Gruda, Jon and Hasan, Souleiman
(2019)
Feeling anxious? Perceiving anxiety in tweets using machine learning.
Computers in Human Behavior, 98.
pp. 245-255.
ISSN 0747-5632
Abstract
This study provides a predictive measurement tool to examine perceived anxiety from a longitudinal perspective,
using a non-intrusive machine learning approach to scale human rating of anxiety in microblogs. Results suggest
that our chosen machine learning approach depicts perceived user state-anxiety fluctuations over time, as well as
mean trait anxiety. We further find a reverse relationship between perceived anxiety and outcomes such as social
engagement and popularity. Implications on the individual, organizational, and societal levels are discussed.
| Item Type: |
Article
|
| Keywords: |
Anxiety;
Machine learning;
Twitter;
Micro-blog;
Health; |
| Academic Unit: |
Faculty of Social Sciences > School of Business |
| Item ID: |
11261 |
| Identification Number: |
https://doi.org/10.1016/j.chb.2019.04.020 |
| Depositing User: |
Jon Gruda
|
| Date Deposited: |
14 Oct 2019 16:11 |
| Journal or Publication Title: |
Computers in Human Behavior |
| Publisher: |
Elsevier |
| Refereed: |
Yes |
| URI: |
|
| Use Licence: |
This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available
here |
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