Annonce en lien avec l’Action/le Réseau : aucun
Laboratoire/Entreprise : LPTM/ETIS
Durée : 12 months
Contact : Dimitrios.Kotzinos@u-cergy.fr
Date limite de publication : 2017-12-20
Contexte :
A one-year post-doctoral position is open in the framework of the OpLaDyn project (Understanding Opinion and
Language Dynamics using massive data), a recently selected project of the TransAtlantic Digging into Data
Challenge,
https://diggingintodata.org/awards/2016/news/winners-round-four-t-ap-digging-data-challenge.
This is an international project in which a team with expertise in Data Science, Physics, Linguistics, Philosophy
and Law aims to study problems in Human Social Sciences developing an interdisciplinary view of the relation
between information patterns in Big Data and the dynamics of social actions, bridging the gap between Social
and Natural Sciences.
Big Data technologies are changing the informational environment in which people live, keeping traces of their
activities, merging behavior and decision-making processes of social actors. Based on textual data obtained
from different media, we will study emerging patterns in social actions, focusing on opinion diffusion and
language evolution.
In the framework of this project, the team has access to the historical database of The New York Times, which
gathers documents covering over more than 150 years. These can be combined with modern databases like
Twitter, in order to develop comparative studies on opinion and language dynamics.
Sujet :
By analyzing large bases of textual data we aim at extracting patterns of relevant information, in order to
construct data based models of opinion formation and evolution.
This implies addressing, among others, the following questions:
How can relevant information be obtained from the Big Data sources at disposal in order to build data
based models of opinion dynamics? What is the role of the metadata in this endeavor?
How can one infer the network of social contacts on the basis of these data?
How can one capture opinion dynamics? Which parameters characterize the dynamical process? How
these parameters depend on the type of media where opinion diffuses?
More specifically, using the NYT database, which runs over a long period (roughly from1850 until now), we are
interested in understanding how scientific topics of high societal impact migrate from the channels restricted to
scientists to the public media and how this diffusion contributes to fashion the public opinion on those particular
topics.
Profil du candidat :
Candidates should hold a PhD in Physics or in Computer Science, with some knowledge in the area of social
networks, opinion dynamics or information diffusion. She/he should have good modeling and programming
skills. Some knowledge on data management and notions of cloud-based computing are also appreciated.
Formation et compétences requises :
Candidates should hold a PhD in Physics or in Computer Science, with some knowledge in the area of social
networks, opinion dynamics or information diffusion. She/he should have good modeling and programming
skills. Some knowledge on data management and notions of cloud-based computing are also appreciated.
Adresse d’emploi :
The selected candidate will work at Laboratoire de Physique Théorique et Modélisation (LPTM)
UMR8089 CNRS-UCP, https://www.u-cergy.fr/fr/laboratoires/labo-lptm.html , in collaboration with Laura
Hernández (LPTM) and Dimitris Kotzinos, from ETIS laboratory of Cergy-Pontoise University (Paris-Seine
University). She/he will benefit from the working environment of both laboratories and will take part in the
activities of the OpLaDyn team.
Contacts:
Laura Hernández, Laura.Hernandez@u-cergy.fr
Dimitris Kotzinos, Dimitrios.Kotzinos@u-cergy.fr
Website: http://project.u-cergy.fr/~opladyn/
Document attaché : PostDoc_opinion_dyn.pdf