What Makes a Good Biography?: Multidimensional Quality Analysis Based on Wikipedia Article Feedback Data
Authors | Lucie Flekova Oliver Ferschke Iryna Gurevych |
|---|---|
Publication date | 2014 |
ISBN | 978-145032744-2 |
DOI | 10.1145/2566486.2567972 |
Links |
What Makes a Good Biography?: Multidimensional Quality Analysis Based on Wikipedia Article Feedback Data - scientific work about Wikipedia quality published in 2014, written by Lucie Flekova, Oliver Ferschke and Iryna Gurevych.
Overview
With more than 22 million articles, the largest collaborative knowledge resource never sleeps, experiencing several article edits every second. Over one fifth of these articles describes individual people, the majority of which are still alive. Such articles are, by their nature, prone to corruption and vandalism. Manual quality assurance by experts can barely cope with this massive amount of data. Can it be effectively replaced by feedback from the crowd? Can authors provide meaningful support for quality assurance with automated text processing techniques? Which properties of the articles should then play a key role in the machine learning algorithms and why? In this paper, authors study the user-perceived quality of Wikipedia articles based on a novel Wikipedia user feedback dataset. In contrast to previous work on quality assessment which mostly relied on judgements of active Wikipedia authors, authors analyze ratings of ordinary Wikipedia users along four quality dimensions (complete, well written, trustworthy and objective). Authors first present an empirical analysis of the novel dataset with over 36 million Wikipedia article ratings. Authors then select a subset of biographical articles and perform classification experiments to predict their quality ratings along each of the dimensions, exploring multiple linguistic, surface and network properties of the rated articles. Additionally, authors study the classification performance and differences for the biographies of living and dead people as well as those for men and women. Authors demonstrate the effectiveness of their approach by the F1 scores of 0.94, 0.89, 0.73, and 0.73 for the dimensions complete, well written, trustworthy, and objective. Based on the results, authors believe that the quality assessment of big textual data can be effectively supported by current text classification and language processing tools.
Embed
Wikipedia Quality
Flekova, Lucie; Ferschke, Oliver; Gurevych, Iryna. (2014). "[[What Makes a Good Biography?: Multidimensional Quality Analysis Based on Wikipedia Article Feedback Data]]". Behaviour and Information Technology Volume 33, Issue 12, 13 December 2014, pp. 1361-1370. ISBN: 978-145032744-2. DOI: 10.1145/2566486.2567972.
English Wikipedia
{{cite journal |last1=Flekova |first1=Lucie |last2=Ferschke |first2=Oliver |last3=Gurevych |first3=Iryna |title=What Makes a Good Biography?: Multidimensional Quality Analysis Based on Wikipedia Article Feedback Data |date=2014 |isbn=978-145032744-2 |doi=10.1145/2566486.2567972 |url=https://wikipediaquality.com/wiki/What_Makes_a_Good_Biography?:_Multidimensional_Quality_Analysis_Based_on_Wikipedia_Article_Feedback_Data |journal=Behaviour and Information Technology Volume 33, Issue 12, 13 December 2014, pp. 1361-1370}}
HTML
Flekova, Lucie; Ferschke, Oliver; Gurevych, Iryna. (2014). "<a href="https://wikipediaquality.com/wiki/What_Makes_a_Good_Biography?:_Multidimensional_Quality_Analysis_Based_on_Wikipedia_Article_Feedback_Data">What Makes a Good Biography?: Multidimensional Quality Analysis Based on Wikipedia Article Feedback Data</a>". Behaviour and Information Technology Volume 33, Issue 12, 13 December 2014, pp. 1361-1370. ISBN: 978-145032744-2. DOI: 10.1145/2566486.2567972.
