Quantifying the Impact of Biopics on Wikipedia Articles

Quantifying the Impact of Biopics on Wikipedia Articles

Amit Arjun Verma (Indian Institute of Technology, Ropar, India), Neeru Dubey (Indian Institute of Technology, Ropar, India), Simran Setia (Indian Institute of Technology, Ropar, India), Prudvi Kamtam (Jawaharlal Nehru Technological University, Hyderabad, India) and S. R. S. Iyengar (Indian Institute of Technology, Ropar, India)
Copyright: © 2022 |Pages: 11
DOI: 10.4018/JCIT.20220701.oa5
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Abstract

Wikipedia is known for its extensive and comprehensive knowledge of multifarious topics. These topics are maintained as articles along with a history of versions of these articles, these versions are also known as revisions. Revisions are the results of edits made by various users. Here, the authors analyze biographical Wikipedia articles, mainly biographies that have a movie based on them re- leased after the year 2010. The authors look at the impact of the movie release on its corresponding biography article on Wikipedia by looking at various metrics of each revision in a Wikipedia article and analyze how the revisions closer to the movie’s release date compare with the rest of the revisions. The results show that quality and content in Wikipedia articles increases significantly during the release time frame of corresponding biopics. The authors believe their work will stimulate more research in the direction of understanding Wikipedia’s relationship with its allied portals.
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Introduction

Wikipedia is an online encyclopedia to which anyone can contribute. The vast amount of content present on Wikipedia has made it popular among academicians and general knowledge seekers (Chhabra & Iyengar, How Does Knowledge Come By?, 2017). The success of Wikipedia is largely attributed to the large number of editors who improve the completeness, accuracy, and vision of the articles. It constantly ranks as one of the most popular portals on the Internet, according to Alexa.com. Besides its popularity, researchers have found that its content quality is comparable to traditional encyclopedias (Giles, 2005). Also, the average revert time of vandalism and inaccuracy is within a few minutes (Kittur, Suh, Pendleton, & Chi, 2007) (Priedhorsky, et al., 2007) (Viégas, Wattenberg, & Dave, 2004). Since its inception, it has grown exponentially and currently comprises more than 6 million articles contributed by almost 40 million registered users in English Wikipedia alone.

The quality and completeness of Wikipedia articles have attracted the attention of researchers from various domains to study online collaboration dynamics (Kittur & Kraut, Beyond Wikipedia: coordination and conflict in online production groups, 2010) (Johnson, et al., 2016) (Kittur & Kraut, Harnessing the wisdom of crowds in wikipedia: quality through coordination, 2008) (Ren & Yan, 2017) to examine its impact on other online collaborative portals (Vincent, Johnson, & Hecht, 2018) (Warncke-Wang, Ranjan, Terveen, & Hecht, 2015), and to train state-of-the-art artificial intelligence algorithms (Hoffart, Suchanek, Berberich, & Weikum, 2013) (Medelyan, Milne, Legg, & Witten, 2009) (Mikolov, Sutskever, Chen, Corrado, & Dean, 2013). Even with such a vast domain coverage, researchers have mainly focused on analyzing Wikipedia's content quality. For instance, Kittur and Kraut (Kittur & Kraut, Harnessing the wisdom of crowds in wikipedia: quality through coordination, 2008) found in their analysis that coordination among the editors significantly improves the quality of the Wikipedia articles. Similar results were stated by Arazy and Nov (Arazy & Nov, Determinants of wikipedia quality: the roles of global and local contribution inequality, 2010), they showed the positive impact of contribution inequality on Wikipedia quality. A series of literature unravel the impact of collaboration, group composition, and role identification on Wikipedia quality (Arazy, Morgan, & Patterson, Wisdom of the crowds: Decentralized knowledge construction in Wikipedia, 2006) (Arazy, Nov, Patterson, & Yeo, 2011) (Liu & Ram, 2011) (Welser, et al., 2011).

Despite the exhaustive research on Wikipedia quality, we know little about the impact of external agents on it. Perhaps the most recent example is the study conducted by McMahon et al. (McMahon, Johnson, & Hecht, 2017), which showed that the click-through rates of Google SERPs (search engine results pages) drop dramatically when Wikipedia links are removed. suggesting that Google is quite reliant on Wikipedia to satisfy user information needs. Succeeding the work of McMahon et al., Vincent et al. (Vincent, Johnson, & Hecht, 2018) observed that Wikipedia provides substantial value to Stack Overflow (Stack Overflow, n.d.) and Reddit (Reddit, n.a.) communities, with Wikipedia content increasing visitation, engagement, and revenue on both these portals.

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