Abstract
Social media is a potential source of information that infers latent mental states through Natural Language Processing (NLP). While narrating real-life experiences, social media users convey their feeling of loneliness or isolated lifestyle, impacting their mental well-being. Existing literature on psychological theories points to loneliness as the major consequence of interpersonal risk factors, propounding the need to investigate loneliness as a major aspect of mental disturbance. We formulate lonesomeness detection in social media posts as an explainable binary classification problem, discovering the users at-risk, suggesting the need of resilience for early control. To the best of our knowledge, there is no existing explainable dataset, i.e., one with human-readable, annotated text spans, to facilitate further research and development in loneliness detection causing mental disturbance [9]. In this work, three experts: a senior clinical psychologist, a rehabilitation counselor, and a social NLP researcher define annotation schemes and perplexity guidelines to mark the presence or absence of lonesomeness, along with the marking of text-spans in original posts as explanation, in 3, 521 Reddit posts. We expect the public release of our dataset, LonXplain, and traditional classifiers as baselines via GitHub (https://github.com/drmuskangarg/lonesomeness_dataset).
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Acknowledgement
We would like to sincerely thank the postgraduate student annotators, Ritika Bhardwaj, Astha Jain, and Amrit Chadha, for their dedicated work in the annotation process. We are grateful to Veena Krishnan, a senior clinical psychologist, and Ruchi Joshi, a rehabilitation counselor, for their unwavering support during the project. Furthermore, we would like to express our heartfelt appreciation to Prof. Sunghwan Sohn for consistently guiding and supporting us.
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Ethical Considerations and Broader Impact
We emphasize that the sensitive nature of our work necessitates that we use publicly available Reddit posts in a purely observational manner. This research intends to improve public health surveillance and other health applications that automatically identify lonesomeness on Reddit. To adhere to privacy constraints, we do not disclose any personal information such as demographics, location, and personal details of social media user while making LonXplain publicly available [24]. The annotations scheme is carried out under the observation of a senior clinical psychologist, a rehabilitation counselor, and a social NLP expert. This research is purely observational and we do not claim any solution for clinical diagnosis at this stage [1]. Reddit posts might subject to biased demographics such as race, location and gender of a user. Therefore, we do not claim diversity in our dataset. Our dataset is susceptible to the prejudices and biases of our student annotators. There will be no ethical issues or legal impact with our dataset and is subject to IRB approval.
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Garg, M., Saxena, C., Samanta, D., Dorr, B.J. (2023). LonXplain: Lonesomeness as a Consequence of Mental Disturbance in Reddit Posts. In: Métais, E., Meziane, F., Sugumaran, V., Manning, W., Reiff-Marganiec, S. (eds) Natural Language Processing and Information Systems. NLDB 2023. Lecture Notes in Computer Science, vol 13913. Springer, Cham. https://doi.org/10.1007/978-3-031-35320-8_27
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DOI: https://doi.org/10.1007/978-3-031-35320-8_27
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