mlsanityData to 7 Oct 2026

Large Language Models for Social Networks: Applications, Challenges, and Solutions

arXiv 2401.02575 ↗First posted 4 Jan 2024cs.SI cs.AI cs.LGcited by 11

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Abstract (arXiv)

Large Language Models (LLMs) are transforming the way people generate, explore, and engage with content. We study how we can develop LLM applications for online social networks. Despite LLMs' successes in other domains, it is challenging to develop LLM-based products for social networks for numerous reasons, and it has been relatively under-reported in the research community. We categorize LLM applications for social networks into three categories. First is knowledge tasks where users want to find new knowledge and information, such as search and question-answering. Second is entertainment tasks where users want to consume interesting content, such as getting entertaining notification content. Third is foundational tasks that need to be done to moderate and operate the social networks, such as content annotation and LLM monitoring. For each task, we share the challenges we found, solutions we developed, and lessons we learned. To the best of our knowledge, this is the first comprehensive paper about developing LLM applications for social networks.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 76 of its 90 references that are in the map. First posted on arXiv 4 Jan 2024.

Builds on

76 of 90 references.

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50 most cited of 76 All 76 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 7; 2026: 1.

11 papers.

  1. 2024Retrieval-Augmented Generation with Graphs (GraphRAG)cited by 170
  2. 2024LiSeCo: Linear Semantic Control for Language Generationcited by 20
  3. 2025Cite Before You Speak: Enhancing Context-Response Grounding in E-commerce Conversational LLM-Agentscited by 7
  4. 2024Multimodal LLMs Struggle with Basic Visual Network Analysis: a VNA Benchmarkcited by 2
  5. 2025Harnessing the Potential of Large Language Models in Modern Marketing Management: Applications, Future Directions, and Strategic Recommendationscited by 2
  6. 2025SNS-Bench-VL: Benchmarking Multimodal Large Language Models in Social Networking Servicescited by 2
  7. 2025Plan Then Retrieve: Reinforcement Learning-Guided Complex Reasoning over Knowledge Graphscited by 1
  8. 2025RedOne 2.0: Rethinking Domain-specific LLM Post-Training in Social Networking Servicescited by 1
  9. 2025Large VLM-based Stylized Sports Captioningcited by 0
  10. 2025Breakdance Video classification in the age of Generative AIcited by 0
  11. 2026LLMs for Social Network Modeling: From Network Generation to Dynamic Processescited by 0