Cultural advice

The Australian National University acknowledges, celebrates and pays our respects to the Ngunnawal and Ngambri people of the Canberra region and to all First Nations Australians on whose traditional lands we meet and work, and whose cultures are among the oldest continuing cultures in human history.

Aboriginal and Torres Strait Islander peoples are advised that ANU Library collections may include images, names, voices, and other representations of deceased persons.

Material in the collection may contain terms, language or views that reflect the period in which the item was created and may be considered inappropriate today.

Link Topics from Q&A Platforms using Wikidata: A Tool for Cross-platform Hierarchical Classification

Loading...
Thumbnail Image

Date

Authors

Sha, Alyssa
Pereira Nunes, Bernardo
Haller, Armin

Journal Title

Journal ISSN

Volume Title

Publisher

Association for Computing Machinery (ACM)

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.

Description

Citation

Source

WebSci '23: Proceedings of the 15th ACM Web Science Conference 2023

Book Title

Entity type

Access Statement

Open Access

License Rights

Creative Commons Attribution 4.0 International License

Restricted until

Downloads