Analyzing social media networks with NodeXL - Chapter-10 Images

1Copyright © 2011, Elsevier Inc. All rights Reserved
Chapter 10
Twitter
Conversation, Entertainment, and
Information,
All in One Network!
Analyzing Social Media Networks with NodeXL
Insights from a Connected World

2
Scott Golder (@redlog) is a graduate student in Sociology at Cornell University. He was
previously a researcher at HP Labs, and holds an A.B. in Linguistics with Computer Science from
Harvard University and an M.S. in Media Arts and Sciences from the MIT Media Laboratory. His
research interests broadly include network and social identity effects online, which he has
examined in a variety of environments including usenet, online poker, social bookmarking and
social network services. His website is www.redlog.net.
Vladimir Barash (@vlad43210) is a graduate student in Information Science at Cornell
University. He holds a BA in Cognitive Science from Yale University. His research interests
include social media, online communities and diffusion, and his thesis topic is on the
structural properties of diffusion in social networks. His websited is www.vlad43210.com

FIGURE 10.1
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Estimated growth of Twitter. The growth curve shows sharp increases in
March 2007 and April 2009, because of the SXSW festival and The Oprah
Winfrey Show .

FIGURE 10.2
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Twitter’s web-based interface. Its most prominent contents are a stream of
tweets (left) and a dashboard with user-specific information (right).

FIGURE 10.3
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TweetDeck is a popular desktop-based Twitter client.

FIGURE 10.4
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Twhirl is a popular desktop-based Twitter client.

FIGURE 10.5
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A tweet with an @reply message. This message is sent from @vlad43210
to @redlog.

FIGURE 10.6
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An interesting tweet posted by @ASAnews. This tweet starts a retweet
chain (see the next figures).

FIGURE 10.7
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@redlog retweets the tweet posted by @ASAnews. The @ASANews
message about David Brooks’ article now spreads to @redlog’s followers,
even if they don’t follow @ASANews directly.

FIGURE 10.8
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@vlad43210 retweets @redlog’s retweet of the tweet posted by
@ASAnews. The message now spreads to @vlad43210’s followers, even if
they do not follow either @ASAnews or @redlog. In this way, messages
can spread via retweets and reach a very large audience.

FIGURE 10.9
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The friends and followers network is an information/ attention network . This
figure shows Scott with two friends (Pee-Wee and Derek) and two followers
(Marc and Vlad).

FIGURE 10.10
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The middle actor is a bridge between two communities. The top, red
numbers above the actors are their eigenvector centrality, and the bottom,
blue numbers are their betweenness centrality.

FIGURE 10.11
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The NodeXL Import menu. Note there are two options that import Twitter
data, from a user’s network and from a search query.

FIGURE 10.12
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NodeXL’s Twitter User’s Network import screen. The levels options
selected will import both @vlad43210’s friends and followers, as well as
any friend/follower connections between them.

FIGURE 10.13
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The @vlad43210’s 1.5-degree egocentric Twitter network. The vertex at the
center is @vlad43210, the many vertices at the edges represent
@vlad43210’s weak social ties, most of them complete strangers.

FIGURE 10.14
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The @vlad43210’s 1.5-degree egocentric Twitter network. We have filtered
out the complete strangers to focus on @vlad43210’s strong social ties —
his friends and colleagues. Two clusters emerge (top right and bottom left).

FIGURE 10.15
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The @vlad43210 1.5-degree egocentric Twitter network (strong social ties
only). NodeXL automatically identifi es the clusters and colors them
differently. Top right (green) corresponds to @vlad43210’s friends, and
bottom left (purple) corresponds to his academic colleagues.

FIGURE 10.16
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The @vlad43210 1.5-degree egocentric Twitter network. Greener vertices
have higher eigenvector centrality, and larger vertices have higher
betweenness centrality.

FIGURE 10.17
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The @vlad43210 1.5-degree egocentric Twitter network. Greener vertices
have higher eigenvector centrality, and larger vertices have higher
betweenness centrality. Thicker edges correspond to users that @reply to
@vlad43210 or mention his username in one of their tweets.

FIGURE 10.18
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Twitter Search Network import dialog. The options selected import the first
100 people to mention “Black Friday” in their tweets, and all of the Follows,
Replies-to, and Mentions relationships between them.

FIGURE 10.19
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Twitter mentions network for “Black Friday.” Note that the network
resembles a set of connected stars: around @Shop- NPartyGirl,
@luv_mydaschund, and @sdiego1717, respectively.

FIGURE 10.20
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Twitter mentions network for “Black Friday.” Thicker edges represent
retweets of @ShopNPartyGirl’s messages.

FIGURE 10.21
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Twitter mentions network for “Black Friday.” @ShopNPartyGirl and her
friend/ follow relationships are highlighted in red. Greener vertices have
more tweets, larger vertices have more followers.

FIGURE 10.22
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Twitter mentions network for “Black Friday.” @ShopNPartyGirl and her
friend/ follow relationships are highlighted in red. Greener vertices have
more tweets, larger vertices have more followers. @ShopNPartyGirl is
represented in the canvas by her Twitter profile image.

Analyzing social media networks with NodeXL - Chapter-10 Images

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Analyzing social media networks with NodeXL - Chapter-10 Images