# SocialSim: Towards Socialized Simulation of Emotional Support Conversation

arXiv: https://arxiv.org/abs/2506.16756 · HTML: https://mlsanity.com/paper/2506.16756/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 35 references that are in the map.
- First posted on arXiv 20 Jun 2025.

## Builds on (most cited first, 10 of 10)

- [LoRA: Low-Rank Adaptation of Large Language Models](https://mlsanity.com/paper/2106.09685/) (2021)
- [Llama 2: Open Foundation and Fine-Tuned Chat Models](https://mlsanity.com/paper/2307.09288/) (2023)
- [A Diversity-Promoting Objective Function for Neural Conversation Models](https://mlsanity.com/paper/1510.03055/) (2015)
- [How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Metrics for Dialogue Response Generation](https://mlsanity.com/paper/1603.08023/) (2016)
- [PsyQA: A Chinese Dataset for Generating Long Counseling Text for Mental Health Support](https://mlsanity.com/paper/2106.01702/) (2021)
- [MISC: A MIxed Strategy-Aware Model Integrating COMET for Emotional Support Conversation](https://mlsanity.com/paper/2203.13560/) (2022)
- [AugESC: Dialogue Augmentation with Large Language Models for Emotional Support Conversation](https://mlsanity.com/paper/2202.13047/) (2022)
- [Cue-CoT: Chain-of-thought Prompting for Responding to In-depth Dialogue Questions with LLMs](https://mlsanity.com/paper/2305.11792/) (2023)
- [Building Emotional Support Chatbots in the Era of LLMs](https://mlsanity.com/paper/2308.11584/) (2023)
- [COKE: A Cognitive Knowledge Graph for Machine Theory of Mind](https://mlsanity.com/paper/2305.05390/) (2023)

## Built on by (most cited first, 7 of 7)

- [ES-MemEval: Benchmarking Conversational Agents on Personalized Long-Term Emotional Support](https://mlsanity.com/paper/2602.01885/) (2026)
- [Towards Open-Ended Emotional Support Conversations in LLMs via Reinforcement Learning with Future-Oriented Rewards](https://mlsanity.com/paper/2508.12935/) (2025)
- [EmoHarbor: Evaluating Personalized Emotional Support by Simulating the User's Internal World](https://mlsanity.com/paper/2601.01530/) (2026)
- [Affective Flow Language Model for Emotional Support Conversation](https://mlsanity.com/paper/2602.08826/) (2026)
- [CARE: Cognitive-reasoning Augmented Reinforcement for Emotional Support Conversation](https://mlsanity.com/paper/2510.05122/) (2025)
- [ESC-Skills: Discovering and Self-Evolving Skills for Emotional Support Conversations](https://mlsanity.com/paper/2605.27908/) (2026)
- [Modeling Multiple Support Strategies within a Single Turn for Emotional Support Conversations](https://mlsanity.com/paper/2604.17972/) (2026)

## Abstract (arXiv)

Emotional support conversation (ESC) helps reduce people's psychological stress and provide emotional value through interactive dialogues. Due to the high cost of crowdsourcing a large ESC corpus, recent attempts use large language models for dialogue augmentation. However, existing approaches largely overlook the social dynamics inherent in ESC, leading to less effective simulations. In this paper, we introduce SocialSim, a novel framework that simulates ESC by integrating key aspects of social interactions: social disclosure and social awareness. On the seeker side, we facilitate social disclosure by constructing a comprehensive persona bank that captures diverse and authentic help-seeking scenarios. On the supporter side, we enhance social awareness by eliciting cognitive reasoning to generate logical and supportive responses. Building upon SocialSim, we construct SSConv, a large-scale synthetic ESC corpus of which quality can even surpass crowdsourced ESC data. We further train a chatbot on SSConv and demonstrate its state-of-the-art performance in both automatic and human evaluations. We believe SocialSim offers a scalable way to synthesize ESC, making emotional care more accessible and practical.