Learning patterns/Prioritizing articles for improvement
What problem does this solve?
Prioritizing articles when we are trying to improve quality is tough task. Especially when there are many articles and volunteers think that they should spend their time in improving most prior article to the project.
What is the solution?
To run a prioritizing exercise to find out importance of the articles based on the parameters they fixed upon. Wikipedians who participate in this exercise will get fixed score based on number of the articles considering for exercise and participants. Then by considering pre-discussed parameters participants allocate score for articles they prioritize. Finally volunteers who are contributing to project (often both participents of priority excersize and volunteers of project are same) will have a priority list if they wish to follow.
Things to consider
- Limit Numbers: As exercise is for a known number of articles and also looking for another number of priority articles say, one has to fix number of participants to prioritize and points or score that participant can allocate accordingly. One can also have a minimum and maximum number of points that one can give to an article. Well thought limits on these numbers are necessary.
- Discuss and fix parameters: Parameters for the prioritization should be discussed and fixed. These parameters can be based on importance or condition of article or anything that suits final quality improvement activity. Having parameters help making exercise more meaningful.
- If articles that has to be prioritized are numerous then one can consider selecting articles in batches to prioritizing exercise and can repeat this till all articles get prioritized.
- Create a table where x-axis will be with all the articles that has to be prioritized and y axis with participants names. Finally participants edit table and give their priority points for evaluating articles.
When to use
- Improving quality of machine artilces in Telugu Wikipedia - There are nearly 1944 article which were machine translated as part of google's project in 2009-11. Wikipedians found out serious quality issues in these articles and tried several times to improve the articles. To work on this project, identifying priority is also one of the major issue. Some of the Wikipedians who contributed to this project suggested that prioritizing these articles would encourage community to contribute. So, by selecting 116 articles each time for prioritization and 5 Wikipedians to select priority articles with 60 positive and 60 negative points each on hand. As community found out some of these articles should be deleted because of notability and other issues, negative points helps identifying articles for deletion proposals and positive points to quality improvement. parameters were discussed and participants who prioritize articles considered them. Finally in first round, 51 articles for improvement and 39 articles for deletion requests were considered. People who contributed by prioritization are also contributing to improving the articles.
- Prioritizing books for collaborative effort to digitize: Telugu Wikisource community members are working in collaborative effort to complete digitization of several books and create downloadable eBooks. For this effort, community thought that prioritizing books will be helpful because to make effort on important books. User:Arjunaraoc created a framework where limited number of wikisourcers can prioritize books based on some parameters. Every participant will have 10 marks where he can allocate each book 1-3 marks. Prioritized books will be turned to downloadable eBook by collaborative effort of community members.