Problematizing and Addressing the Article-As-Concept Assumption in Wikipedia

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Problematizing and Addressing the Article-As-Concept Assumption in Wikipedia
Authors
Yilun Lin
Bowen Yu
Andrew Hall
Brent J. Hecht
Publication date
2017
DOI
10.1145/2998181.2998274
Links
Original

Problematizing and Addressing the Article-As-Concept Assumption in Wikipedia - scientific work related to Wikipedia quality published in 2017, written by Yilun Lin, Bowen Yu, Andrew Hall and Brent J. Hecht.

Overview

Wikipedia-based studies and systems frequently assume that no two articles describe the same concept. However, in this paper, authors show that this article-as-concept assumption is problematic due to editors' tendency to split articles into parent articles and sub-articles when articles get too long for readers (e.g. "Portland, Oregon" and "History of Portland, Oregon" in the English Wikipedia). In this paper, authors present evidence that this issue can have significant impacts on Wikipedia-based studies and systems and introduce the sub-article matching problem. The goal of the sub-article matching problem is to automatically connect sub-articles to parent articles to help Wikipedia-based studies and systems retrieve complete information about a concept. Authors then describe the first system to address the sub-article matching problem. Authors show that, using a diverse feature set and standard machine learning techniques, system can achieve good performance on most of ground truth datasets, significantly outperforming baseline approaches.