I was recently analyzing Twitter networks and started to create groups according to a certain topic. An example would be the 100 most relevant people for the keyword “snowboarding”. Based on using the Twitter list feature where you can tag people with the word snowboarding the more often people are tagged the more they are relevant for this keyword.
Sharing knowledge in a public way has a long tradition. Analogously there is also a long tradition of the study of communities of practice evolving around the sharing of knowledge and the underlying computer mediated communication (Hildreth, Kimble, & Wright, 1998). Wasko et al (Wasko & Faraj, 2000) find that knowledge exchange is motivated by moral obligation and community interest rather than by narrow self-interest. Focusing on the behavioral rather the structural variables affecting knowledge exchange they find that people participate primarily out of community interest, generalized reciprocity and prosocial behavior. Millen et al (Millen, Fontaine, & Muller, 2002) emphasize the role of communities of practice on the improvement of organizational performance, which is also valid beyond the organizational boundaries. In the software development field such communities also hold a disciplinary background, similar work activities and tools, shared stories, contexts and values. Twitter is only a new way of social interaction between such communities beyond the existing ones (e.g., hallway exchanges and water-cooler conversations, meetings and conferences, brown bag lunches, newsletters, teleconferences, online environments, shared web spaces, email lists, discussion forums, and synchronous chat.). In the form of communities of interests, Henri and Pudelko (Henri & Pudelko, 2003) note a very similar phenomenon of people who are ” assembled around a topic of common interest. Its members take part in the community to exchange information, to obtain answers to personal questions or problems, to improve their understanding of a subject, to share common passions or to play.” Hence analyzing programming communities on Twitter is an ideal laboratory to explore how this new medium affects the flow of information in communities of practice or interest. For this task I have selected in a set of five keywords that represent programming communities, which represent five modern programming languages, which are widely used among software developers:
- I did not collect lists for C/++ because its very noisy as of having only one letter
Those keywords are particularly useful because they are seldomly used outside of context of programming languages and do not stand for other communities that might also be represented in Twitter. Finally investigating how the informal connections and the sharing of information in such communities leads to acquiring social capital which then leads to a better communication relates directly to the research questions. The exploration of communities of practice which are considered to realize social capital especially for members who show, and share expertise and experience provides an interesting field both from a practical but also theoretical view.
For each of those keywords I assembled the 100 most relevant Twitter users according to the above mentioned list feature. The result list is somewhat puzzling (see figure 1) I have visualized it in a so called spring-embedding social network layout. Each node corresponds to a person and the color corresponds to a programming language. The more ties nodes have together the closer they are.
Of course the image is only a small part of the Twitter network, meaning that each of those 100 people are embedded in a bigger network, that is not shown here. To cover that I have calculated the number of ties that the those people have with the “outside” word, which is everything that beyond those 500 people. An overview of the communication has been captured in table 1, which shows the amount of Follower ties, @-replies and retweets for those groups.
Studying the communication pattern I was thinking: So what exactly does this mean? Is it that despite the fact that we are all developers and programmers somewhow we stick to our own turf, and rather neglect what is happening in other domains? Regarding the little theoretical overview towards communities of practice it seems like although there is exchange going on programmers prefer to connect with their own people, simply because the tweets are more relevant, if you do not program in a foreign language.
P.S. This perfectly fits into the homophily or assortative mixing considerations found in sociology. It is still puzzling to find it so emerging for the field of programming.
P.P.S. Normally to analyze such tendencies there is a SNA Metric called External-Internal-Index that calculates a significance how much those ties that we see differ from random distribution. This index also varifies this tendency, yet it is hard to interpret due to the lack of comparable data. I guess I will compare this tendencies with other groups on Twitter.