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

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arxiv 2401.02575 v1 pith:PEHW6CP7 submitted 2024-01-04 cs.SI cs.AIcs.LG

classification cs.SIcs.AIcs.LG
keywords networkssocialapplicationscontentknowledgetaskschallengesdevelop
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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Cited by 1 Pith paper

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  1. Harnessing the Potential of Large Language Models in Modern Marketing Management: Applications, Future Directions, and Strategic Recommendations

    cs.CL 2025-01 reject

    A narrative review asserting that LLMs transform marketing with personalization and automation, but without new evidence or rigorous analysis.

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