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Here are some SNA approaches to media studies:

Abstract. To test hypotheses about presidential cabinet network centrality
and presidential job approval over time and to illustrate automatic social
network identification, this research mined the social networks among
cabinets of Presidents Reagan through G.W. Bush based on the members’
co-occurrence in news stories. Each administration’s data was sliced into
time intervals corresponding to Gallup presidential approval polls. It was
hypothesized that when the centrality of the president is lower than that
of other cabinet members, job approval ratings are higher. This is based on
the assumption that news is generally negative and when the president
stands above the other cabinet members in network centrality, he or she is
more likely to be associated with the negative press coverage in the minds
of members of the public. The hypothesis was supported. Nevertheless, when
the positive and negative sentiment of news stories is added, each
administration was found to have different effects.

To test hypotheses concerning presidential cabinet network centrality and
its relationship to presidential job approval, this research mined the
social network structure of President Barack Obama’s cabinet members
through automatic network analysis of all New York Times and Washington
Post stories including any of 24 individual cabinet members and the
president. The WORDij semantic-network software identified their
co-occurrences in these news stories. The software also segmented the
aggregate text into two-week intervals based on the average time between
Gallup presidential approval polls. Time-series analysis linked network
centrality with presidential job approval after removing serial
autocorrelation. The research tested the hypothesis that when the
centrality of the president is higher than the centrality of the cabinet
members, presidential job approval ratings are lower. Conversely, when the
centrality of the president is lower relative to average cabinet member
centrality, job approval ratings are higher. This is based on the reasoning
that press coverage is commonly negative, and the president absorbs more
negative press sentiment when he stands higher in centrality than the other
cabinet members, acting as a metaphoric “lightening rod.” When the
president’s centrality is lower relative to the cabinet average, this
lightening rod effect dissipates as other cabinet members would absorb more
of the negative press content as publics process information about the
administration. The hypothesis was supported for the Obama administration
and his cabinet with a significant negative correlation between relative
presidential centrality and job approval at a time lag of l=3, a period of
6 weeks.

Unprecedented social and technological developments call into question the
meanings and boundaries of privacy in contemporary China. This study
examines the discourse of privacy on Sina Weibo, the country’s largest
social medium, by performing a semantic network analysis of 18,000 postings
containing the word “隐私 (privacy).” The cluster analysis identifies eleven
distinct yet organically related concept clusters, each representing a
unique dimension of meaning of the complex concept. The interpretation of
the findings is situated in the discussion of the rapidly evolving private
realm in relation to emerging new contexts of the public realm. Privacy,
justified for both its instrumental functions and intrinsic values, both
reflects and constitutes new forms of sociality on the socio-techno space
of Weibo.

This paper studies the network structure, conversation patterns, and
semantic content of socially mediated exchanges via the microblogging
service Twitter. The project tracked interactions and messages beginning
with a randomly selected user, followed by a snowball sample of the user’s
network. From 01/24/2010 to 04/24/2010 a total of 5776 unique users were
collected, with a total of 3,392,138 tweets. The content of tweets was then
examined for two groups: users with a highly centralized (radial) network,
and those with a densely interlocked network. The most central English
language word pairs were identified through semantic software analysis
using the WORDij package, and also subjected to language analysis using the
LIWC2007 software. Degree of interactivity between ego and alters was also
measured. The findings suggest a relationship between network structure,
interaction patterns, and message content that may be described as
producing distinct genres of Twitter experience: one practiced by
conversationalists, who focus on information sharing and strategic identity
construction, and another by protagonists, who are more inwardly focused
and performative, with minimal interaction. These genres have implications
for scholars interested in the interdependency between technology and human
communication behaviors.

ABSTRACT The literature argues that the amount of media coverage of issues
sets the public agenda. What sets the media agenda appears to largely be
governmental communication. It was hypothesized that governmental actors
would attract media to the issue of acid rain. Once coverage started,
interest groups would push the media bandwagon for wider sectors of
society. This creates a climate of “buzz journalism.” After conflict among
interest groups accelerated and the wagon reached optimal speed,
governmental actors would brake the issue cycle and media coverage would
dissipate. It was further hypothesized that a period of “long-tail
journalism” would ensue in which there was little media coverage over the
years without this governmental-generated buzz of coverage. The plot of the
number of stories per year for the next 25 years showed that there was some
coverage but very predictable in its residual factual nature with no hooks
to policy considerations. Not until again in 2009 was acid rain connected
with a governmental initiative, the “Cap and Trade ”policy” deliberations
set in motion by the Obama administration. Coverage of acid rain moved
again above the long-tail, although only slightly with weakly organized
semantic networks. To test these hypotheses, coverage of acid rain during
1977—1989 in the New York Times Index (459 abstracts) and the Congressional
Quarterly Almanac (43 articles) were content analyzed to identify
co—appearing actors (n=354). These sources were used because electronic
access to relevant news documents as not robust. Actor network data were
aggregated by year and actor centrality measured, serving as independent
variables in time—series regressions with media coverage as the dependent
The hypotheses were supported. Governmental actors had an elliptical power
curve. They appeared to start and stop the media top, but interests groups
put the spin on in the middle. Spin, however, was not the only cycle
apparent. This suggests a more comprehensive social cleansing model of
media agenda setting. What is left after government is done with an issue
is the residual core fabric of the content factual content.

Abstract. The current research compares celebrities to public
intellectuals, dead or alive, in their amounts of traditional and new media
coverage and in their agency in online social discourse networks. Previous
research studied only public intellectuals on these variables. A
comprehensive theory is presented that brings together media-related
processes about celebrities and public intellectuals into a coherent
framework and expands the theory to also include online discussion content
variables. WordLink software is used to index semantic-network structures,
with additional content variables examined. Eleven hypotheses are derived
from the broadly-based theory. The hypotheses are supported by the data.
Highlights include: discussion content about celebrities is more entropic,
more focused on peripheral content, more socio-emotional, and the
discussants more narcissistic. They also focus on less abstract concepts
than do those discussing public intellectuals. Although celebrities receive
more media coverage than public intellectuals, the latter have twice the
size of online social networks associated with them. The glow of
celebrities produced and managed as the output of mega-media organizations
fades relatively quickly after their death, while the more focused
conceptual beams of public intellectuals, even after their corporeal
passing, are associated with activation of more developed social networks
in the time-suspension of cyberspace.

Abstract: Social media are fundamentally based on communication networks
containing friends, acquaintances, or others. Because communication is
essential to collaboration on activities, we assume that those who have
more contacts in work-oriented social media are more likely to be
collaborative in their work behaviors. Design educators have been stressing
of importance of collaboration in training recent cohorts of design
students. Our goal was to empirically examine designers on the LinkedIn
social media site in terms of how they describe collaboration and why. The
results supported hypotheses that designers with larger networks of online
contacts were more verbal, had higher collaborative word use, were more
positive, were more evaluative, used more competence-oriented words, and
had semantic networks for collaboration that were more complex, with
greater discrimination, differentiation, and integration. Given the
experiences of current young adults with social media, we further
hypothesize that future design work will become increasingly collaborative.

We investigated possible causal relationships between a professional
association’s division network structure based on co-memberships, and the
division network structure based on the semantic similarity of papers
presented at annual meetings. Data from the International Communication
Association (ICA), a basic-research focused organization of academic social
scientists with 21 divisions, provide for an analysis at two points in
time, 2007 and 2011. QAP correlations among the four networks entered into
a quasi-experimental cross-lagged correlation design suggested evidence for
possible causality. Compared to the no cause baseline, the time 1
co-membership network structure was a significant predictor of the time 2
semantic division network structure. The reverse relationship was not
significant. As well, there is considerable reduction of the size of the
synchronous correlation of the semantic and co-membership division networks
from time 1 to time 2. Noteworthy was also the pattern of diachronic
association of the same kind of network. The semantic division network at
time 1 explained only 31% of the same network at time 2. Likewise, the
co-membership network at time 1 explained only 25% of that network at time
2. This would be consistent with the basic research focus of the
association. Such a focus privileges novelty. The paper uses theory to form
the research questions and interpretations. Because of the limitations of
the statistical model, and the case study design, these results should be
taken as exploratory and suggestive. Future research may reduce these

Abstract—This research demonstrated a new approach to time-series analysis
of semantic network data. Three years of the Obama administrations coverage
in the New York Times and Washington Post was extracted from Lexis-Nexis.
The text was sliced into 74 two-week time intervals corresponding to
frequency of Gallup polls. Words appearing in three word positions on
either side of each word were tabulated, one for the aggregate text file
and 74 times for each of the time slice data. A matrix of word pairs by
time slices created the basis for computing a time slice similarity score
for each pair of slices. These time units then became nodes in a network
analysis with link strengths defined by semantic similarity. Network
analysis procedures were applied to explore the meaning of the structures
identified.While events can be laid upon a chronological time series,
events and event frames may often be of a different character than merely
time-dependent. Some events/frames operate in spurts, perhaps with
considerable time between them that may result in the analyst missing the
wholeness of the event/frames. Some events/frames retrench and add new
elements as they “move back in time, then forward again.” Some
events/frames contain arcs in which an alternative framing is offered by
opposing groups. Some events/frames are pivotal, changing the fundamental
dynamics of the overall event/frame space. Some events mark epics that may
begin after a pivotal time.

Depending on socio-political perspectives some events/frames may be treated
from a common semantic domain, while the same such events/frames may from a
different socio-political be treated quite differently. Methods that foster
parsimony in treating events/frames may be preferred in some circumstances.

The method used here, analyzing time as nodes in a network based on their
similarity of word pair frequencies appears to offer the most flexibility
for observing these various kinds of events and frames. Turning time
outside in, that is treating time slices as nodes and their semantic
similarities as links, yields some unique value. The event/time space is
analyzed for its underlying network structure. Community detection reveals
a simplified structure. Particular time nodes serve specialized roles in
the network. Exploration with other networks can elaborate a conceptual
framework for event/time space.

Abstract—Analysis of sentiment expressed in political systems’
communication over long periods of time has been difficult. This research
illustrates a method based on network analysis, the Sentiment Network
Analyzer (SNAZ). It identifies weighted shortest paths between seed words
and 3,500 target sentiment words as these occur in semantic networks
extracted from open-source documents sliced into time intervals. Computing
the normalized intensity ratios of positive and negative sentiment for each
time slice enables application of the “Losada Line.” For a system to be
flourishing there must be at least 2.9 times more positive than negative
communication. Below that ratio the system is languishing. Excessive
positivity above a ratio of 11.6 marks the disintegration of a system into
chaotic oscillation. We collected and analyzed five years of documents
propaganda mentioning the Taleban from Afghani and Pakistani sources
transcribed by BBC International Monitoring. Likewise, we extract and
analyze stories communicated by Radio Free Europe/Radio Liberty (RFE/RL)
connected with Afghanistan over the same five-year period. Semantic network
and sentiment network analysis is coupled with the computation of
positivity ratios in each time slice during this period. Taleban content is
generally evident of flourishing, except for a period of oscillation
between flourishing and excessive positivity beginning in the third quarter
of 2010. RFE/RL is consistently languishing, reaching the 2.9 flourishing
level in only one period. We discuss possible reasons. We also consider
some implications for perception management and counterterrorism strategy.

You can find more examples at

James Danowski

On Wed, Oct 30, 2013 at 11:44 PM, Mathieu ONeil <[log in to unmask]>wrote:

> *****  To join INSNA, visit  *****
> Hi everyone
> I am currently preparing an undergraduate course in media studies and I
> was curious to find out if anyone knows of SNA approaches to media
> political economy issues such as interlocking directorates, organisational
> practices such as newsroom dynamics, moral panics, media and conflict, etc?
> Thanks for any input,
> cheers,
> Mathieu O'Neil
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