Tag Archives: social networks

What Does a Political Networks Conference Do? (On Twitter)

Last week I mapped the Twitter follow network of those attending the Political Networks Conference in Boulder, CO.  I gathered this data prior to the first day of the conference, so I decided to take a second look now that the conference is over.

Political Networks Twitter Follow Network – Post Conference (Click image for larger version.)

How does the post-conference graph differ from the pre-conference graph?

  • The first notable difference is the addition of 18 new nodes.  The size of the network grew by over 50% as new Twitter users decided to follow @PolNetworks during the conference.
  • Another difference is the addition of 215 new follow edges.  With only 181 edges in the original graph, the number of follow relationships in the network grew more than 100%.
  • The account with the biggest increase in followers was @krmckelv.  Karissa went from only 1 follower to 8.  (She has since changed her Twitter handle to @karissamckelvey.)

Now let’s limit the post-conference graph to a subgraph containing only those nodes that were also in the pre-conference graph.  How has this component changed?

Graph Density: Increased 0.03 from 0.15 to 0.18.

Graph Transitivity:  Decreased 0.03 from 0.56 to 0.53.

Graph Efficiency:  Decreased 0.02 from 0.87 to 0.85.

So new follow edges were added (density), but in a way that more incomplete than complete triangles were formed (transitivity).  Not surprisingly, the new ties were redundant in connecting the graph, lowering efficiency.

Here are some individual-level statistics for the interested.  It was great to get to know many of you at the conference, and I’ll see you at the next one!

Account In Degree Out Degree Eig. Centrality
JaciKettler 10 20 0.3
smotus 35 18 0.27
kwcollins 20 19 0.27
burtmonroe 15 17 0.26
therriaultphd 20 18 0.24
BrendanNyhan 31 17 0.24
JohnCluverius 8 13 0.22
RebeccaHannagan 4 12 0.21
ianpcook 7 12 0.2
Student 27 14 0.2
jlove1982 7 11 0.2
KyleLSaunders 9 13 0.19
krmckelv 12 17 0.19
JeffGulati 9 12 0.18
richardmskinner 8 10 0.15
James_H_Fowler 8 11 0.15
prisonrodeo 16 9 0.15
archimedino 5 10 0.14
davekarpf 7 8 0.13
NateMJensen 5 8 0.13
jon_m_rob 0 8 0.13
sissenberg 8 7 0.12
3876 7 8 0.12
hsquared47 3 7 0.12
marioguerrero 1 7 0.12
FHQ 17 7 0.11
heathbrown 4 8 0.11
First_Street 1 7 0.1
98percentright 5 6 0.1
davidlazer 17 5 0.07
GeoffLorenz 0 5 0.07
jasonjones_jjj 4 6 0.06
matthewhitt 2 4 0.06
DocPolitics 1 4 0.06
JoeLenski 2 4 0.05
maizeandblue 1 4 0.05
allenlinton2 2 3 0.04
DryHeathen 0 4 0.04
ajungherr 0 4 0.04
slimbock 0 2 0.03
cassyld 2 2 0.02
PolNetworks 52 1 0.02
rmbond15 2 3 0.02
DominikBatorski 0 2 0.01
vatrafilm 0 1 0
janschulz 0 1 0
dogaker 0 1 0
stefanjwojcik 1 1 0
KenneyMkenney 0 1 0
ophastings 0 1 0
jbrittaq 0 1 0
jboxstef 1 1 0
Hirschi5 0 1 0

Download edge list as .xlsx: polnetworks2_edge_list

Facebook Resources

By Jaime Settle

As is the norm for academic research on novel technologies and phenomena, it seemed like we waited ages for quality research about Facebook using user-generated data instead of self-reported usage data. I was recently steered toward two sites that may be useful for staying informed about the latest trends and data analysis using Facebook:

Facebook Data Team, a group of researchers at Facebook who handle the collection, management, and analysis of Facebook data

Overstated, a blog by Cameron Marlow, an in-house researcher at Facebook whose research focuses on “various aspects of online communities including the diffusion of information across online social networks, access to information and social capital, and the incentives that impact social media production.”

These sites might generate interesting new ideas and reveal relevant trends that could improve our exploration of the effects of Facebook on political behavior and the transmission of political information. For example, it seems that there was a trend among Facebook users who supported the idea of health care reform to post a very specific status message this fall, leading to a sharp increase in the use of the word “health care” in status messages (much beyond the increase observed during the 2008 election.

from "Memology: The Top 15 Status Terms of 2009"