mlsanityData to 7 Oct 2026

IoT-Enabled Social Relationships Meet Artificial Social Intelligence

arXiv 2103.01776 ↗First posted 21 Feb 2021cs.CY cs.AI cs.NIcited by 8

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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.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 3 of its 109 references that are in the map. First posted on arXiv 21 Feb 2021.

Builds on

3 of 109 references.

References · 3

  1. 2017Cyber-Physical Systems Security -- A Surveycited by 19
  2. 2017AI Oriented Large-Scale Video Management for Smart City: Technologies, Standards and Beyondcited by 2
  3. 2018Social-Feature Enabled Communications among Devices towards Smart IoT Communitycited by 1

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Cited by year

Citing papers per year: 2022: 2; 2023: 3; 2024: 2; 2025: 1.

8 papers.