org/W18-6239/) (Gopalakrishna Pillai et al., WASSA 2018)
ACL
- Reshmi Gopalakrishna Pillai, Mike Thelwall, and Constantin Orasan. 2018. What Makes You Stressed? Finding Reasons From Tweets. In Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, pages 266–272, Brussels, Belgium. Association for Computational Linguistics.