# IoT-Enabled Social Relationships Meet Artificial Social Intelligence

arXiv: https://arxiv.org/abs/2103.01776 · HTML: https://mlsanity.com/paper/2103.01776/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 109 references that are in the map.
- First posted on arXiv 21 Feb 2021.

## Builds on (most cited first, 3 of 3)

- [Cyber-Physical Systems Security -- A Survey](https://mlsanity.com/paper/1701.04525/) (2017)
- [AI Oriented Large-Scale Video Management for Smart City: Technologies, Standards and Beyond](https://mlsanity.com/paper/1712.01432/) (2017)
- [Social-Feature Enabled Communications among Devices towards Smart IoT Community](https://mlsanity.com/paper/1807.03590/) (2018)

## Built on by (most cited first, 8 of 8)

- [Neural Theory-of-Mind? On the Limits of Social Intelligence in Large LMs](https://mlsanity.com/paper/2210.13312/) (2022)
- [COKE: A Cognitive Knowledge Graph for Machine Theory of Mind](https://mlsanity.com/paper/2305.05390/) (2023)
- [Towards Artificial General Intelligence (AGI) in the Internet of Things (IoT): Opportunities and Challenges](https://mlsanity.com/paper/2309.07438/) (2023)
- [Edge-enabled Metaverse: The Convergence of Metaverse and Mobile Edge Computing](https://mlsanity.com/paper/2205.02764/) (2022)
- [Context-Aware Service Recommendation System for the Social Internet of Things](https://mlsanity.com/paper/2308.08499/) (2023)
- [Listen Then See: Video Alignment with Speaker Attention](https://mlsanity.com/paper/2404.13530/) (2024)
- [RED QUEEN: Safeguarding Large Language Models against Concealed Multi-Turn Jailbreaking](https://mlsanity.com/paper/2409.17458/) (2024)
- [AGI Enabled Solutions For IoX Layers Bottlenecks In Cyber-Physical-Social-Thinking Space](https://mlsanity.com/paper/2506.22487/) (2025)

## Abstract (arXiv)

With the recent advances of the Internet of Things, and the increasing accessibility of ubiquitous computing resources and mobile devices, the prevalence of rich media contents, and the ensuing social, economic, and cultural changes, computing technology and applications have evolved quickly over the past decade. They now go beyond personal computing, facilitating collaboration and social interactions in general, causing a quick proliferation of social relationships among IoT entities. The increasing number of these relationships and their heterogeneous social features have led to computing and communication bottlenecks that prevent the IoT network from taking advantage of these relationships to improve the offered services and customize the delivered content, known as relationship explosion. On the other hand, the quick advances in artificial intelligence applications in social computing have led to the emerging of a promising research field known as Artificial Social Intelligence (ASI) that has the potential to tackle the social relationship explosion problem. This paper discusses the role of IoT in social relationships detection and management, the problem of social relationships explosion in IoT and reviews the proposed solutions using ASI, including social-oriented machine-learning and deep-learning techniques.