Detecting Communities in Science Blogs Christina K. Pikas [email_address] http://terpconnect.umd.edu/~cpikas/ScienceBlogging

Problem Area eScience includes using electronic tools both for conducting science and for communicating about science There are an abundance of tools both online and offline to help scientists communicate Lots of scientists and members of the interested public maintain blogs (~2500?) Ultimate Questions: Why? With whom are scientists communicating? What are scientists communicating about? What is the value to the scientists and to science?

eScience includes using electronic tools both for conducting science and for communicating about science

There are an abundance of tools both online and offline to help scientists communicate

Lots of scientists and members of the interested public maintain blogs (~2500?)

Ultimate Questions: Why? With whom are scientists communicating? What are scientists communicating about? What is the value to the scientists and to science?

Specific Problem Addressed What is the nature of the science blogosphere? What is its shape? Who are the central participants? What is the connectivity? Where are the potential information flows?

What is the nature of the science blogosphere?

What is its shape?

Who are the central participants?

What is the connectivity?

Where are the potential information flows?

Outline Background Methods Data gathering Analysis Results Discussion

Background

Methods

Data gathering

Analysis

Results

Discussion

Background: Blogs Defined by format Individual posts, with permanent URLs Comments Links In content In blogroll In comments and trackbacks Community develops around single blogs and among blogs through commenting

Defined by format

Individual posts, with permanent URLs

Comments

Links

In content

In blogroll

In comments and trackbacks

Community develops around single blogs and among blogs through commenting

Posts Links to Static Pages Links and automatically generated content http://dorigo.wordpress.com/

Access to posts by search and older posts using the calendar A list of most recent posts is automatically generated

A list of categories the blogger used to describe his posts. Clicking will list all of the posts in that category. The blogroll is a list of blogs the author reads or endorses to some extent. Access to the older posts by month.

The individual post page looks a lot like the blog home page

But with Comments, which may be signed with the the commenter’s URL And a form to leave your own comment. Typically your e-mail will not appear on the site

Background: Social Network Analysis Uses connections between actors to understand potential flows of information and influence Uses graph theoretic methods to find Central or prestigious actors Cohesive subgroups including communities

Uses connections between actors to understand potential flows of information and influence

Uses graph theoretic methods to find

Central or prestigious actors

Cohesive subgroups including communities

Methods: Sample Selection Operational Definition of Science Blog Blogs maintained by scientists that deal with any aspect of being a scientist Blogs about scientific topics by non-scientists Omitted Primarily political speech Ones maintained by corporations Non-English language

Operational Definition of Science Blog

Blogs maintained by scientists that deal with any aspect of being a scientist

Blogs about scientific topics by non-scientists

Omitted

Primarily political speech

Ones maintained by corporations

Non-English language

Methods: Data Gathering Two Networks: Links and Commenters Link Data (Blogroll) Used seed list developed in previous study using directories and searches Snowball sampled using links from blogrolls Visited and copied links Commenter Data Selected most central blogs from blogroll data Used Perl scripts to pull the commenter URLs from each of the last 10 posts

Two Networks: Links and Commenters

Link Data (Blogroll)

Used seed list developed in previous study using directories and searches

Snowball sampled using links from blogrolls

Visited and copied links

Commenter Data

Selected most central blogs from blogroll data

Used Perl scripts to pull the commenter URLs from each of the last 10 posts

Methods: Analysis Used social network analysis and graphing software Examined graph and calculated basic descriptive statistics Found centrality and prestige measures Degree: the links in and out Betweenness: the number of shortest paths that flow through that node Closeness: short paths to other nodes

Used social network analysis and graphing software

Examined graph and calculated basic descriptive statistics

Found centrality and prestige measures

Degree: the links in and out

Betweenness: the number of shortest paths that flow through that node

Closeness: short paths to other nodes

Methods: Analysis Located cohesive subgroups Link methods Components LS Sets Clustering methods Community detection techniques Newman-Girvan Spin Glass

Located cohesive subgroups

Link methods

Components

LS Sets

Clustering methods

Community detection techniques

Newman-Girvan

Spin Glass

Results: Link Analysis (Blogroll) One large component There were 1091 nodes, 6621 arcs Diameter is 9 In-degree ranges from 1 to 292, with the median in-degree of 3, and mean 6 10 of the top 20 blogs by in-degree are authored or co-authored by women 4 of the top 5 blogs by closeness are authored or co-authored by women

One large component

There were 1091 nodes, 6621 arcs

Diameter is 9

In-degree ranges from 1 to 292, with the median in-degree of 3, and mean 6

10 of the top 20 blogs by in-degree are authored or co-authored by women

4 of the top 5 blogs by closeness are authored or co-authored by women

Results: Commenter 5 components, the largest with 911, others with 11 or fewer nodes 938 nodes (starting with the 46), 1152 arcs The largest component has a diameter of 5

5 components, the largest with 911, others with 11 or fewer nodes

938 nodes (starting with the 46), 1152 arcs

The largest component has a diameter of 5

Discussion: Links (Blogroll) Most of the blogs were connected in one dense component A result of the diffusion of blogs? There were a few very central blogs, and then many less central Typical skewed distribution The community of women scientists merits further study

Most of the blogs were connected in one dense component

A result of the diffusion of blogs?

There were a few very central blogs, and then many less central

Typical skewed distribution

The community of women scientists merits further study

Discussion: Commenters Analysis easily located a notorious commenter who leaves incendiary comments on physics and chemistry blogs High out-degree, no links in Traffic on the women scientist blogs is more uniform, with frequent comments that are widely distributed among the blogs Indicates a different use

Analysis easily located a notorious commenter who leaves incendiary comments on physics and chemistry blogs

High out-degree, no links in

Traffic on the women scientist blogs is more uniform, with frequent comments that are widely distributed among the blogs

Indicates a different use

Take Home Messages The science blogosphere is densely connected with many opportunities for influence and information diffusion Communities tend to form within disciplinary boundaries An exception is the community of women scientist bloggers who are from many different disciplines

The science blogosphere is densely connected with many opportunities for influence and information diffusion

Communities tend to form within disciplinary boundaries

An exception is the community of women scientist bloggers who are from many different disciplines

Acknowledgements Thanks to Dr. Jen Golbeck for supervising this work as part of an independent study Thanks also to Dr. Alan Neustadtl for SNA advice Dr. Dagobert Soergel for research advice

Thanks to Dr. Jen Golbeck for supervising this work as part of an independent study

Thanks also to

Dr. Alan Neustadtl for SNA advice

Dr. Dagobert Soergel for research advice

Christina K. Pikas Doctoral Student University of Maryland College of Information Studies [email_address] http://terpconnect.umd.edu/~cpikas/ScienceBlogging

Christina K. Pikas

Doctoral Student

University of Maryland

College of Information Studies

[email_address]

http://terpconnect.umd.edu/~cpikas/ScienceBlogging