Cookies?
Library Header Image
LSE Research Online LSE Library Services

Even good bots fight: the case of Wikipedia

Tsvetkova, Milena, García-Gavilanes, Ruth, Floridi, Luciano and Yasseri, Taha (2017) Even good bots fight: the case of Wikipedia. PLOS ONE, 12 (2). e0171774. ISSN 1932-6203

[img] Text (Even good bots fight) - Published Version
Available under License Creative Commons Attribution.

Download (2MB)
Identification Number: 10.1371/journal.pone.0171774

Abstract

In recent years, there has been a huge increase in the number of bots online, varying from Web crawlers for search engines, to chatbots for online customer service, spambots on social media, and content-editing bots in online collaboration communities. The online world has turned into an ecosystem of bots. However, our knowledge of how these automated agents are interacting with each other is rather poor. Bots are predictable automatons that do not have the capacity for emotions, meaning-making, creativity, and sociality and it is hence natural to expect interactions between bots to be relatively predictable and uneventful. In this article, we analyze the interactions between bots that edit articles on Wikipedia. We track the extent to which bots undid each other’s edits over the period 2001–2010, model how pairs of bots interact over time, and identify different types of interaction trajectories. We find that, although Wikipedia bots are intended to support the encyclopedia, they often undo each other’s edits and these sterile “fights” may sometimes continue for years. Unlike humans on Wikipedia, bots’ interactions tend to occur over longer periods of time and to be more reciprocated. Yet, just like humans, bots in different cultural environments may behave differently. Our research suggests that even relatively “dumb” bots may give rise to complex interactions, and this carries important implications for Artificial Intelligence research. Understanding what affects bot-bot interactions is crucial for managing social media well, providing adequate cyber-security, and designing well functioning autonomous vehicles.

Item Type: Article
Official URL: http://journals.plos.org/plosone/
Additional Information: © 2017 The Authors © CC BY 4.0
Divisions: Methodology
Subjects: H Social Sciences > H Social Sciences (General)
Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4050 Electronic information resources
Sets: Departments > Methodology
Date Deposited: 12 May 2017 10:37
Last Modified: 20 Jun 2020 02:27
Projects: 645043
Funders: European Union’s Horizon 2020
URI: http://eprints.lse.ac.uk/id/eprint/76710

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics