Online Community Metrics: Tips and Techniques for Measuring Participation
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Do you know what people are really doing in your open source project? Having good community data and metrics for your open source project is a great way to understand what works and what needs improvement over time, and metrics can also be a nice way to highlight contributions from key project members. This session will focus on tips and techniques for collecting and analyzing metrics from tools commonly used by open source projects. It’s like people watching, but with data.
Speaker: Dawn Foster
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Sumana's session notes:
Dawn Foster's fantastic "Online Community Metrics: Tips and Techniques for Measuring Participation" was -- to all the community managers in the room -- worth the price of admission on its own. Hit the slides for great pointers to MeeGo's statistics, MLStats for mailing list analysis, irssistats for IRC analysis, and more.
Is the Pypi.python.org package the same as at LibreSoft?
It's useful to have a single sign-on for committing, fora, etc. MeeGo seems to have this.
MeeGo has about two yearly conferences, and dozens of local meetups that contributors organize themselves.
Dawn finds it's not so useful for her in particular to look at social media as any sort of measurable activity, because there's so much noise from users who aren't contributors who talk about MeeGo. But your project may vary.
Tip: compare two release cycles, not two months in a row!
MLStats takes Mailman archives and sucks them into MySQL databases so you can query them. Dawn queries the DB, dumps to CSV, uses a spreadsheet program on those, and then outputs graphs.
MediaWiki has some statistics built in. Most useful: Active users, Page edits since wiki's inception, and Content pages. Watch out for big scrubs that throw off the stats by touching many pages at once.
Regarding analytics, especially Google Analytics, look at Dawn Foster's site & blog posts.
Dave Neary & Dawn Foster are working on a metrics dashboard that should be usable & releasable later this summer or fall. Dave & Dawn will talk about it at OSCON.
Go with the messy giant bash script until you figure out what sort of data you'll want, then optimize & make something more pretty, accessible, sustainable.
Don't report too often -- Dawn suggests quarterly reports, or every other month.