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Transcript of Sunbelt05
Social Network Dynamics in the Blogosphere
The Blog Research on Genre (BROG) Project
School of Library and Information Science
Indiana University Bloomington
BROG project members
• Susan Herring• Inna Kouper• Sarah Mercure• John Paolillo• Lois Ann Scheidt• Peter Welsch• Elijah Wright
The Blogosphere
1. The collective term encompassing all weblogs(cf. blog biosphere or ecosystem)
2. The “intellectual cyberspace” inhabited by bloggers(Wm. Quick, 2001)
3. “Blogs as a community; blogs as a social network”(www.samizdata.net)
Previous research
• One-third of blogs have no hyperlinks
• Small part of the blogosphere is densely interlinked
• ‘A-list’ blogs are central in network
• Cliques exist
• ‘Conversation’ between blogs is sporadic over time
(Efimova & de Moor, 2005; Herring et al., 2004, 2005; Kumar et al., 2003)
BUT: No previous research on change over time in blog networks
Research question
• How do networks of links among blogs change over time?– How quickly?– To what extent?– In what ways?
Sampling method
• Random sample of 4 blogs followed by snowball sample out 3 levels from random blogs
• 3 samples at 4-month intervals– April, August, December 2004
– samples 2 and 3 automated
– 5387, 4900, 4367 unique URLS per sample
(~10,000 total unique URLs)
Source blogs
a) pencilinyourhand.blogspot.com
b) www.danm.us/blog
c) www.mysocalledblog.com
d) orangetang.org/erica/blogger.html
Analytical methods
• Content analysis– 300 random, 150 core blogs (17+ in-links)
• Themes: current events, politics, religion, technology, etc.
• Blog type: personal journal, filter, k-log, mixed, other
• Gender of blog author
Results compared for three samples
Analytical methods (cont.)
• Social network analysis (Degenne & Forsé, 1999)
– based on links in sidebars (‘blogrolls’)• Centrality• Reciprocity
• Visualization of network core– blogs with 10+ in-links– Kamada-Kawai layout in R
Results compared for three samples
Content analysis: Random subsample
• Themes– Personal > current events/politics > technology >
religion
• Blog type– Filter - avg. 42%, increasing over time– Personal journal - avg. 38%, decreasing over time
• Gender of blog author– Male - avg. 65%, increasing over time
Cf. Herring et al. (2004)– 70% of blogs are personal journals;13% are filters– 50% of blog authors are female
Content analysis: Core sample
• Themes– Religion > current events/politics > personal >
technology
• Blog type– Filter - avg. 49%, increasing over time– personal journal - avg. 15.6%, decreasing over time
• Gender of blog author– Male - avg. 66%
Core: blogs with 17+ in-links
Content analysis: Comparison
• Random subsample– few in-links (peripheral to network)few in-links (peripheral to network)– diverse contentdiverse content– high turn-over of individual blogshigh turn-over of individual blogs
• 13% shared across 3 samples
• Core sample– many in-linksmany in-links– focused on religion, politics, morality, educationfocused on religion, politics, morality, education– stable membership over timestable membership over time
• 75% shared across 3 samples
Social network analysis: Centrality
• ‘A-list’ blogs are central– All four source blogs lead to 25/37 A-list blogs
– Avg. 3 degrees of separation from any source blog to any A-list blog (range 1.8 - 4.7 degrees)
• tendency to increase in closeness over time
• Catholic blogs are ‘core of the core’– pattern like A-list
Social network analysis: Reciprocity
• A-list blogs attract more links– Tend to be found in reciprocal relations with other A-list blogs
– Non-A-list blogs link preferentially to A-list blogs, but low rate of reciprocation
• Change over time– Increase in reciprocal linking of A-list blogs (p = .001)
– Decrease in reciprocal linking of non-A-list blogs (p = .001)
• Catholic blogs pattern like A-list
Visualization
• Cut-off at 10 in-degrees (350 blogs)• Three thematic clusters emerge:
• Catholicism (red)• Politics/current events (green)• Homeschooling (blue)
• Catholic (and some political) blogs consolidate over time
• Other clusters fragment or disperse
QuickTime™ and aTIFF (LZW) decompressor
are needed to see this picture.
Sample 1 (April 2004)
Sample 2 (August 2004)
Sample 3 (December 2004)
Animation
QuickTime™ and aVideo decompressor
are needed to see this picture.
Study limitations
• Only four random sources, three of them filter blogs, one Catholic
– Filters more likely to have links (Blood, 2002)– Catholic blogs more likely to link to each other?
• Snowball sampling creates bias towards connectivity
– Overestimates overall connectivity
• First sample was collected manually, second and third samples via automated crawl
– May not be strictly comparable
How does the network change?
• Core gets tighter– religious, politically conservative blogs
• Periphery gets looser– thematically-diverse, albeit disproportionately
filter-type, male blogs
• Change is evident at 4-month intervals
Possible explanations
• Political/religious discourses increasingly polarized– US 2004 presidential campaign
• Tendency for cliques to become more cliquish– If so, should be demonstrable for other cliques in
the blogosphere
Future directions
• Conduct longitudinal network analysis starting from other source blogs, e.g.– Politically liberal
– Non-filter types
– Female authors
• Sample at shorter intervals
• Track network evolution over long time spans
Contact: