Learning patterns/Analysing effects of offline meetups
What problem does this solve?
Offline face-to-face meetings are an important part of the Wikimedia community. However, there are only few systematic assessments of their effects of such meeting on online behaviour as it can be difficult to obtain the meeting data. Once collected, statistical methods can be used to assess whether the offline meetups have an effect on the online behaviour of Wikipedians. In this learning pattern, I want to highlight some methods how the meeting data can be analysed, and discuss problems and limitations which must be kept in mind when working with meetup data.
What is the solution?
Effect on what?
Like in any other research project, the first step is to identify what you are actually interested in and which research question you want to answer. Do you want to know...
- whether users make more edits after attending a meetup?
- whether users make higher quality edits after attening a meetup?
- whether users remain active for longer after attending an edithaton?
- whether users know the rules of Wikipedia better after attending an edithaton?
- whether users are more likely to become administrator after having met other administrators face-to-face?
- whether users start (or stop) using the talk page to interact with those that they have met?
Many questions can be asked about the effects of offline meetups on the online behaviour of Wikipedians. To identify the effects, different data and strategies of analysis might be needed. This learning pattern will outline approaches and relevant thigns to consider irrespective of the specific research question. Nevertheless, before starting any analysis, it is important to make your questions and aims clear.
Work in progress, being continued
Identifying effects
Things to consider
When to use
- Use this pattern when you want to better understand offline meetups of a Wikipedia community.
- I have used this approach in my project.