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  <front>
    <journal-meta />
    <article-meta>
      <contrib-group>
        <aff id="aff0">
          <label>0</label>
          <institution>Proceedings of the 16th All-Russian Conference “Digital Libraries: Advanced Methods and Technologies</institution>
          ,
          <addr-line>Digital Collections” ― RCDL-2014, Dubna</addr-line>
          ,
          <country country="RU">Russia</country>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>Sergey Chernov Center for the Study of New Media and Society, New Economic School</institution>
          ,
          <addr-line>Moscow</addr-line>
        </aff>
      </contrib-group>
      <fpage>10</fpage>
      <lpage>12</lpage>
      <abstract>
        <p>Computer science research community devoted a special attention to the studies of online social networks. In the meantime, we observed that algorithms and data processing techniques are often not enough to fully exploit research potential of social data available. One needs a set of models and methods explaining social interaction to pose meaningful questions on the wealth of data. This is a moment when social sciences come into a picture providing the necessary tools and knowledge. Here we review some research papers on online social networks, which have been published in the fields of economics, sociology, psychology and political science. We hope, such an interdisciplinary view on the social network research might help to eliminate existing gap between information management experts and scholars from social sciences.</p>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>1 Introduction</title>
      <p>Recent boom of online social networks provided
computer scientists with a lot of new research directions
and inspired numerous efficient algorithms for scalable
network analysis. In addition, it motivated scholars
from social sciences like economics, sociology,
psychology and political science, to catch up with
modern data processing techniques. The massive
datasets of digitized social data attracted social
scientists, who rarely worked with terabytes of
information or used scalable data analysis algorithms.
Their usual toolbox is tailored to hundreds and
thousands of data points, which are rather trustworthy
and verifiable. In contrast, contemporary social graphs
are built from millions of nodes and billions of edges,
the data is highly dynamic, incomplete, unreliable and
difficult to interpret.</p>
      <p>It is reasonable to assume that online analytical tools
from computer science will be widely adopted by social
scientists in a short term prospective and current
technological gap will be eliminated. On the other hand,
the social disciplines will stay superior in posing right
questions on social data, which is a key skill in
understanding characteristics and mechanisms of a
modern society. Such division of competencies creates
a need for the interdisciplinary research teams and a
number of highly visible research papers were produced
by consortia of social and data processing experts.</p>
      <p>To provide an overview of problems and challenges
addressed by the social sciences using online networking
data, we selected a set of publications from four
aforementioned branches of social sciences. Each study is
summarized into a key research question, a method used and
a general outcome. We grouped these works by the field of
study, while some papers might be attributed to two or more
disciplines. We also made an attempt to mention some
national papers where applicable. Finally, some relevant
studies completed with support from the Center for the
Study of New Media and Society were added to the picture.</p>
    </sec>
    <sec id="sec-2">
      <title>2 Psychology</title>
      <p>
        An interesting compilation of papers on online
addiction is prepared by Kuss and Griffiths [
        <xref ref-type="bibr" rid="ref19">19</xref>
        ]. One of the
most comprehensive reviews of psychologically oriented
research using Facebook was done by Wilson, Gosling, and
Graham in 2012 [
        <xref ref-type="bibr" rid="ref32">32</xref>
        ]. A large volume of more than 400
articles has been split into five categories including: into 5
categories: descriptive analysis of users, motivations for
using Facebook, identity presentation, the role of Facebook
in social interactions, and privacy and information
disclosure. Descriptive analysis focuses on Facebook users
and their typical online behaviour. Motivations part is about
why people use Facebook and identity presentation is about
how they want to look for the outside world. Social
interaction category studies relationships between
individuals and groups. Finally, privacy and information
disclosure papers target various trade-offs between personal
information sharing and associated risks.
      </p>
      <p>
        Following the proposed categories, we pick few
representative papers from each. For example, in-house
Facebook research lab published in 2011 one of the
largest studies describing inhabitants of the biggest
social network [
        <xref ref-type="bibr" rid="ref2 ref27 ref3">2, 3, 27</xref>
        ]. For the motivation study we
take an example addressing psychological well-being
and increased social capital of the users [
        <xref ref-type="bibr" rid="ref23">23</xref>
        ]. A case
study of identity representation from [
        <xref ref-type="bibr" rid="ref29">29</xref>
        ] confirms old
wisdom that attractive photos are more likely to help in
getting new friends than unattractive ones. One recent
work which caught quite some attention in press is
devoted to social interactions, in particular, Backstrom
and Kleinberg [
        <xref ref-type="bibr" rid="ref4">4</xref>
        ] studied possibility of identifying
romantic relationship between two people based on
their network neighborhood alone. The results are
promising and might lead to finding structurally
significant people in various online applications.
      </p>
    </sec>
    <sec id="sec-3">
      <title>3 Sociology</title>
      <p>
        The methods of sociological research could be
considered as the most demanded from the computer
science community. Several basic notions in social
network analysis have deep roots in sociology, starting
from the famous works by Granovetter granovetter1973
or by Travers and Milgram [
        <xref ref-type="bibr" rid="ref25">25</xref>
        ]. A good introductions
into a sociological prospective on modern social
network analysis include work by Marin and Wellman
[
        <xref ref-type="bibr" rid="ref20">20</xref>
        ] or by Hansen, Shneiderman and Smith [
        <xref ref-type="bibr" rid="ref16">16</xref>
        ], while
a standard textbook in this area belongs to Faust
andWasserman [
        <xref ref-type="bibr" rid="ref30">30</xref>
        ]. Among research topics addressed
by modern sociologists we observe a popular thema of
geo-dependencies of social ties, which has already
produced several crossdisciplinary teams [
        <xref ref-type="bibr" rid="ref22 ref24 ref28">22, 24, 28</xref>
        ].
Another hot topic is a cascade-behavior prediction [
        <xref ref-type="bibr" rid="ref13 ref7">7,
13</xref>
        ], which promises numerous potential benefits for the
information diffusion applications. A more specific task
in the same direction is measuring the influence on
information sharing of each particular node [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ].
      </p>
    </sec>
    <sec id="sec-4">
      <title>4 Economics</title>
      <p>
        Thanks to the excellent textbooks by Matthew Jackson
[
        <xref ref-type="bibr" rid="ref18">18</xref>
        ] and by Easley and Kleinberg [
        <xref ref-type="bibr" rid="ref9">9</xref>
        ], we currently have a
good overview of the role of social networks in economics.
For a short intro in this area one is advised to look at a
brief summary [
        <xref ref-type="bibr" rid="ref17">17</xref>
        ]. However, economics research is often
focused on small-scale networks from offline world, rather
than on massive online datasets. Situation is changing
nowadays and more and more papers address online
networks in the economics science, for an up-to-date
review one might look into a work by Ravasan, Rouhani
and Asgary [
        <xref ref-type="bibr" rid="ref21">21</xref>
        ]. A lot of available studies concentrate on
applied questions, for example, work by Acquisti and
Fong [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ] shows how online information could be used for
discrimination during in a hiring process. Another
interesting topic is connected to online fundrising
potential [
        <xref ref-type="bibr" rid="ref6">6</xref>
        ]. Some early studies in political economy
show dependencies between online activity and offline
movements [
        <xref ref-type="bibr" rid="ref10">10</xref>
        ].
      </p>
    </sec>
    <sec id="sec-5">
      <title>5 Political Science</title>
      <p>
        Modern political science is a lot more about proper
math and heavy computing as it was ever before.
Researcher perform complex data analysis on millions
of tweets and online texts to better understand current
political issues and verify classic models and theories of
the field. A recent outburst of civil movements
supported by visible online activity was recently studied
in Egypt [
        <xref ref-type="bibr" rid="ref26">26</xref>
        ], Spain [
        <xref ref-type="bibr" rid="ref14">14</xref>
        ], USA [
        <xref ref-type="bibr" rid="ref8">8</xref>
        ] and Russia [
        <xref ref-type="bibr" rid="ref15">15</xref>
        ].
Other interesting topics include debates around political
economy of privacy on Facebook [
        <xref ref-type="bibr" rid="ref11">11</xref>
        ] and Internet
surveillance [
        <xref ref-type="bibr" rid="ref12">12</xref>
        ]. Regarding applications, some
interesting vizualizations around political activites are
developed in [
        <xref ref-type="bibr" rid="ref31">31</xref>
        ].
      </p>
    </sec>
    <sec id="sec-6">
      <title>6 Conclusions</title>
      <p>This survey is a minor step towards better
cooperation between computer science and social
sciences communities. A set of research problems listed
above is not exhaustive by any means, but rather a basic
selection for future development. We hope, interested
readers will follow the way of diving into alien, but
interesting research disciplines, and will find necessary
bits of knowledge, which are invisible within their
native research circle.
Сергей Чернов</p>
    </sec>
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