“Never doubt that a small group of thoughtful, committed citizens can change the world. Indeed, it...

“Never doubt that a small group of thoughtful,

committed citizens can change the world. Indeed, it is the only thing that ever

has.”--Margaret Mead

Thank You R Hackers of NYC

Harvesting & Analyzing Interaction Data in R:

The Case of MyLyn

Sean P. Goggins, PhDDrexel University

outdoors@acm.org

MyLyn Research Collaborators:

Peppo Valetto, PhD (PI) & Kelly Blincoe

I Study Small GroupsI use electronic trace data, interviews, field notes, electronic content & surveys for raw data

Coolest Open* Data to Me Group’s Emerging & Evolving

Group Formation & Development

The long tail of social computing, which I describe as everything *except* Wikipedia & Facebook

Groups constructing knowledge, creating information and forming identity.

*Available, but not always easy to get in an analyzable form

Points Harvesting Small, Open Data [MyLyn]

Analyzing Temporal Changes in the MyLyn Network

Libraries Used & Source Code StatNet

iGraph

R Sourcecode and Data will be available for download at http://www.groupinformatics.org . If you use this data or scripts please cite:

Goggins, S. P., Laffey, J., Amelung, C., and Gallagher, M. 2010. Social Intelligence In Completely Online Groups. IEEE International Conference on Social Computing. 500-507. DOI=10.1109/SocialCom.2010.79.

Blincoe, K., Valetto, G., and Goggins, S. 2011. Leveraging Task Contexts for Managing Developers’ Coordination. Under Review.

Data for RAn Example From the MyLyn Project

More About MyLyn: http://tasktop.com/blog/http://www.eclipse.org/mylyn/

Bug Database

HTML Parser

MySQL Database

MyLyn ContextUploads

.zip file

Talk Cues

TalkWork

Coordination Requirements & Dependencies

MyLyn Data Has 2 Advantages for Analysis compared to source Control systems analysis:1. You see files *viewed*

together2. Discourse on a Bug is

directly connected to the files read and edited1. Closer connection

between analysis of work & talk.

Harvesting Data for RAn Example From the MyLyn Project

MyLyn Interaction Datamart

Interaction Warehouse

TalkWork

Analyzing Open Data with R

An Example From the MyLyn Project

Analysis Tools Eight Mylyn Releases (Temporal Analysis)

R Packages Used TNET

iGraph

Statnet

Weighted Network: TNET

The Dense Graph (Work) Developers create a dense graph. Not a

complete graph, but dense.

A Sparser Graph (Talk) Commenter's create a sparse graph

Release One (2.0) Analysis

CodeDiscussion

WorkTalk

iGraph

Release 1

STATNET for Discussion StatNet

Red = Bug CommenterBlue = Bug Opener

StatNET

Release 1

Release OneWork & Talk

Release 1 (2.0) iGraph & Statnet

Clusters

In Degree & Out Degree

iGraph

StatNET

Release 1

Google Summer Coder

Release One (2.0): Filtered

Code Discussion

304, 373, 399 & 143 formThe Strongest ConnectionsIn both networks

WorkRelease 1

Release One (2.0): Filtered

Code Discussion

304, 373, 399 & 143 formThe Strongest ConnectionsIn both networks

Google Summer Coder

TalkWork

457, 391 & 159 – Comment & Open

Release 1

Compare Over TimeFirst & Last Release

Release 1 (2.0) Compared to Release 8 (3.3)

304, 399, 143, 159, 173, 373

399, 118, 304, 159, 391, 416StatNET & ordinary plotting

Release 1

Release 8

Release 1 (2.0) Compared to Release 8 (3.3)

Two disconnectedGraphs in release 8

304, 373, 399 & 143

Release 1

Release 8

143 & 304 disengagedOr missing entirely

iGraph

Release EightWork & Talk

Release 8 (3.3): Filtered

Discussion

Nobody is“Just Blue”

Release 8

Release 8 (3.3): Filtered

Discussion

Notice 416 in Talk & Second Coder Graph

Release 8

Clusters

In Degree & Out Degree

iGraph

StatNET

Release 8 (3.3) iGraph & Statnet

399, 118 & 159 are significant, But play with different clusters of Other people.

BlueCluste

Release 8

Releases One EightHigh Level Views Over Time

Discussion, Releases 1 – 8

Where there is no color,There are multiple, incompleteGraphs.

Code, Releases 1 – 8

One Possible explanation: A few centralPeople who slowly butObservably begin to engageOther contributors inAn open source softwareDevelopment project.

Structure evolvesKey Groups Evolve

iGraph

Next Step: The StoryBut that’s the research part, not the cool “R Stuff” Part

The People

399304

Our next step is piecing together a narrative about the groups that emerged on this project, and describing each of the individuals. This is all open data. When we finish this part, we will publish one or more papers. For now, Let’s look at the cool “R Stuff”

Interaction Traces from Small Groups: The Case

of MyLyn

Sean P. Goggins, PhDDrexel University

outdoors@acm.org

Collaborators:

Peppo Valetto, PhD & Kelly Blincoe

Questions? In the after session.

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