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Job Talks - Assistant Professor in computational social science

The shortlisted candidates for the position of Assistant prof. in computational Social Sciences will present their research

Event, Job Talks

Salle N207, 1 Place Saint-Thomas-d’Aquin, 75007 Paris

Auditions schedule

8h30 : Pedro Ramaciotti Morales on "The geometry of misinformation: The link between polarization and misinformation in online multidimensional political settings"

Pedro Ramaciotti Morales (PhD in Applied Mathematics at École Polytechnique) has been a researcher at the computer science department at Sorbonne University, and at the Centre for European Studies and the médialab at Sciences Po. His research interests – at the interface between social  sciences and both computational and modeling approaches – revolve around political dynamics in online social platforms, including online political competition systems, algorithmic mediation, social movements, and media ecosystems.

9h20 : Mathilde Emeriau on "In or Out? Xenophobic Violence and Immigrant Integration. Evidence from 19th century France"

Mathilde Emeriau is an Assistant Professor in the department of Government at LSE. She graduated from Stanford University in 2019 with a PhD in Political Science. Her research centers on discrimination and immigrant integration with a special focus on France. She combines historical data, original data collection, and government surveys to study the conditions under which immigrants integrate into their host communities.

10h10 : Oscar Stuhler on "Analyzing Textual Representations of Social Structures"

Oscar Stuhler is a PhD candidate in sociology at New York University. He studies public discourse with computational methods. His  primary research focus is to develop methods and theory for a formal  analysis of textual representations of social structures.

11h30 : Margaret Foster on "Between a Hammer and an Anvil: Bottom-Up Organizational Transformation"

Drawing on the literature on militant socialization and management, I propose a mechanism of grassroots-driven organizational change broadly applicable when leaders balance short-term survival  with long-term mission focus. However, the measurement of hidden processes---such as internal transformation--- presents a challenge, particularly in contexts that lack rich and accessible micro-level data. Thus, I present an empirical strategy that uses interpretable machine-learning techniques to derive insight in data-poor environments.

Margaret Foster is a Postdoctoral Fellow at the University of North Carolina at Chapel Hill. She is a computational social scientist studying the organizational dynamics and pathologies of resource-constrained, issue-motivated organizations, emphasizing the organizational dynamics of violent conflict actors. Methodologically, she maintains a line of research using tools of computational social science to develop insight and measure difficult concepts in otherwise data-poor environments, particularly emphasizing text-as-data and network approaches. Her ongoing projects include an Item Response Theory  (IRT) model with interpretable underlying theoretical dimensions, a strategy to quantify the abstract idea of “change” in militant groups, and a project conceptualizing and operationalizing the idea of “gridlock” in the context of international organizations. She received her Ph.D. from Duke University in 2020. Previously, she was an analyst at the SITE Intelligence Group, where she conducted deep qualitative research and helped to establish a monitoring and infrastructure for online extremist communities.

12h20 : Alex Kindel on "Working papers and the stylization of rigor among elite US economists"

Alex Kindel is a PhD candidate in Sociology at Princeton University. Alex is a historical sociologist and computational social scientist conducting research on prestige, aesthetics, and measurement. His work asks how prestigious social positions are produced and maintained  hrough performance, arrangement, materiality, and other stylistic aspects of social life. Alex is also interested in developing methods for evaluating machine learning measures of social and cultural  processes. In past and ongoing work, he has studied the predictability of complex longitudinal survey outcomes; how academic institutions cultivate investment and maintain favorable public image; the design of  data preparation software for complex social data structures; and the  comparative depiction of occupations on the popular US game show Jeopardy!.

Practical Informations

Job talks are open to public, registration are mandatory due to security reasons.

Job talks will be from 8:30am to 1pm.

Selection Committee

  • Christine Musselin (Chair) (DR CNRS, CSO)
  • Sylvain Parasie (Vice-chair) (PU médialab)
  • Achim Edelmann (Assistant Prof, médialab)
  • Laura Morales (PU, CEE)
  • Philipp Brandt (Assistant Prof, CSO)
  • Kinga Makovy (Assistant Prof, New York University Abu Dhabi)
  • Floriana Gargiulo (CR CNRS, GEMAS, Sorbonne Université) 
  • Thierry Poibeau (DR CNRS, ENS Paris-Saclay)
  • Sophie Mützel (Full Prof, sociologie, université de Luzern)
  • Eric Fleury (Professeur, Ecole Normale Supérieure de Lyon)