# LOST: A Mental Health Dataset of Low Self-esteem in Reddit Posts

arXiv: https://arxiv.org/abs/2306.05596 · HTML: https://mlsanity.com/paper/2306.05596/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 41 references that are in the map.
- First posted on arXiv 8 Jun 2023.

## Builds on (most cited first, 9 of 9)

- [On the Properties of Neural Machine Translation: Encoder-Decoder Approaches](https://mlsanity.com/paper/1409.1259/) (2014)
- [EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks](https://mlsanity.com/paper/1901.11196/) (2019)
- [Improving Neural Machine Translation Models with Monolingual Data](https://mlsanity.com/paper/1511.06709/) (2015)
- [Ethical Challenges in Data-Driven Dialogue Systems](https://mlsanity.com/paper/1711.09050/) (2017)
- [Distilling the Knowledge of BERT for Sequence-to-Sequence ASR](https://mlsanity.com/paper/2008.03822/) (2020)
- [CAMS: An Annotated Corpus for Causal Analysis of Mental Health Issues in Social Media Posts](https://mlsanity.com/paper/2207.04674/) (2022)
- [An Annotated Dataset for Explainable Interpersonal Risk Factors of Mental Disturbance in Social Media Posts](https://mlsanity.com/paper/2305.18727/) (2023)
- [Detection and Classification of mental illnesses on social media using RoBERTa](https://mlsanity.com/paper/2011.11226/) (2020)
- [Process Knowledge-infused Learning for Suicidality Assessment on Social Media](https://mlsanity.com/paper/2204.12560/) (2022)

## Built on by (most cited first, 6 of 6)

- [Interpersonal Theory of Suicide as a Lens to Examine Suicidal Ideation in Online Spaces](https://mlsanity.com/paper/2504.13277/) (2025)
- [MentalQA: An Annotated Arabic Corpus for Questions and Answers of Mental Healthcare](https://mlsanity.com/paper/2405.12619/) (2024)
- [AraHealthQA 2025: The First Shared Task on Arabic Health Question Answering](https://mlsanity.com/paper/2508.20047/) (2025)
- [Assess and Prompt: A Generative RL Framework for Improving Engagement in Online Mental Health Communities](https://mlsanity.com/paper/2508.16788/) (2025)
- [Expert-Level Crisis Detection in Mental Health Conversations](https://mlsanity.com/paper/2606.10380/) (2026)
- [Whose Assessment of Distress? Community Perspectives and LLM Alignment on Well-Being Posts](https://mlsanity.com/paper/2608.29446/) (2026)

## Abstract (arXiv)

Low self-esteem and interpersonal needs (i.e., thwarted belongingness (TB) and perceived burdensomeness (PB)) have a major impact on depression and suicide attempts. Individuals seek social connectedness on social media to boost and alleviate their loneliness. Social media platforms allow people to express their thoughts, experiences, beliefs, and emotions. Prior studies on mental health from social media have focused on symptoms, causes, and disorders. Whereas an initial screening of social media content for interpersonal risk factors and low self-esteem may raise early alerts and assign therapists to at-risk users of mental disturbance. Standardized scales measure self-esteem and interpersonal needs from questions created using psychological theories. In the current research, we introduce a psychology-grounded and expertly annotated dataset, LoST: Low Self esTeem, to study and detect low self-esteem on Reddit. Through an annotation approach involving checks on coherence, correctness, consistency, and reliability, we ensure gold-standard for supervised learning. We present results from different deep language models tested using two data augmentation techniques. Our findings suggest developing a class of language models that infuses psychological and clinical knowledge.