{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/cross-dialect-social-media-dependency-parsing","title":"Cross-Dialect Social Media Dependency Parsing for Social Scientific Entity Attribute Analysis","arxiv_id":null,"date":"2022-10-01","proceeding":"COLING (WNUT) 2022 10","authors":["Chloe Eggleston","Brendan O’Connor"],"abstract":"In this paper, we utilize recent advancements in social media natural language processing to obtain state-of-the-art syntactic dependency parsing results for social media English. We observe performance gains of 3.4 UAS and 4.0 LAS against the previous state-of-the-art as well as less disparity between African-American and Mainstream American English dialects. We demonstrate the computational social scientific utility of this parser for the task of socially embedded entity attribute analysis: for a specified entity, derive its semantic relationships from parses’ rich syntax, and accumulate and compare them across social variables. We conduct a case study on politicized views of U.S. official Anthony Fauci during the COVID-19 pandemic.","url_abs":"https://aclanthology.org/2022.wnut-1.4","url_pdf":"https://aclanthology.org/2022.wnut-1.4.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"cross-dialect-social-media-dependency-parsing","repo_url":"https://github.com/slanglab/tweetie_wnut2022","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"attribute","task_name":"Attribute"},{"task_slug":"dependency-parsing","task_name":"Dependency Parsing"}],"methods":[{"method_slug":null,"method_name":"American"}],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/dependency-parsing-on-tweebank","task":"Dependency Parsing","dataset":"Tweebank","model":"SuPar-BERTweet","rank_in_archive_order":1,"of":3,"metrics":{"Labelled Attachment Score":"83.4","Unlabeled Attachment Score":"87.2 "},"uses_additional_data":false}],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}