Large Language Models for Social Networks: Applications, Challenges, and
  Solutions
Jingying Zeng Richard Huang Waleed Malik Langxuan Yin Bojan Babic Danny Shacham Xiao Yan Jaewon Yang Qi He
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.