Applied Computational Social Sciences
Data-Intensive Governance - PSL Institute

Une expertise de recherche en sciences sociales articulée avec des capacités en sciences des données pour :

  • Renforcer la pertinence de la recherche académique sur les grandes problématiques sociétales
  • Eclairer la décision publique et privée
  • Favoriser une meilleure gouvernance collective

Prochaines sessions des groupes de travail

2024-03-04 at 17:30h - Public governance working group

Kai Gehring (University of Bern)

Analyzing Climate Change Policy Narratives with the Character-Role Narrative Framework

Abstract: Understanding behavioral aspects of collective decision-making is an important challenge for eco- nomics, and narratives are a crucial group-based mechanism that influences human decision- making. This paper introduces the Character-Role Narrative Framework as a tool to systematically analyze narratives, and applies it to study US climate change policy on Twitter over the 2010- 2021 period. We build on the idea of the so-called drama triangle that suggests, within the context of a topic, the essence of a narrative is captured by its characters in one of three essential roles: hero, villain, and victim. We show how this intuitive framework can be easily integrated into an empirical pipeline and scaled up to large text corpora using supervised machine learning. In our application to US climate change policy narratives, we find strong changes in the frequency of simple and complex character-role narratives over time. Using contagiousness, popularity, and sparking conversation as three distinct dimensions of virality, we show that narratives that are simple, feature human characters and emphasize villains tend to be more viral. Focusing on Donald Trump as an example of a populist leader, we demonstrate that populism is linked to a higher share of such simple, human, and villain-focused narratives.

2024-03-11 at 17:30h - Public governance working group

Rosanne Logeart (Paris School of Economics)

Does Access Mean Success? Connection to Policy-Makers and Lobbying Success of Political Actors

Abstract: This article aims at understanding the policy-making process by examining the relationship between access to policy-makers and lobbying success. I collect unique large-scale textual data on the content of lobbying activities and their subsequent policy changes. I identify instances of lobbying success with two complementary approaches: one based on a plagiarism-detection algorithm and the other on GPT. I match this novel data with meetings held between policy-makers and interest representatives to measure access to policy-makers. It reveals notable disparities in access, with the business sector having more access to policy-makers than the civil society. Moreover, I find that access to policy-makers is associated with a higher likelihood of lobbying success, by 11 percent of one standard deviation. This increased success likelihood is larger for entities with more access, as measured by the number of meetings they have. Distinguishing access to policy-makers contemporaneously or before the discussions on a policy, I find that prior access to policy-makers is also associated with higher chances of success. It suggests that reputation and connection-building play a critical role. These results are driven by the business sector, composed of companies and business associations. It indicates that in addition to having more access to policy-makers and being better politically connected, companies and business associations derive greater benefits from these connections. In contrast, NGOs with access to policy-makers do not display an increased probability of success.


CNRS Dauphine INSP Mines Nicod

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