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Abstract

Wikipedia is the most influential popular information source on the Internet, and is ranked as the fifth most visited website [1] (Alexa, 2017). The English-language Wikipedia is a prominent source of online health information compared to other providers such as MedlinePlus and NHS Direct (Laurent and Vickers, 2009). Wikipedia has challenged the way that traditional medical encyclopaedia knowledge is built by creating an open sociotechnical environment that allows non-domain experts to contribute to its articles. Also, this sociotechnical environment allows bots – computer scripts that automatically handle repetitive and mundane tasks – to work with humans to develop, improve, maintain and contest information in Wikipedia articles. The contestation in Wikipedia is unavoidable as a consequence of its open nature, which means that it accepts contradictory views on a topic and involves controversies. The objective of this research is to understand the impact of controversy on the relationship between humans and bots in environments that are managed by the crowd. This study analyses all the articles under the WikiProject Medicine, and includes 36,850 Wikipedia articles. Medical articles and their editing history have been harvested from the Wikipedia API covering all edits from 2001 till 2016. The data includes the revisions ID, username, timestamp, and comment. The articles under the WikiProject Medicine contain 6,220,413 edits and around 1,285,936 human and bot editors. To measure controversies, we studied reverted and undone edits. A revert on Wikipedia occurs when an editor, whether human or bot, restores the article to an earlier version after another editor's contribution. Undone edits are reverted single edits from the history of a page, without simultaneously undoing all constructive changes that have been made since the previous edit. Reverted and undone edits that occur systematically indicate controversy and conflict (Tsvetkova et al., 2017). To measure the relationship between humans and bots, we focused on both positive and negative relationships. A positive relationship is when an editor, such as a human, endorses another editor, such as a bot, by reverting or undoing a recent edit to the other editor's contribution. A negative relationship is when an editor, such as human, discards another editor, such as a bot, by reverting or undoing the other editor's contribution. Our results show that there is a relationship between controversial articles and the development of a positive relationship between humans and bots. The results demonstrate that bots and humans could behave differently in controversial environments. The study highlights some of the important features of building health-related knowledge on Wikipedia. The contribution of this work is to build on previous theories that consider web-based systems as social machines. These theories recognise the joint contribution of humans and machines to activities on the web, but assume a very static type of relationships that is not sensitive to the environment in which humans and machines operate in. Understanding the interactions between humans and bots is crucial for designing crowdsourced environments that are integrative to their human and non-human population. We discuss how our findings can help set up future research directions and outline important implications for research on crowd. References: Laurent, M. R & Vickers, T. J (2009) ‘Seeking Health Information Online: Does Wikipedia Matter.?’ J Am Med Inform Assoc, 16(4), 471-479. Tsvetkova, M, García-Gavilanes, R, Floridi, L and Yasseri, T. (2017) ‘Even good bots fight: The case of Wikipedia.’ PLoS One, 12(2): e0171774. [1] https://www.alexa.com/topsites

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/content/papers/10.5339/qfarc.2018.ICTPD425
2018-03-15
2019-12-15
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