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Utilizing Social Network Analysis to Study Communities of Women in Conflict Zones


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/ Synopsis This article proposes to study the plight of women in conflict zones through the lens of social network analysis. We endorse the novel idea of building a social network within troubled regions to assist in understanding the structure of women's communities and identifying key individuals and groups that will help rebuild and empower the lives of women. Our main argument is that we can better understand the complexity of a society with quantitative measures using a network analysis approach. Given the foundation of this paper, one can develop a model that will represent the connections between women in these communities. This model can then support work aiming to help women in zones of conflict.
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Journal of Humanistic Mathematics
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Utilizing Social Network Analysis to Study
Communities of Women in Con!ict Zones
James R. Gatewood
United States Military Academy
Candice R. Price
University of San Diego
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Utilizing Social Network Analysis to Study
Communities of Women in Conflict Zones
James R. Gatewood
Department of Mathematical Sciences, United States Military Academy, West Point NY
Candice R. Price
Department of Mathematics, University of San Diego, CA
This article proposes to study the plight of women in conflict zones through
the lens of social network analysis. We endorse the novel idea of building a
social network within troubled regions to assist in understanding the structure of
women’s communities and identifying key individuals and groups that will help
rebuild and empower the lives of women. Our main argument is that we can
better understand the complexity of a society with quantitative measures using a
network analysis approach. Given the foundation of this paper, one can develop a
model that will represent the connections between women in these communities.
This model can then support work aiming to help women in zones of conflict.
1. Introduction
To understand the plight of women in troubled regions it is important to
take into account their cultural, religious, economic and political experiences.
One has to learn the roles of women in times of peace to understand their
circumstances during times of war. A question that may arise is: Are the
women in the region seen as equal members of society or are/were they
subordinate to men [9]? Although women and men both struggle in zones
of conflict for rights and representation, “women often encounter structures
Journal of Humanistic Mathematics Vol 7, No 1, January 2017
4 Social Network Analysis of Women in Conflict Zones
of patriarchal authority in the national movement, the military, the private
sphere and through the discourses and practices of dominant belief systems”
[9]. In order to help empower these women, one has to take into account
their whole experience.
This paper puts forth a discussion of women in conflict zones and presents
a possible framework, a social network model analysis, to assist in rebuild-
ing troubled regions by understanding the connections that lie within these
communities. First, in Section 2, we provide a definition for conflict and
conflict zones, and discuss some causes of conflict. In Section 3, we explore
what women and their communities endure in conflict zones. In Section 4,
we discuss how a social network model can assist in addressing the needs of
women in these regions by providing the mathematical methods needed to
analyze collected data. With a network model in place, some policies can be
constructed to further benefit the lives of women in these zones. We conclude
this paper with a section (Section 5) on how to collect the necessary data to
implement a social model, including a sample survey.
2. Conflict Zones
We define conflict as “competitive or opposing action of incompatibles:
antagonistic state or action (as of divergent ideas, interests, or persons)” [16].
The term conflict zone is more difficult to pin down as it can be viewed dif-
ferently by different factions. We will define a conflict zone as a “land area
that encloses flash points and critical areas of conflict” [14]. We distinguish
between three main types of conflict zones: terroristic, incursion and territo-
rial conflicts [4]. In the case of terroristic conflicts, the government control is
firm but there may be cases of isolated incidents of violence. The incursion
type of conflict is characterized by the situation in which government holds
control but there are still frequent armed incursions and withdrawals orga-
nized by the opposing groups. Territorial conflict relates to the case where
government loses control over the region and is usually engaged in direct
fighting with the opposition [4].
Though a developmental stage perspective may be desirable, it is often
difficult to distinguish between pre-conflict, conflict, and post conflict areas,
because conflict zones are sites of both change and continuity [10]. To fa-
cilitate a more coherent view of conflict zones it is useful to identify where
people, interest and events reinforce each other, where they are contested,
James R. Gatewood and Candice Rene´e Price 5
and even where they diverge [10]. There are various interests in conflict
zones, including simple survival; furthering of political and social agendas;
status and profit. The fact that these are not mutually exclusive shows the
importance of research and policy that examine the interests, motives, and
strategies of those within conflict zones.
2.1. Causes of Conflict
There is no single cause of conflict. Conflicts can be caused by a combi-
nation of the following factors as described in [3]:
Political and institutional factors: weak state institutions, elite power
struggles and political exclusion, breakdown in social contract and cor-
ruption, identity politics;
Socioeconomic factors: inequality, exclusion and marginalization, ab-
sence or weakening of social cohesion, poverty;
Resource and environmental factors: greed, scarcity of national re-
sources often due to population growth leading to environmental inse-
curity, unjust resource exploitation.
The triggers for these factors include: single acts, events or the anticipa-
tion thereof that set off violent conflict or its escalation (e.g. elections, behav-
ior of political actors, sudden collapse of currency, increased food scarcity)
[3]. While a history of conflict does not necessarily guarantee the further re-
ignition of tensions in an area, it does indicate the presence of socioeconomic
and political conditions that predispose a community to conflict [3].
Conflict is governed by a system of rules and norms. When there is an
absence of such systems to manage conflict and channel it into constructive
areas, it can become negative and destructive. Unfortunately, conflict in such
cases often creates temperamental and dangerous situations for vulnerable
populations, specifically women. Women and children are substantially more
affected by these kinds of circumstances and thus have a larger stake in
conflict resolution. And while women continue to be poorly represented in
formal peace processes, they contribute in many informal ways to conflict
6 Social Network Analysis of Women in Conflict Zones
3. Plight of Women in Conflict Zones
It is difficult to make universal statements about the impact of conflict
on the lives of women because the extent to which conflict restricts women’s
freedom of movement depends on a number of factors. Differences in culture,
geography, and context play a role in the impact of conflict on women. In the
agricultural sector, women may take over responsibility for working the land,
caring for livestock, trading, or carrying out wage labour outside the home.
One key issue, though, is that women are often denied access to, owning, and
inheriting productive resources in their own names. In urban areas, a kind of
“feminization” of the informal sector takes place during conflict. Women may
regard work in the informal sector as a way of liberation and empowerment
or as a means of exploitation and survival.
For example, if we focus on forced displacement, in some cases displace-
ment can lead to greater mobility for women. In other contexts, women may
be perceived as less threatening and thus may have more mobility to carry
out economic activities which men are no longer able to do. Women may
also assume additional responsibilities such as taking on the role of primary
breadwinner. In some cases, women may be given priority for training and de-
velopment programs in health and education, as well as in income-generating
activities. The skills women gain enable them to assume new roles within
their households, becoming the main breadwinners. Men however may react
to these changes with depression, alcoholism, and an escalation of violence
against women in public and private [21]. The relatively small gains women
obtain during displacement do not necessarily translate to more equitable
gender relationships. These gains are usually not accompanied by any change
to the overall paradigms of gender differences, leaving women with new roles
to fulfill but no institutional leverage to fulfill them effectively [21].
Conflict is a gendered activity: women and men have different access
to resources, power, and decision making before, during and after conflicts
[22]. The experience of women and men in situations of tension, war, and
post-conflict reconstruction is significantly different. Approximately 80% of
today’s civilian casualties are women and 80% of all refugees and internally
displaced people worldwide are women and children [22]. As emphasized in
the Platform for Action of the United Nations Fourth World Conference on
Women, “while entire communities suffer the consequences of armed conflict
and terrorism, women and girls are particularly affected because of their
status in society and their sex” [22].
James R. Gatewood and Candice Rene´e Price 7
Women are caught in a paradox: while they are the main civilian victims
of conflicts, they are often powerless to prevent conflicts and likely to be ex-
cluded from the negotiations when it comes to their resolution. Women are
often confined to a marginal role in the post-conflict reconstruction and rec-
onciliation efforts. This exclusion of women from decision-making positions
prior to, during, and following violent conflicts, reinforces their victimization
The importance of including women and gender perspectives in the plan-
ning and implementation of peace operations is increasingly recognized. This
has led to some milestone achievements, such as the deployment of the first
all-female peacekeeping unit in Liberia; mediation efforts to end conflicts in
Uganda, Sudan, and the Democratic Republic of Congo; supporting initia-
tives aimed at strengthening the presence and capacity of female officers in
peace operations, in places such as Afghanistan; strengthening the develop-
ment of gender-sensitive early warning strategies to prevent the outbreak of
conflict in Colombia and the Solomon Islands; advocating for women’s in-
clusion in the design, implementation and conduct of post-conflict elections
in Burundi; providing gender expertise in a variety of peace operations. In
order to rebuild these conflict areas women have to be directly involved in the
process [24]. However, women are still significantly underrepresented in most
areas of UN peace operations, in peace negotiations, and in national gover-
nance, particularly at senior levels. And while many policies have surfaced
to protect women in times of conflict, women’s issues are still often given low
priority and inadequate support. We propose that the mathematics of social
networks can and should be utilized in order to address the roles of women
in these processes. Once the connections and roles of individual women are
better understood, information can be better collected from or disseminated
within the community.
4. Model: Social Network Model
A social network approach to understanding the relationships between
women and their communities can assist in understanding how relationships
are formed and organized. When conflicts arise, instability within a region
causes social structures to break down. Often, women in these regions come
from communities where there is a strong emphasis on the relationships and
bonds between people [20]. In these communities, women depend much more
8 Social Network Analysis of Women in Conflict Zones
on each other than women do in western societies [20]. In order to begin to
rebuild communities in conflict zones, we must first understand relationship
dynamics. Since women play a central role in economic, social, and family
life, understanding how they organize the community might be a first step;
and, a social network model will assist in understanding the structures of
these groups.
A few questions that a social network model/approach might be able to
address include:
How do relationships between women form, organize into groups, and
exert influence under challenging conditions?
Which actors have the most influence in a group?
How do groups relate to one another?
Who are the most connected individuals?
The social network model can also assist in zones of conflict where outside
forces might become involved. In the example of Western World involvement
in African affairs, there can be communication challenges and cultural dif-
ferences; however, an understanding of the local social networks might help
alleviate some of the tension and stress by acknowledging how a particular
society organizes especially under taxing conditions. Thus utilizing a net-
work, task forces can be of greater assistance in conflict zones where they are
not a part of the community.
To reconstruct a community in devastated parts of the world, we propose
to start by rebuilding the lives of women within these conflict zones. This
approach differs from other attempts in trying to rebuild nations after conflict
in that it is concentrated on first rebuilding the lives of individuals and
communities and not the entire country all at once. Rebuilding communities
comes from understanding the diversity and cultural needs of women. This
approach allows one to view how human relationships interact and form and
requires more investment in detailed resources. This approach is sustainable
as it allows the rebuilding of communities to happen organically. A social
network model can support an understanding of how to optimize the use of
James R. Gatewood and Candice Rene´e Price 9
The modelers must make sure to incorporate women’s groups and their
activities. Furthermore they must be mindful of the cultural sensitivities
of the region and the historical role of women within the particular society.
Once the network is created, the next step is to examine the model to find
patterns and use the mathematical techniques discussed in the next subsec-
tion to seek out which communities have connections to understand the links
for cooperation and rehabilitation.
4.1. Mathematical Methods
Asocial network is a graph comprised of nodes and links. The nodes
are called agents. They are connected by links which describe the relation-
ship between agents. The analysis of social networks can explain how strong
the connections are and which agents are the most influential. The analysis
can also spot patterns and subgroups which may not have been noticeable
before. A network analysis approach is an innovative method in that every
observable entity is a part of the network as opposed to just a sample of the
population. We are also able to utilize the idea that networks can be embed-
ded in other networks. The complexity of a society can then be understood
with quantitative measures using a network analysis approach.
Social networks have already been used from mapping terrorist networks
to mapping the HIV positive field [12]. A social network model will strive
to identify central people in a network. In conflict regions it is rare that
only one individual can influence everyone; however, individuals must form
connections with others to get things accomplished [19]. We propose to use
social network analysis to exploit these bonds and links in order to further
understand the roles of women in conflict zones.
Due to the difficulty of gathering data in conflict zones, there is a dearth
of readily available network data to completely address the concerns in this
paper. Thus we will use a jazz musician social network [6] to demonstrate
what can be done to work on issues in conflict regions when the data from
these zones becomes available; see Figure 1. When we construct a social
network model addressing women in conflict zones, women will be the agents
and their relationships will be represented by the links. Our example will
nonetheless allow us to show how one can calculate centrality measures that
help determine the most influential members in the network. We utilize the
definitions given in [15] for these centrality measures.
10 Social Network Analysis of Women in Conflict Zones
Figure 1: Jazz Musicians Network. The graph representation was created by
the authors using data from [6].
4.1.1. Degree Centrality
Degree centrality was historically the first centrality measure introduced,
and it is conceptually the simplest. The degree of an agent is defined by
Equation (4.1):
aij (4.1)
aij =1 if agent niis connected to agent nj
0 if agent niis not connected to agent nj.
Note that the degree can be interpreted as the number of direct connections
an agent has. In this setting, therefore, we measure the centrality of an agent
to its network by the size of its degree.
James R. Gatewood and Candice Rene´e Price 11
An agent with high degree centrality is directly connected to many other
agents in the network; see Figure 2for an example. Given that this person is
highly connected to other people, there is a high probability that they have
readily available all the information flowing through the network. In a region
of conflict, such agents can be used to assess how and what information is
flowing through the network.
Figure 2: Jazz Musicians Network with degree centrality illustrated.
The larger the node, the higher the degree centrality measure. The graph repre-
sentation was created by the authors using data from [6].
4.1.2. Closeness Centrality
This measure expresses the average social distance from each individual
to every other individual in the network. The concept of social distance is
easily understood by considering the example of the “Erd˝os number” of a
mathematician, calculated by finding the shortest path of connections from
any one mathematician to Paul Erd˝os based on “collaborative distance” de-
fined via joint authorship of mathematical papers [5]. Someone who has
12 Social Network Analysis of Women in Conflict Zones
written a paper with Erd˝os is considered to be 1 degree away, while anyone
who has written a paper with someone who wrote a paper with Erd˝os is 2
degrees away, and so forth.1This same concept can be applied to any social
network and is known as closeness centrality.
To calculate closeness centrality we use the following definition:
gij )#1
Here gij represents the number of links in the shortest path connecting agents
niand nj. In this way an individual with a direct tie to everyone else ends
up with the largest closeness value. An example demonstrating this notion
is provided in Figure 3below.
One property of closeness centrality is that it tends to give high scores
to individuals who are near the center of network communities in an overall
larger network. High closeness centrality individuals tend to be important
influencers within their local network community. They are often respected
locally and they occupy short paths for information spread within their net-
work community. If we can identify the agents with high closeness centrality
measure in a conflict zone, important information can be released to these
few agents and spread among the population fast.
4.1.3. Betweenness Centrality
Betweenness is another measure that uses the concept of counting the
shortest paths between individuals in a network. It has different properties,
however, from closeness centrality. To calculate betweenness centrality, we
start by finding all the shortest paths between any two agents in the network.
Then, we count the number of these shortest paths that go through each agent
as in Equation 4.2. This number is betweenness centrality.
Bi=Pi<j gjk (ni)
1Editor’s note: A recent paper in Journal of Humanistic Mathematics studies the
Erd˝os collaboration graph and its evolution as the Human Genome Project has developed;
see “Some Effects of the Human Genome Project on the Erd˝os Collaboration Graph” by
Chris Fields, Volume 4Issue 2 (July 2014), pages 3–24, available at http://scholarship., accessed on January 12, 2017.
James R. Gatewood and Candice Rene´e Price 13
Figure 3: Jazz Musicians Network with closeness centrality illustrated.
The larger the node, the higher the closeness centrality measure. The graph rep-
resentation was created by the authors using data from [6].
Here gjk is the number of links in the shortest path connecting agents njand
nk, and gjk (ni) is the number of these paths that contain agent ni.
The results of this calculation can help us find the individuals who are
necessary conduits for information that must traverse separate parts of the
network. These are usually very different individuals from those with high
closeness. High betweenness individuals often do not have the shortest av-
erage path to everyone else, but they have the greatest number of shortest
paths that necessarily have to go through them; see Figure 4for an illustra-
tion in our jazz musicians network example. Another example would be the
highway map of the United States. Cities in the Midwest like Chicago and
Denver have higher betweenness centrality than New York or Los Angeles
because many shortest paths that include cities on the east and west coast
have to pass through those cities. In a social network, high betweenness
individuals are often found at the intersections of more densely connected
14 Social Network Analysis of Women in Conflict Zones
Figure 4: Jazz Musicians Network with betweenness centrality illus-
trated. The larger the node, the higher the betweenness centrality measure. The
graph representation was created by the authors using data from [6].
network communities. These agents are known as brokers. They are well
positioned to perform brokering roles across these clusters in the sense that
they connect otherwise disconnected people who yet may benefit from an
exchange of information.
Brokers are often critical to social networks in conflict zones as they col-
laborate across social clusters and can maintain the spread of information
through an entire network. Because of their locations between network com-
munities, individuals with high betweenness are often overlooked. This oc-
curs because they are not central to any single social cluster, and instead
reside on the periphery of several such clusters. These clusters tend to en-
gender more trust and admiration within rather than outside of the cluster.
Women in conflict zones that have a high betweenness measure can assist in
sharing information among various clusters of a social network.
James R. Gatewood and Candice Rene´e Price 15
4.1.4. Eigenvector Centrality
Probably the most mathematically sophisticated centrality measure, eigen-
vector centrality measures how well connected an agent is to other well con-
nected agents, reminiscent of the catchphrase: It is not what you know but
who you know. High eigenvector centrality represents a highly connected
agent that is connected to other highly connected agents.
To calculate eigenvector centrality, we first construct an adjacency ma-
trix, A, that describes who is connected to whom in the social network. We
use equation aij for our entries in the matrix; see Figure 5below. Using
the eigenvalue equation, Av =λv, we calculate the eigenvalues λthat are
the scalar solutions to this equation. There can be many different λvalues;
we choose the largest eigenvalue. After making this choice, we then find the
associated eigenvector. This eigenvector, v, provides us the eigenvector cen-
trality measure for each agent in the network. The largest component in the
eigenvector corresponds to the agent with the highest eigenvector centrality.
Figure 5: Sample graph and adjacency matrix. Example graph with 5
vertices and 5 edges and its adjacency matrix AG.
High eigenvector centrality individuals are usually the leaders of the com-
munity. These are the agents in the network that governments, organizations,
and those who are catalysts for change would seek out to better understand
the needs of the community. They can also be utilized to create global
changes to the social network. When studying women in conflict zones, it
is important to connect with these leaders to find what information and
resources are needed in the community.
An example demonstrating this notion in the context of our jazz musicians
network is provided in Figure 6below.
16 Social Network Analysis of Women in Conflict Zones
Figure 6: Jazz Musicians Network with eigenvector centrality illus-
trated. The larger the node, the higher the eigenvector centrality measure. The
graph representation was created by the authors using data from [6].
5. Data Collection
One way to determine the well being of women in conflict zones is to con-
duct surveys. When conducting a survey, one can try to ask questions that
will lead to information about an individual’s family, community and social
structure. In Appendix Awe provide an example of a survey with specific
questions that could help develop a social network model. Gathering all the
data and incorporating the findings into several social network graphs, one
can begin to see the social structure among women. One can then analyze
the data collected by utilizing the methods discussed in Section 4. Commu-
nicating constantly with women involved in these surveys will build trust and
can also empower them to take control of their situation or at least utilize
the power they have to rebuild their lives.
James R. Gatewood and Candice Rene´e Price 17
Although we believe that this is an appropriate tool to approach women
in conflict zones, there are limitations to this course of action to gathering
data. As with any survey, researchers must ask themselves the following
questions before embarking on the study:
Which communities do we want to study?
How do we define community?
What are the cultural biases we as the researchers bring to the study?
What are the aims of the study?
Who in the community is included and excluded in the study?
Researchers must be cautious and understand the challenges of collecting
data in conflict zones. Because political events associated with conflict can
lead to destabilization and chaos, researchers must be aware of issues such as
apathy, displacement of families, refugee status, and negative repercussions
from opposing forces. Also, researching in such a zone is not a “neutral” ac-
tivity [1,2]. Situations in these zones are fluid and results drawn from survey
data may or may not be valid conclusions of the true impact. Researchers
should also consider that they have some impact during conflict, even if
minimal. Furthermore standard survey processes might or might not be ap-
plicable when drawing conclusions. A researcher in a conflict zone also has
to take into account that there will be numerous unpredictable parameters.
With all these caveats, we enthusiastically endorse the idea that building
a social network model within troubled regions based on these surveys will
help us understand the structure of women’s communities and identify key
individuals and groups that will in turn help rebuild and empower the lives
of women.
18 Social Network Analysis of Women in Conflict Zones
A. Sample Survey
1. Id Number
2. What is your Age?
3. Which gender do you identify with?
a. Female
b. Male
c. Other
4. Where geographically do you reside (your community group)?
5. Who are the members in your community?
(Family members, friends, associates, etc)
6. With whom do you communicate with on a daily basis?
7. Who do you respect and value to make decisions in your life? Or whose opinion do you
consider when making decisions?
8. Which groups do you associate with or are a part of?
(Church groups, community organizations, places, etc)
9. Do you hold any leadership position in any organization?
James R. Gatewood and Candice Rene´e Price 19
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... A tool to study social interactions is social network analysis (SNA) which has previously been used in several domains, including natural resources governance or conflict management (Gatewood & Price, 2017;Ngaruiya & Scheffran, 2016). The use of SNA brings together a quantitative and qualitative approach for the integrated analysis of political, economic or social processes in connection to structural and environmental processes (Bodin & Prell, 2011). ...
... The use of SNA brings together a quantitative and qualitative approach for the integrated analysis of political, economic or social processes in connection to structural and environmental processes (Bodin & Prell, 2011). Conflict has the potential of breaking social structures in a region (Gatewood & Price, 2017). As a result of the conflict between Boko Haram insurgents and governmental forces in northeast Nigeria, communities are displaced and forced into new social structures. ...
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In this study, we aim to analyze social networks in which internally displaced persons (IDPs) are involved in northeast Nigeria, after they have been displaced by the insurgency of the Boko Haram group. While IDPs usually resettle in camps operated by the government, contacts with host communities are common. We further analyze the potential that such contacts may lead to conflicts between IDPs and their host communities in the Lake Chad region. Data for this study were collected by interviewing IDPs in the Bakassi IDP camp in Maiduguri and by interviewing members of the host community in Maiduguri in close proximity to the Bakassi IDP camp. A Social Network Analysis approach was used to analyze the data, by constructing social network graphs and computing network attributes, mainly the betweenness centrality of actors. The results of the study show on the one hand a mixture of friendly and conflicting relationships between IDPs and the host community from the IDPs’ perspective, and on the other hand, only few contacts between members of the host community and IDPs in the Bakassi IDP camp, from the host community's perspective. The analysis suggests that in the context of conflict present in the Lake Chad region, IDPs and members of the host community mainly use closed networks, to keep available resources and economic opportunities within their communities. We recommend a better service delivery to IDPs but also to members of the host communities who feel neglected as more attention is given to IDPs with the distribution of humanitarian aid.
... Pre-and post-multiplication of the adjacency (i.e. graph links exist if pixels share non-zero length boundaries -known as the rook definition -or both zero and non-zero length boundaries -known as the queen definition) or spatial weights matrix C for this surface partitioning by the projection matrix (I -11 T /n) essentially replaces its principal eigenfunction [the one visualized by Maćkiewicz and Ratajczak (1996), and by Gatewood and Price (2017)] with one having an eigenvalue of 0 and an eigenvector proportional to vector 1, an eigenfunction already part of the accompanying Laplacian matrix. The remaining eigenfunctions are the same or asymptotically the same as those for matrix C. ...
Existing interfaces between mathematics and art, and geography and art, began overlapping in recent years. This newer overarching intersection partly is attributable to the scientific visualization of the concept of an eigenvector from the subdiscipline of matrix algebra. Spectral geometry and signal processing expanded this overlap. Today, novel applications of the statistical Moran eigenvector spatial filtering (MESF) methodology to paintings accentuates and exploits spatial autocorrelation as a fundamental element of art, further expanding this overlap. This paper studies MESF visualizations by compositing identified relevant spatial autocorrelation components, examining a particular Van Gogh painting for the first time, and more intensely re-examining several paintings already evaluated with MESF techniques. Findings include: painting replications solely based upon their spatial autocorrelation components as captured and visualized by certain eigenvectors are visibly indistinguishable from their original counterparts; and, spatial autocorrelation supplies measurements allowing a differentiation of paintings, a potentially valuable discovery for art history.
... Gatewood and Price [38] analyze a social network of jazz musicians (Reference [39]; n = 198, density = 14.1%) that is available in this KONECT dataset collection. Their response variable is the degree of centrality within this network, which is the principal eigenvector of n-by-n matrix C ( Figure 5a). ...
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This paper proposes a new classification of correlated data types based upon the relative number of direct connections among observations, producing a family of correlated observations embracing seven categories, one whose empirical counterpart currently is unknown, and ranging from independent (i.e., no links) to approaching near-complete linkage (i.e., n(n – 1)/2 links). Analysis of specimen datasets from publicly available data sources furnishes empirical illustrations for these various categories. Their descriptions also include their historical context and calculation of their effective sample sizes (i.e., an equivalent number of independent observations). Concluding comments contain some state-of-the-art future research topics.
Sociological social psychology emphasizes the impacts of society on social psychological processes. There are three major perspectives in sociological social psychology: symbolic interaction, social structure and personality, and group processes. The symbolic interactionist perspective emphasizes the ways that individuals construct social reality through social interaction. Alternatively, the social structure and personality perspective emphasizes the relatively stable elements of social structure that impact interactions among people such as roles, statuses, and norms. Finally, the group processes perspective focuses on the ways that societal conditions are recreated in small group environments and how interactions in groups contribute to the maintenance of society. These perspectives are being extended to include the study of sociobiology, the intersection of social and biological conditions that impact social psychological process.
The Connected City explores how thinking about networks helps make sense of modern cities: What they are, how they work, and where they are headed. Cities and urban life can be examined as networks, and these urban networks can be examined at many different levels. The book focuses on three levels of urban networks: Micro, meso, and macro. These levels build upon one another, and require distinctive analytical approaches that make it possible to consider different types of questions. at one extreme, micro-urban networks focus on the networks that exist within cities, like the social relationships among neighbors that generate a sense of community and belonging. at the opposite extreme, macro-urban networks focus on networks between cities, like the web of nonstop airline flights that make face-to-face business meetings possible. This book contains three major sections organized by the level of analysis and scale of network. Throughout these sections, when a new methodological concept is introduced, a separate ‘method note’ provides a brief and accessible introduction to the practical issues of using networks in research. What makes this book unique is that it synthesizes the insights and tools of the multiple scales of urban networks, and integrates the theory and method of network analysis.
When NATO nations responded to complex emergencies in the early 1990s, they found themselves operating in conflict zones with many unfamiliar actors. The international military contingents were no longer the principle organisers of the "battle field". The presence of large, vulnerable populations called for the involvement of a host of civil agencies to provide immediate humanitarian relief as well as the long term requirements for development, nation building and security sector reform. Two different approaches towards co-operation co-existed. Among the military there was a universal recognition of the need for co-ordination. But the civilian organisations represented a much wider array, or disarray, of disciplines, conflicting charters and in some cases, unbridled rivalry. They were suspicious of attempts to organise them into a co-operative structure because for many, successful competition had been the basis of their survival and success. At the beginning of the 1990s, co-ordinating the elements of the international response in the conflict zone was therefore seen as unachievable by the military element and undesirable by the civil organisations. However as the number of interventions increased, a model for conducting themselves in a co-operative manner began to emerge. In many cases the military and civilian actors in each intervention were the same. At a local level co-operative structures began to grow between them, in the civil sector these were orchestrated by lead organisations and among the military, by the framework provider or lead nation. Despite the same actors participating in each emergency, the co-operative linkages between them relied on the personalities at the interfaces between them, rather than the institutionalisation of their relationships . The structures they created were ephemeral and had to be recreated for each new contingency. By the end of the decade Kosovo represented a template for these operations; if not a model for success at every level, it was at least a methodology on which to build a co-operative structure that might survive from one operation to another. The attack on the 11 September jeopardises this aspiration. Although the deployment to Afghanistan has a familiar ad hoc and incremental character , the nature of the coalition and the operation itself are essentially different to the Kosovo model and may stand at the threshold of a new genre of operations . Despite many reasons for the military and the civilian agencies to be more co-ordinated , no strongly based structures have emerged so far . Until the elements of the international response are confronted more immediately and closer to home by the consequences of a dramatic failure , the ad hoc approach may continue.
Many structural definitions for social community have been proposed in attempt to characterize and further understand the structure of social relationships. Algorithms using quantitative concepts such as centrality measures, spectral methods and other clustering measures have been used to compute social communities. While these methods have had much success in extracting meaningful subgroups in social and biological (and other) networks, they do not necessarily reveal the defining structure of social attraction.We propose a new definition here for social community with a very clear and simple graph-theoretic structure which can also be realized as a new clique-relaxation. This structure evolved from Freeman's definition of social community, and this definition is further supported by long-standing sociometric principles such as Granovetter's weak-tie hypothesis or Faust's and others’ studies on how global structure can be inferred from a complete understanding of local structures (although our definition goes beyond dyadic and triadic configurations). We provide computational results that show our simply-stated structural definition reveals communities that correspond almost identically to, and sometimes are better than, the widely used centrality-based methods.We name these new communities familial groups, inspired by the network structures resulting from inheritance or blood-line relations. These structures form naturally in hierarchical arrangements such as in corporate settings. Using results from graph theory, our structural definition for familial groups also immediately implies a ranking of the individuals within the group, easily identifying leaders and subcommunities.
We argue here that processes of political centralization and hierarchy building can be profitably explored by focusing on how resources were strategically manipulated in search of power by people organized in social networks of varying sizes and spatial extents. Adopting this perspective encourages reconsideration of the ways in which such core concepts as structure, agency, and society can be redefined to cast new light on ancient power contests. In addition, we suggest that a network approach complements traditional emphases on processes of domination and resistance by drawing attention to the importance of alliances in shaping political formations. The potential utility of these precepts is illustrated in an example drawn from our research on Terminal Classic (800–1000 AD) political struggles in the Naco valley of northwestern Honduras. Special attention in this case centers on the manner in which craft products were manipulated by people of varying ranks to define and achieve goals as well as to control the actions of others. The study’s broader implications for the analysis of ancient political relations are highlighted at the essay’s conclusion.
In the field of post-conflict reconstruction, gender-related issues are mostly analyzed through a legal or a development paradigm. These conditions, coupled with a general disinclination by the international community — the industrialized, western countries — to challenge cultural norms, whether real or imagined, allows for a security-first and/or a security-development nexus to take precedence regarding post-conflict reconstruction. This paper advances the argument that by viewing gender issues as existential to the security of a state transitioning out of conflict, as opposed to viewing gender as a development or a legal issue, makes it possible to engage in real reconstruction, which means addressing the gender bias that dominates many societies.
introduction to social networks, interesting the centrality chapter.
Surveys provide crucial information about the social consequences of armed conflict, but armed conflict can shape surveys in ways that limit their value. We use longitudinal survey data from throughout the recent armed conflict in Nepal to investigate the relationship between armed conflict events and survey response. The Chitwan Valley Family Study (CVFS) provides a rare window into survey data collection through intense armed conflict. The CVFS data reveal that with operational strategies tailored to the specific conflict, duration of the panel study is the main determinant of attrition from the study, just as in most longitudinal studies outside of conflict settings. Though minor relative to duration, different dimensions of armed conflict can affect survey response in opposing directions, with bombings in the local area reducing response rates but nationwide political events increasing response rates. This important finding demonstrates that survey data quality may be affected differently by various dimensions of armed conflict. Overall, CVFS response rates remained exceptionally high throughout the conflict. We use the CVFS experience to identify principles likely to produce higher quality surveys during periods of generalized violence and instability.