SocialQuotes: Learning Contextual Roles of Social Media Quotes on the Web

A vast amount of human discussion, storytelling, content creation, and reporting now occurs on social media platforms. As such, social media posts are often quoted on web pages as context. In this paper, we argue that these quotations and their surrounding page context provide a rich, platform-independent source of data for studying the intersection of natural language and social media. We introduce a taxonomy of quotation roles that categorizes how social media posts are used within content. We release a dataset of 38M social quotes derived from the Common Crawl, and role labels for a subset assessed by human raters. We show that the interplay of accounts, roles, and topics across the web graph reveal valuable social diffusion patterns, and that roles can be predicted with fine-tuned large language models from web context.