Why Antiwork: A RoBERTa-Based System for Work-Related Stress Identification and Leading Factor Analysis
<|reference_start|>Why Antiwork: A RoBERTa-Based System for Work-Related Stress Identification and Leading Factor Analysis: Harsh working environments and work-related stress have been known to contribute to mental health problems such as anxiety, depression, and suicidal ideation. As such, it is paramount to create solutions that can both detect employee unhappiness and find the root cause of the problem. While prior works have examined causes of mental health using machine learning, they typically focus on general mental health analysis, with few of them focusing on explainable solutions or looking at the workplace-specific setting. r/antiwork is a subreddit for the antiwork movement, which is the desire to stop working altogether. Using this subreddit as a proxy for work environment dissatisfaction, we create a new dataset for antiwork sentiment detection and subsequently train a model that highlights the words with antiwork sentiments. Following this, we performed a qualitative and quantitative analysis to uncover some of the key insights into the mindset of individuals who identify with the antiwork movement and how their working environments influenced them. We find that working environments that do not give employees authority or responsibility, frustrating recruiting experiences, and unfair compensation, are some of the leading causes of the antiwork sentiment, resulting in a lack of self-confidence and motivation among their employees.<|reference_end|>
@article{lu2024why,
    title={Why Antiwork: A RoBERTa-Based System for Work-Related Stress
  Identification and Leading Factor Analysis},
    author={Tao Lu, Muzhe Wu, Xinyi Lu, Siyuan Xu, Shuyu Zhan, Anuj Tambwekar,
  Emily Mower Provost},
    journal={arXiv preprint arXiv:2408.13473},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.13473},
    primaryClass={cs.CL}
}