PhD in Political Sciences / Computational Social Sciences (M/F)

Updated: 25 days ago
Location: Paris La Defense, LE DE FRANCE
Job Type: FullTime
Deadline: 25 Apr 2024

5 Apr 2024
Job Information
Organisation/Company

CNRS
Department

Institut des Systèmes Complexes de Paris Île-de-France
Research Field

Physics
Researcher Profile

First Stage Researcher (R1)
Country

France
Application Deadline

25 Apr 2024 - 23:59 (UTC)
Type of Contract

Temporary
Job Status

Full-time
Hours Per Week

35
Offer Starting Date

1 Oct 2024
Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme
Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

This thesis project will be developed using data from the Politoscope of the Paris Institut of Complex Systems (Institut des Systèmes Complexes de Paris Ile-de-France, ISC-PIF) and the European Polarisation Observatory of Sciences Po, which represent a privileged source of data on social networks.

The data from the European Polarization Observatory includes user interaction data on Twitter with political elites from 30 European countries. These data provide a valuable source for comparative studies. The data from the Politoscope project is centered on the activity of Twitter in France, encompassing a decade of collection, enabling an important longitudinal dimension of the project.

The PhD student will work physically in Paris, between the ISC-PIF and Sciences Po. The scientific ecosystem for the development of the thesis offer a world-leading center in political sciences, as well as a diverse interdisciplinary environment integrating researchers in mathematics, computer sciences, sociology, and connections with researchers working in platform regulation and policy-making.

An important part of comparative political analysis is based on the position of parties on the political spectrum: right-left axis, attitudes towards immigration, redistribution or even environmental protection. Conventional approaches to estimating party positions include the use of "expert surveys" in which political science experts provide individual subjective estimates (rating each party on Likert scales for different policy topics, and including the Chapel Hill Expert Survey or the Global Party Survey are well-known examples). Alternatively, other approaches rely on the texts of party manifestos through annotations or NLP methods (for example, by automatically identifying named topics and positive attitudes or negative towards them). These important resources require, however, in their construction, considerable resources and limit the temporal resolution available for longitudinal studies. A third line of approaches – ideological spatialization methods (ideological scaling or ideal-point estimation) – exploit traces of behavioral data. These approaches are based on Item-Response Theory frameworks to position individuals on the parameter spaces of choice models, from which the dimensions of attitudes towards political issues are then derived. In the 2010s, these approaches expanded to include social media data, positioning political elites and large populations of users based on how they perceive the positions of political elites, but on dimensions tailored to the political analysis in the American context. The European context is, however, different in terms of dimensionality: different studies (whether at the level of the population or of political elites) show the need to consider multiple issue and ideology dimensions to explain the different choice data. The need for this multidimensionality imposes a series of conceptual and methodological challenges.

In this project, the PhD student will work with social media and political survey data to propose methods to produce and assess political position estimates based on behavioral data. A first aim of this study is to explore the extent to which social media data can be leveraged to produce issue and ideology positions for political parties in a way that allows for comparative studies across Europe, and for granular longitudinal studies. Building on the responses to this methodological challenge, the PhD student will engage in research leveraging social media data and computational methods producing comparative analysis, focusing on the evolution of polarization and the dimensionality of political competition in Europe.

Desired profile:

Political science students with strong methodological background
Students with strong computational/data knowledge and skills are particularly encouraged to apply

Date of start: 1 October 2024
Duration of the contract: 3 years.


Requirements
Research Field
Physics
Education Level
PhD or equivalent

Languages
FRENCH
Level
Basic

Research Field
Physics
Years of Research Experience
None

Additional Information
Website for additional job details

https://emploi.cnrs.fr/Offres/Doctorant/UAR3611-PEDRAM-003/Default.aspx

Work Location(s)
Number of offers available
1
Company/Institute
Institut des Systèmes Complexes de Paris Île-de-France
Country
France
City
PARIS
Geofield


Where to apply
Website

https://emploi.cnrs.fr/Candidat/Offre/UAR3611-PEDRAM-003/Candidater.aspx

Contact
City

PARIS
Website

http://iscpif.fr

STATUS: EXPIRED

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