What Makes You Stressed? Finding Reasons From Tweets

Reshmi Gopalakrishna Pillai, Mike Thelwall, Constantin Orasan


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.
Anthology ID:
W18-6239
Volume:
Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis
Month:
October
Year:
2018
Address:
Brussels, Belgium
Editors:
Alexandra Balahur, Saif M. Mohammad, Veronique Hoste, Roman Klinger
Venue:
WASSA
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
266–272
Language:
URL:
https://aclanthology.org/W18-6239
DOI:
10.18653/v1/W18-6239
Bibkey:
Cite (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.
Cite (Informal):
What Makes You Stressed? Finding Reasons From Tweets (Gopalakrishna Pillai et al., WASSA 2018)
Copy Citation:
PDF:
https://aclanthology.org/W18-6239.pdf