# Ten Social Dimensions of Conversations and Relationships

arXiv: https://arxiv.org/abs/2001.09954 · HTML: https://mlsanity.com/paper/2001.09954/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Jan 2020.

## Built on by (most cited first, 18 of 18)

- [Do LLMs Understand Social Knowledge? Evaluating the Sociability of Large Language Models with SocKET Benchmark](https://mlsanity.com/paper/2305.14938/) (2023)
- [The Persuasive Power of Large Language Models](https://mlsanity.com/paper/2312.15523/) (2023)
- [The Parrot Dilemma: Human-Labeled vs. LLM-augmented Data in Classification Tasks](https://mlsanity.com/paper/2304.13861/) (2023)
- [Conversations Gone Alright: Quantifying and Predicting Prosocial Outcomes in Online Conversations](https://mlsanity.com/paper/2102.08368/) (2021)
- [Whose wife is it anyway? Assessing bias against same-gender relationships in machine translation](https://mlsanity.com/paper/2401.04972/) (2024)
- [How Social is It? A Benchmark for LLMs' Capabilities in Multi-user Multi-turn Social Agent Tasks](https://mlsanity.com/paper/2505.04628/) (2025)
- [Machines in the Crowd? Measuring the Footprint of Machine-Generated Text on Reddit](https://mlsanity.com/paper/2510.07226/) (2025)
- ["I understand your perspective": LLM Persuasion through the Lens of Communicative Action Theory](https://mlsanity.com/paper/2606.08076/) (2026)
- [The Need for Interpretable Features: Motivation and Taxonomy](https://mlsanity.com/paper/2202.11748/) (2022)
- [ExpressivityBench: Can LLMs Communicate Implicitly?](https://mlsanity.com/paper/2411.08010/) (2024)
- [You need to MIMIC to get FAME: Solving Meeting Transcript Scarcity with a Multi-Agent Conversations](https://mlsanity.com/paper/2502.13001/) (2025)
- [Who's Asking? Simulating Role-Based Questions for Conversational AI Evaluation](https://mlsanity.com/paper/2510.16829/) (2025)
- [Frictionless Love: Associations Between AI Companion Roles and Behavioral Addiction](https://mlsanity.com/paper/2604.20011/) (2026)
- [P1SCO: Social Dimensions from a Perspectivist Lens](https://mlsanity.com/paper/2605.25312/) (2026)
- [Semantic-Guided RL for Interpretable Feature Engineering](https://mlsanity.com/paper/2410.02519/) (2024)
- [Exposure to Content Written by Large Language Models Can Reduce Stigma Around Opioid Use Disorder in Online Communities](https://mlsanity.com/paper/2504.10501/) (2025)
- [Learning Perspectivist Social Meaning via Demographic-Conditioned Fusion Embeddings](https://mlsanity.com/paper/2606.07123/) (2026)
- [Les Mis'erables Dialogue: A film-based network representation of social communication](https://mlsanity.com/paper/2610.13148/) (2026)

## Abstract (arXiv)

Decades of social science research identified ten fundamental dimensions that provide the conceptual building blocks to describe the nature of human relationships. Yet, it is not clear to what extent these concepts are expressed in everyday language and what role they have in shaping observable dynamics of social interactions. After annotating conversational text through crowdsourcing, we trained NLP tools to detect the presence of these types of interaction from conversations, and applied them to 160M messages written by geo-referenced Reddit users, 290k emails from the Enron corpus and 300k lines of dialogue from movie scripts. We show that social dimensions can be predicted purely from conversations with an AUC up to 0.98, and that the combination of the predicted dimensions suggests both the types of relationships people entertain (conflict vs. support) and the types of real-world communities (wealthy vs. deprived) they shape.