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Complex Networks team

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Academic year: 2022

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Complex Networks team

http://complexnetworks.fr

LIP6 laboratory (CNRS, Sorbonne Universit´e)

http://complexnetworks.fr 1/8

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Networks/graphs from different contexts

computer science: internet, P2P, web, usages, etc.

social sciences: friendships, communications, collaborations, exchanges, economics, etc.

biology: brain, genes, proteins, ecosystems, etc.

linguistics: synonymy, co-occurrences, etc.

transportation: roads, air, electrical networks, etc etc

Various contexts, but common properties

common problems to solve

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Some common questions

Measurement and metrology

How to acquire data about these networks? Reliability?

Algorithmic questions

Efficient computations on very large networks

Modelling

Generate artificial networks resembling a given network

⇒Goals: understanding, simulations, . . .

Analysis

How to describe the structure of very large networks?

http://complexnetworks.fr 3/8

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Multiscale Analysis of Dynamical Networks (R. Lamarche-Perrin)

Going from the aggregation of static graphs...

...to the aggregation of dynamic graphs

a bc d

0 5 10 15 20 time

e

Spacial aggregate Temporal aggregate

field: modelling, algorithmics

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Opinion Dynamics & Political Conflicts in the Media (R. Lamarche-Perrin)

Opinion dynamics in social media (Twitter, Facebook, Instagram) Analysis of interaction patterns:

polarisation effects, echo chambers, filter bubbles, information leadership

Conflicting world views inmass media(printed press)

Study the co-occurrences of countries in articles from different newspapers

field: data analysis, interdisciplinary

http://complexnetworks.fr 5/8

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Node Ordering for Efficiency and Compression (M.Danisch)

Handling very large graphs (billion of nodes, links)

Ordering nodes is a key problem to solve a variety of problems:

listing cliques, counting motifs, compressing graphs . . . Project: design efficient orderings to make compression algorithms more efficient

field: algorithmics

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Characterizing navigation traces (L. Tabourier)

Data:individual navigation traces including temporal info (logs) on a website (Melty) with information about categories of pages Previous works:

Measurements to describe navigation sessions and diversity Current project:

Several recommendation systems

effect of recommendation on navigation

field: data analysis, interdisciplinary

http://complexnetworks.fr 7/8

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Conclusion

Topics require

some data manipulation some formal approaches

some taste in interdisciplinary matters To be discussed with the applicant

More details: http://www.complexnetworks.fr/projects/

Contact: [email protected]

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