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PHD POSITION IN COMPUTER SCIENCE
Opinion Dynamics and Political Conflicts in the
Media - A Complex Networks Perspective
DATES: Fall 2017 - Fall 2020
WORKSITE: LIP6 / 4 place Jussieu / 75005 Paris
SALARY: 21k€ gross per year (plus eventual teaching
- Université Pierre-et-Marie-Curie
- École doctorale Informatique, Télécommunications et Électronique
- Laboratoire d'informatique de Paris 6 (UMR 7606)
- Équipe “Complex Networks” (www.complexnetworks.fr)
- Robin Lamarche-Perrin ([log in to unmask])
- Matthieu Latapy ([log in to unmask])
- Clémence Magnien ([log in to unmask])
This PhD position is founded by the European H2020 ODYCCEUS project
“Opinion Dynamics and Cultural Conflicts in European Spaces” that
started in January 2017 (www.odycceus.eu/project)
Please send to <[log in to unmask]>
before the 28th of May, 2017:
- a complete resume;
- a transcript of your master's grades;
- a summary of your master's thesis;
- a short covering letter (one or two pages) describing in more
details what would be your PhD project.
Applications in French and in English are welcome.
Social media and the digitisation of news are having
far-reaching effects on the way individuals and communities
communicate, organise, and express themselves. Can the information
circulating on these platforms be exploited to better understand and
analyse the enormous problems facing our contemporary society? Could
this help us to better monitor the growing number of social crises
due to cultural differences and diverging world-views? Studying the
structure of debates in the public sphere requires sophisticated
methods for the analysis of information flows between individuals.
How is information shaped and broadcasted by mass media? How to
describe the way opinions are discussed in social media? Debates are
often represented as complex entanglements of such social
interactions, embedded in space and time, and displaying a
multilevel structure: From individual to institutional discourses;
From regional to international matters; From the fast dynamics of
media “buzzes” to the slower dynamics of social controversies.
To address these challenging issues, this PhD position aims at
developing new methods for the analysis of multidimensional and
multilevel networks in social sciences. First, by building on recent
work in dynamical graph theory regarding the “link stream”
representation of evolving networks , which provides a novel and
intuitive formalism for the spatio-temporal description of social
interactions by focusing on their causal structure (who interacts
with whom, when) and concealing for a moment their content (how,
why, about what). Second, by integrating recent developments in
graph compression , which builds on information-theoretical data
compression , to provide a macroscopic perspective on such
interaction structures and thus achieve a global understanding of
complex interaction patterns.
The efficiency of the proposed analysis methods will then be
evaluated by empirical work on real data, in collaboration with
researchers in media studies, in political sciences, and in
quantitative geography that are working on the ODYCCEUS project.
First, by focusing on the analysis of opinion dynamics in social
media, such as Twitter, and looking at the topology and dynamics of
interactions related to a particular debate (e.g., climate change,
presidential elections, Brexit). Here, a focus will be put on the
study of typical interaction patterns between actors of the debate,
such as: polarisation, leadership, communitarianism, and solidarity
behaviours. Second, by focusing on the analysis of conflicting world
views in mass media , for example by modelling the news about
international conflicts as a dynamical graph between countries and
media outlets (citations in articles) or between couples of
countries (co-occurrences in articles). The world view of different
media outlets will then be compared by graph analysis, thus allowing
to exhibit particular behaviours depending on the geographical,
political, and cultural interests of the media.
Note that this PhD position does not require any
preliminary knowledge of the hereabove mentioned theoretical
frameworks (dynamical graph and graph compression), but however
requires the capacity to work with abstract formalisms in general,
in order to build generic and sound methods within the domain of
theoretical computer science. This PhD position also requires a
genuine interest for interdisciplinary work, and in particular a
curiosity for some of the research questions that arise in social
and political sciences about traditional media and social media.
- Developments in graph theory for the analysis of
dynamical and multilevel networks: for example, by building on the
“link stream” formalism  and on information-theoretical graph
- Implementation and documentation of algorithms, analysis, and
visualisation tools. Integration of these tools to a software that
will be developed within the ODYCCEUS project: the “Opinion
- Empirical validation of the theoretical contributions in
collaboration with social scientists on several case studies
regarding European debates or conflicts (e.g., refugee crisis,
Brexit, COP21, European elections).
- Learning about theoretical work in media studies and
in political sciences about the theory of agenda-setting to fit the
designed methods to the needs of sociological and political
- Comparing developed methods with those that will be developed in
parallel by other partners of the ODYCCEUS project (e.g., spacial
interaction models in quantitative geography, agent-based opinion
dynamic models in computational sociology).
- Dealing with real, complex, and large-scale data.
- Dissemination of the contributions through technical reports,
publications, demonstrations, and networking, in particular during
the consortium meetings of the ODYCCEUS project.
 Claude Grasland, Robin Lamarche-Perrin, Benjamin
Loveluck, and Hugues Pecout. L'agenda géomédiatique international :
analyse multidimensionnelle des flux d'actualité. L'Espace
Géographique, 45:25–43, 2016.
 Robin Lamarche-Perrin, Yves Demazeau, and Jean-Marc Vincent.
Building Optimal Macroscopic Representations of Complex Multi-agent
Systems. Application to the Spatial and Temporal Analysis of
International Relations through News Aggregation. Transactions on
Computational Collective Intelligence, XV:1–27, 2014.
 Robin Lamarche-Perrin, Tiphaine Viard, and al. A General
Framework for Graph Aggregation. arXiv.org, CoRR, Forthcoming in
 Tiphaine Viard, Matthieu Latapy, and Clémence Magnien. Computing
maximal cliques in link streams. Theoretical Computer Science,
Centre national de la recherche scientifique
Institut des systèmes complexes de Paris Île-de-France
Laboratoire d'informatique de Paris 6
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