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

Author

Listed:
  • Kai Gehring
  • Matteo Grigoletto
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.

Suggested Citation

  • Kai Gehring & Matteo Grigoletto, 2023. "Analyzing Climate Change Policy Narratives with the Character-Role Narrative Framework," CESifo Working Paper Series 10429, CESifo.
    • Handle: RePEc:ces:ceswps:_10429
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    File URL: https://www.cesifo.org/DocDL/cesifo1_wp10429.pdf
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    References listed on IDEAS

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    Cited by:

    1. Francesco Capozza, 2024. "Beliefs about the Gender Gap in Salary Negotiations," CESifo Working Paper Series 11228, CESifo.
    2. Marcel Caesmann & Janis Goldzycher & Matteo Grigoletto & Lorenz Gschwent, 2024. "Censorship in democracy," ECON - Working Papers 446, Department of Economics - University of Zurich.
    3. Lorenz Gschwent & Bjorn Hammarfelt & Martin Karlsson & Mathias Kifmann, 2024. "The Rise of Health Economics: Transforming the Landscape of Economic Research," Papers 2410.06313, arXiv.org.

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    More about this item

    Keywords

    narrative economics; text-as-data; machine learning; large language models; climate change; virality; populism;
    All these keywords.

    JEL classification:

    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • H10 - Public Economics - - Structure and Scope of Government - - - General
    • P16 - Political Economy and Comparative Economic Systems - - Capitalist Economies - - - Capitalist Institutions; Welfare State
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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