Title: Bots vs. Wikipedians, Anons vs. Logged-Ins (Redux): A Global Study of Edit Activity on Wikipedia and Wikidata

Authors: Thomas Steiner

Abstract: Wikipedia is a global crowdsourced encyclopedia that at time of writing is available in 287 languages. Wikidata is a likewise global crowdsourced knowledge base that provides shared facts to be used by Wikipedias. In the context of this research, we have developed an application and an underlying Application Programming Interface (API) capable of monitoring realtime edit activity of all language versions of Wikipedia and Wikidata. This application allows us to easily analyze edits in order to answer questions such as “Bots vs. Wikipedians, who edits more?”, “Which is the most anonymously edited Wikipedia?”, or “Who are the bots and what do they edit?”. To the best of our knowledge, this is the first time such an analysis was done for Wikidata and for really all Wikipedias—large and small. According to our results, all Wikipedias and Wikidata together are edited by about 50% bots and by about 23% anonymous users. Wikidata alone accounts for about 48% of the totally observed edits. If we do not consider Wikidata, i.e., if we only look at all Wikipedias, about 15% of all edits are made by bots and 26% of all edits are made by anonymous users. Overall, we found a stabilizing number of 274 active bots during our observation period. Our application is available publicly online at the URL http://wikipedia-edits.herokuapp.com/, its code has been open-sourced under the Apache 2.0 license.

This contribution to OpenSym 2014 will be made available as part of the OpenSym 2014 proceedings on or after August 27, 2014.

Title: Information Evolution in Wikipedia

Authors: Ujwal Gadiraju, Mihai Georgescu, Marco Fisichella, Andrea Ceroni, Kaweh Djafari Naini

Abstract: The Web of data is constantly evolving based on the dynamics of its content. Current Web search engine technologies consider static collections and do not factor in explicitly or implicitly available temporal information, that can be leveraged to gain insights into the dynamics of the data. In this paper, we hypothesize that by employing the temporal aspect as the primary means for capturing the evolution of entities, it is possible to provide entity-based accessibility to Web archives. We empirically show that the edit activity on Wikipedia can be exploited to provide evidence of the evolution of Wikipedia pages over time, both in terms of their content and in terms of their temporally defined relationships, classified in literature as events. Finally, we present results from our extensive analysis of a dataset consisting of 31, 998 Wikipedia pages describing politicians, and observations from in-depth case studies. Our findings reflect the usefulness of leveraging temporal information in order to study the evolution of entities and breed promising grounds for further research.

This contribution to OpenSym 2014 will be made available as part of the OpenSym 2014 proceedings on or after August 27, 2014.