Learning and Evaluation/Evaluation reports/2015/Editathons/Limitations

Edit-a-thons

Summary

Limitations

Inputs

Outputs

Outcomes

Key findings

Appendix

On this page, you will find answers to: What is an Edit-a-thon? How deep do the data go? What are the programs goals?

Program basics and history	MBA Edit-a-thon in Lyon, 2014. Edit-a-thons are outreach events that bring together anyone interested in editing Wikimedia projects to edit in a collaborative setting. These events, which typically last less than a day, provide a social environment for new and experienced editors to edit together, often about a specific subject matter. Many events take place in educational and cultural facilities, such as libraries, museums, and universities, when others might take place in offices buildings, homes, and public venues such as cafes and restaurants. Sometimes edit-a-thons are combined with training lessons, where experienced Wikipedians educate participants about the basic "how-to's" on editing, followed by an editing session. Other events might include backstage tours of cultural institutions that are hosting the event, followed by editing, or just a simple session where participants start editing upon arrival at the venue. An early edit-a-thon was proposed on English Wikipedia in February 2004. User:Jimbo proposed a library-based Editing Weekend in mid-2004. Neither were pursued at the time. In 2009, Australia's Powerhouse Museum hosted what is believed to be the first GLAM edit-a-thon. Wikipedians were given a tour of the museum, met with curators, were able to take photographs, and improved and created articles related to the Powerhouse and its collections. The Wikipedian who coordinated the Powerhouse event, Wittylama, eventually organized another event at the British Museum, which featured a tour of the museum and a contest focused around improving the article about the Hoxne Hoard. Called the "Hoxne Challenge," it has served as an inspiration for edit-a-thons in partnership with cultural institutions since. One of the first events to use the term "edit-a-thon" was the British Library edit-a-thon in January 2011, and the frequency of such events grew over the following years. Both the term “editathon” and “edit-a-thon” are used to refer to these events. For the sake of consistency, we used “edit-a-thon” throughout this report.
Response rates, data quality, report limitations	Data were obtained for 121 edit-a-thons. The metrics in these reports are meant to give a general sense of the landscape of edit-a-thons, and represent only a handful of possible measures for understanding these events and their results. The data in this report were both reported by program leaders and mined from Wikimedia project pages. On measures “The numeric data doesn't do justice to some important outcomes of edit-a-thons. The more events we have organized, the clearer it has become that they are an important means to spread awareness and positive perceptions on Wikimedia and to build GLAM partnerships that can be deepened in the future. In our 2 edit-a-thon programmes included in this report, we collaborated with 7 GLAMs (5 of them new partners). After the events all of them reported that they are interested in future collaboration, content donations, or possibly a Wikipedian in residence. How to make this progress visible?" Sanna Hirvonen former GLAM coordinator, Wikimedia Finland A total of 144 unique edit-a-thon events were identified for inclusion in this report. However, data could only be obtained for 121 of these events. The start dates of those included ranged from 7 September 2013 to 6 December 2014. Data on Edit-a-thons were collected from three sources: (1) from the program leaders directly; (2) from publicly available information on organizer websites and on-wiki reports; and (3) through WMF Labs tools such as Wikimetrics, Quarry and Catscan. The data obtained included: number of participants, event start and end times, number of bytes added and removed, number of pages created, number of pages improved, information on the goals of edit-a-thons, information on inputs to each edit-a-thon. Only a minority of events reported key inputs such as budget, staff hours, and volunteer hours, and this information cannot be mined. Thus, while we explore these inputs, we cannot draw many strong conclusions about program scale or how these inputs affect program success. In addition, the data for edit-a-thons are not normally distributed, the distributions are, for the most part, skewed. This is partly due to small sample size and partly to natural variation, but does not allow for comparison of means or analyses that require normal distributions. Instead, we present the ‘’median’’ and ranges of metrics and use the term ‘’average’’ to refer to the median average, since the median is a more ’’statistically robust’’ average than the ’’arithmetic mean’’. To give a complete picture of the distribution of data, we include the means and standard deviations as references. To see the summary statistics of data reported and mined, including counts, sums, arithmetic means and ‘’standard deviations’’, see the appendix.
Priority goals	Program leaders reported a total of 18 ‘’priority goals’’, with ‘’building and engaging community’’ and ‘’increasing awareness of Wikimedia projects being the most common.’’ We asked program leaders to select their priority goals for edit-a-thons. Program leaders reported ‘’priority goals’’ for 32 edit-a-thons and the number of ‘’priority goals’’ identified per event ranged from 2 to 15 with an average of 5. The table below lists the priority goals in order of frequency they were selected. Priority Goals. Goals noted as priority by edit-a-thon program leaders, listed by most frequently noted. On goals “Edit-a-thons are a means to spread awareness and positive perceptions on Wikimedia among professionals. They help us build GLAM partnerships." Sanna Hirvonen Wikimedia Finland former GLAM program coordinator A total of 18 different goals were selected, with 5 goals being selected for over 70% of events. The most commonly selected goal was building and engaging community (94%), followed by increasing awareness of Wikimedia projects (81%), increasing diversity of information coverage (78%), making contributing easier (75%), and increasing diversity of participants (75%).