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Wikipedia DOI 93.3% 22 20 90% We proposed a method to identify the edits adding bibliographic references to Wikipedia. The proposed method consists of the following steps. (1) The method extracts the references and matches them to a bibliographic database to build the basic data set. (2) It obtains the full revision history of the page that includes the references from dump data of Wikipedia. It also extracts identifiers and titles for each reference from the basic data set. (3) The method gets the candidate edits adding the references by using the ways, which use either identifiers or titles. (4) The method selects the oldest one as the edit adding the reference. We evaluated the proposed method by using the data set based on DOI links referenced on English Wikipedia. As a result, the accuracy was 93.3% as a whole and over 90% in 20 out of 22 research fields. We showed that the proposed method was able to identify the edits adding bibliographic references at a high accuracy regardless of research fields.

Wikipedia DOI (1) DOI (2) DOI 93 ESI 22 User 34,062 Bot 31 IP () 16,349 DOI User Bot 0.93 We aimed at clarifying the characteristics of the Wikipedia editors who had added Digital Object Identifier (DOI) links to English Wikipedia as scholarly bibliographic references. The results are summarized as follows: (1) Approximately 930 thousand items classifiable into 22 research fields based on the Essential Science Indicators are identified by using DOI links. These items were added by 34,062 users, 31 bots, and 16,349 IP users. (2) Concentration in the number of DOI links on English Wikipedia added by Wikipedia editors is high as a whole (Gini coefficient 0.93), and most research fields' values are also high in common, due to the editors who added DOI links systematically to the existing references on a large scale.

Wikipedia 2011 4 11 () 1 Wiki Education We conducted a time-series analysis to clarify the sustainability for adding scholarly bibliographic references to English Wikipedia (enwiki). The results are summarized as follows: The characteristics of the trends between the edits in enwiki as a whole and the adding the references are different in the point that the latter keeps a certain scale at recent years. The number of editors adding the references has seasonal growth trends in April and November every year since 2011. The majority of new editors for adding the references contribute for single month only, but the scale of the editors remains flat in recent years. These characteristics in the editors adding the references seem to be affected by the participants of Wiki Education, so adding the references would be sustainable as long as these activities continue.

Referencing scholarly documents as information sources on Wikipedia is important because it supports or improves the quality of Wikipedia content. Several studies have been conducted regarding scholarly references on Wikipedia; however, little is known of the editors and their edits contributing to add the scholarly references on Wikipedia. In this study, we develop a methodology to detect the oldest scholarly reference added to Wikipedia articles by which a certain paper is uniquely identifiable as the “first appearance of the scholarly reference.” We identified the first appearances of 923,894 scholarly references (611,119 unique DOIs) in 180,795 unique pages on English Wikipedia as of March 1, 2017 and stored them in the dataset. Moreover, we assessed the precision of the dataset, which was highly precise regardless of the research field. Finally, we demonstrate the potential of our dataset. This dataset is unique and attracts those who are interested in how the scholarly references on Wikipedia grew and which editors added them.