@inproceedings{df18e01d6dff4ca5aa3e65b1337bd930,
title = "Link Topics from Q&A Platforms using Wikidata: A Tool for Cross-platform Hierarchical Classification",
abstract = "This paper proposes a novel rule-based topic classification tool for questions on Q&A platforms mediated by the Wikidata ontology-an open and accessible multilingual ontology curated by a large community of online users. Q&A platforms are important sources of information on the Web and often appear as part of Web search results. By adopting Wikidata taxonomic relations as references, our tool can categories the Web content from different platforms in a unified coarse-to-fine mode based on their domain coverage. To validate and demonstrate the potential applicability of our tool, a set of use cases and experiments are carried out on two popular Q&A platforms-Zhihu and Quora, where the impact of topic categories on question lifecycles is explored. Furthermore, we compare our results with the output generated by GPT-3 classifier. This tool sheds light on how structured knowledge bases can enable data interoperability and serve as a filtering functionality to mitigate classification bias of OpenAI.",
keywords = "Entity Linking, Q&A platforms, Topic classification, Wikidata ontology",
author = "Sha, {Alyssa Shuang} and Nunes, {Bernardo Pereira} and Armin Haller",
note = "Publisher Copyright: {\textcopyright} 2023 Owner/Author.; 15th ACM Web Science Conference, WebSci 2023 ; Conference date: 30-04-2023 Through 01-05-2023",
year = "2023",
month = apr,
day = "30",
doi = "10.1145/3578503.3583625",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery (ACM)",
pages = "357--362",
booktitle = "WebSci 2023 - Proceedings of the 15th ACM Web Science Conference",
address = "United States",
}