Research:The Rise and Decline
This is an open access summary of a peer reviewed publication:
- Halfaker, A., Geiger, R. S., Morgan, J. T., & Riedl, J. (2013). The rise and decline of an open collaboration system:
- How Wikipedia’s reaction to popularity is causing its decline. American Behavioral Scientist, 57(5), 664-688. PDF
Project Overview Edit
Open collaboration systems like Wikipedia need to maintain a pool of volunteer contributors in order to remain relevant. Despite historically garnering massive numbers of contributions, recent research has shown that the number of active contributors in Wikipedia has entered a steady decline and suggests that declining retention of newcomers is the cause. Through a data-driven approach, this paper presents evidence that several changes that the Wikipedia community made to manage quality and consistency in the face of a massive growth in participation have led to a more restrictive environment for newcomers. Specifically, the restrictiveness of the encyclopedia's primary quality control mechanism and the algorithmic tools used to reject contributions is implicated as a cause of decreased newcomer retention. Also, the community's formal mechanisms for norm articulation are shown to have calcified against changes – especially for newcomers. Recommendations are offered for Wikipedia's community organizers and the Wikimedia Foundation.
- Key methodological features: Content analysis of newcomer work; data analysis and numerical modeling of logs
- Submission to American Behavioral Scientist
- An open licensed summary of the findings.
Key findings Edit
- The decline represents a change in the rate of retention of desirable, good-faith newcomers.
- The proportion of good-faith newcomers who join Wikipedia has not changed since 2006.
- These good-faith newcomers are more likely to have their work rejected.
- This rejection predicts the observed decline in retention.
- Semi-autonomous tools (like en:WP:HUGGLE) are partially at fault.
- Reverting tools are increasingly likely to revert the work of good-faith newcomers.
- These automated reverts exacerbate the negative effects of rejection on retention.
- Users of Huggle tend to not engage in the best practices for discussing reverts.
- New users are being pushed out of policy articulation.
- The formalized process for vetting new policies and changes to policies ensures that newcomers' changes do not survive.
- Newcomers and other editors are moving increasingly toward less formal spaces.
It's no secret that the number of active editors in the English Wikipedia is declining. As the figure below shows, the number of active editors (editors with >= 5 edits/month) abruptly stopped growing in early 2007 and entered a steady, linear decline. Recent research has shown evidence that this transition is rooted in the declining retention of new editors, not a change in the retention of already-experienced old-timers. What is unclear, or was before this work, is why this sudden switch in the retention of new editors took place.
This implicates the changes that the Wikipedia editors made to preserve the quality and consistency of the encyclopedia in causing the decline in retention of desirable newcomers. Below, the results are broken up into a description of three general findings.
The decline in good-faith newcomers Edit
One of the biggest open questions about Wikipedia's newcomer decline was whether it was the result of a natural decline in the quality of newcomers (where lower-quality newcomers were "encouraged" to go elsewhere) or whether changes in how Wikipedia welcomes newcomers was at fault. In order to explore this, we manually categorized the work of 2100 newcomers sampled over the history of the website. With the help of Maryana Pinchuk (User:Accedie), Oliver Keyes (User:Ironholds) and Steven Walling (User:Steven_Walling) we categorized these newcomers into 4 ordinal quality classes based on their first session of editing activity:
- Vandals - Purposefully malicious, out to cause harm
- Bad-faith - Trying to be funny, not here to help or harm
- Good-faith - Trying to be productive, but failing
- Golden - Successfully contributing productively
In the analysis, we simplify these 4 categories into desirable newcomers (good-faith & golden) and undesirable newcomers (bad-faith & vandal).
The three plots above make a few things apparent:
- The proportion[unclear] of desirable newcomers entering Wikipedia has not changed since 2006
- These desirable good newcomers are more likely than their ancestors to have their first contributions rejected
- The decline in good newcomers is the result of a decline in desirable newcomers. Undesirable newcomers (not shown) retention rate stays constant.
Efficient quality control -> impersonal newcomer experience Edit
In order to maintain the quality of encyclopedic content in the face of exponential growth in the contributor community, Wikipedians developed automated (bots) and semi-automated (Huggle, Twinkle, etc.) tools to make the work of rejecting undesirable contributions efficient (read: take as little human effort as possible). These tools are apparently effective at their job. Recent research has shown that the time between when vandalism is posted and reverted is very short (median: ~2 minutes) and has been steadily falling. However, we suspected that the ways in which efficiency was achieved with these tools was part of the problem.
Recent research by Geiger et al. has shown that an increasing number of newcomers' first contact with someone in Wikipedia is with the business end of an algorithmic quality control tool. First messages to new editors shows the growing use of automated tools to send messages to newcomers. We suspected that the increasing rate of interactions between desirable newcomers (described in the previous section) and algorithmic tools was exacerbating the effect of rejection on retention.
The plots below describe two analyses that support this suspicion. Desirable newcomer reverts by tools shows that desirable newcomers are increasingly likely to have their work rejected by an algorithmic quality control tool and that the growth in the use of these tools to reject newcomer work coincides with the beginning of the decline (early 2007). BRD reciprocation rate shows something a little more nuanced. We hypothesized that there would be a behavioral pattern explaining why reverts by algorithmic tools affect newcomers more strongly. Wikipedia's Bold, Revert, Discuss cycle (BRD) recommends a process by which editors may efficiently do work and resolve conflicts. As the figure shows, editors who revert using Huggle are much less likely to participate in a BRD discussion (~7%) than editors who revert manually (~60%).
Formalization of norms against newcomer changes Edit
Recent work studying Wikipedia's policies and guidelines has suggested that the process by which these rules and recommendations are vetted reflect community concerns and decentralization in governance participation. However, it's also been shown that experienced Wikipedians have more power over interpretation of the rules and that policy and guideline creation has slowed since 2006 We suspected that, although natural and generally beneficial, that this calcification of the rules of Wikipedia would bias new articulation against newcomer concerns.
To explore this hypothesis, we built a model predicting which edits to policies and guidelines were likely to be reverted. In short, this model showed us that:
- Over time, editor experience has become a more important success factor
- Unlike formal policies and guidelines, essays have not suffered such a crackdown
While we do not suggest that the rules of Wikipedia be open to reinterpretation by newcomers, we advocate that concern should be allocated for newcomers with a legitimate interest in changing the way that Wikipedia works. We argue that the results covered in the previous two sections suggest how important it is that newcomers have a say in how they are treated.
Thanks to Maryana Pinchuk, Steven Walling, and Oliver Keyes for their insightful comments on the research project as it developed and for helping us to manually label newcomer activities.
- Bongwon Suh, Gregorio Convertino, Ed H. Chi, and Peter Pirolli. 2009. The singularity is not near: slowing growth of Wikipedia. In Proceedings of the 5th International Symposium on Wikis and Open Collaboration (WikiSym '09). ACM, New York, NY, USA, , Article 8 , 10 pages. 10.1145/1641309.1641322 [pdf]
- The Wikimedia Foundation, The Editor Trends Study http://strategy.wikimedia.org/wiki/Editor_Trends_Study
- Geiger, R. S., Halfaker, A., Pinchuk, M., & Walling, S. 2012. Defense Mechanism or Socialization Tactic? Improving Wikipedia's Notifications to Rejected Contributors. In Proceedings of ICWSM. IEEE http://www.aaai.org/ocs/index.php/ICWSM/ICWSM12/paper/view/4657
- Aniket Kittur, Bongwon Suh, Bryan A. Pendleton, and Ed H. Chi. 2007. He says, she says: conflict and coordination in Wikipedia. In Proceedings CHI. ACM, New York, NY, USA, 453-462. 10.1145/1240624.1240698
- Andrew G. West, Sampath Kannan, and Insup Lee. 2010. STiki: an anti-vandalism tool for Wikipedia using spatio-temporal analysis of revision metadata. In Proceedings of WikiSym. ACM, New York, NY, USA, , Article 32 , 2 pages. 10.1145/1832772.1832814
- The reader is encouraged to examine en:WP:BRD before continuing.
- Beschastnikh, I., Kriplean, T., McDonald, D. W. (2008). Wikipedia Self-Governance in Action: Motivating the Policy Lens. ICWSM.
- Kriplean, T., Beschastnikh, I., McDonald, D. W., & Golder, S. A., (2007) Community, consensus, coercion, control: cs*w or how policy mediates mass participation. GROUP (pp. 167-177).
- Forte, A., Larco, V., & Bruckman, A. (2009). Decentralization in Wikipedia Governance. Journal Manage. Info. Sys. 26(1), 49-72.
- See the full description for more details.