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The political economy of coal across 12 countries: Analysing qualitative interviews with topic models

Energy Research & Social Science, ISSN: 2214-6296, Vol: 101, Page: 103137
2023
  • 4
    Citations
  • 0
    Usage
  • 38
    Captures
  • 1
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    4
    • Citation Indexes
      3
    • Policy Citations
      1
      • Policy Citation
        1
  • Captures
    38
  • Mentions
    1
    • News Mentions
      1
      • News
        1

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Reports Summarize Energy Research Study Results from Mercator Research Institute of Global Commons & Climate Change (The Political Economy of Coal Across 12 Countries: Analysing Qualitative Interviews With Topic Models)

2023 AUG 02 (NewsRx) -- By a News Reporter-Staff News Editor at Politics, Law & Government Daily -- Data detailed on Energy Research have been

Article Description

Understanding the ongoing investments in coal-fired power plants requires an analysis of the political economy. Here, we conduct a computational analysis of 212 interviews from 12 countries on the political economy of coal using topic modelling (TM). Our study highlights relevant topics by actor group and country. While most topics are similarly distributed across all actor groups, we find distinct clusters of countries in which similar topics play important roles. For example, in Indonesia and India, sustaining low electricity tariffs is brought forward as a reason to invest in coal, whereas in South Africa and Kenya the civil society is considered instrumental in the choice of coal or alternatives. To validate our findings, we compare them to outcomes of qualitative case studies and to papers grouping countries based on quantifiable factors. As this study is among the first to apply TM to interview data, we thereby highlight strengths and challenges for such application and the interpretability of results. We argue that topic models are effective supplements to qualitative case studies, particularly when analysing large amounts of text.

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