Hi Georg Thanks for the interest. I have some minor edits to do so will do those and get it posted later this week. It's 31 pages long so might see if I can do a summary version too.
Thanks Sharan On 2018/12/22 18:13:42, Georg Link <gl...@unomaha.edu> wrote: > Hi Sharan, > > Interesting setup. I would like to read the paper :) > > Happy Holidays, > Georg > > On Sat, Dec 22, 2018 at 3:59 AM Sharan Foga <sha...@apache.org> wrote: > > > Hi All > > > > I’m sorry I haven’t been that active on this recently, this has been > > caused by a few things happening that meant that I needed to focus my time > > and effort elsewhere. > > > > One of the things that my time has been focussed on is on assignment for > > my MBA where I have used Kibble as my research tool. > > > > To give you some background. > > > > My paper was focussed on the transmission of culture and values in open > > source and I wanted to create a baseline to be able to measure cultural > > indicators. So how can Kibble help? (I hear you ask :-), so let me explain > > a little. > > > > Kibble includes the following: > > > > - Pony Factor – which is an indicator of the diversity of key project > > contributors. So thinking of the Apache culture and its values, we would be > > looking to see the Pony Factor grow over time as a project community grows > > and accepts new conributors. There is also a meta Pony Factor which tries > > to measure the diversity of the companies contributing. > > > > - Sentient / Mood Analysis – which indicates the mood of the mailing list > > communications. > > > > - Key Phrase Extraction (KPE) – which pulls out important words or phrases > > that summarise the main topics or ideas that are being discussed on the > > mailing list. > > > > - Contributor Retention – this is divided into two parts; one is the > > length of time contributors have been in a community and two; a breakdown > > of active, retained, people who have left a community and also those that > > have returned after a breakdown > > > > > > * Methodology * > > What I’ve done is this: > > > > Apache culture was created as a result of the Apache Webserver project. So > > I used this Kibble data for this project to create a cultural baseline > > based on the above indicators. > > > > I then took two sets of Apache projects (one group that have been ASF Top > > Level projects for over 5 years and one group that have been Apache Top > > Level projects for less than 5 years) and measured their indicators in > > Kibble. > > > > I then compared them both to the Apache webserver cultural baseline. > > > > My results were interesting and the most significant thing I can mention > > is that the +1 indicator, which is something culturally unique to Apache as > > a consensus indicator came out as part of the KPE analysis is all 3 > > groups.(So some cultural transmission is happening!) > > > > It also seemed to indicate that the older projects were better at some of > > the Apache cultural aspects e.g the recognition of merit, where the younger > > projects were amazingly successful at community growth. > > > > I’ll load my paper maybe onto the wiki for people to look at (and probably > > critique :-) before I share it more widely within Apache. > > > > Thanks > > Sharan > > > > > > > > > > -- > Georg J.P. Link > PhD Candidate > College of Information Science and Technology | PKI 367 > University of Nebraska at Omaha | www.unomaha.edu > he/him >
