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Europe On Edge: Mapping Right-Wing Influence And Public Sentiment Across The Eu

Author

Listed:
  • Milena TRENTA

    (Facultad de Ciencias Sociales y de la Comunicación; Camino La Hornera, 37, 38200, San Cristóbal de La Laguna, Spain)

  • Josué GUTIÉRREZ BARROSO

    (Universidad de La Laguna, Facultad de Ciencias Sociales y de la Comunicación; Camino La Hornera, 37, 38200, San Cristóbal de La Laguna, Spain)

  • Lenin RODRÍGUEZ PEÑATE

    (Universidad de La Laguna; Camino La Hornera, 37, 38200, San Cristóbal de La Laguna, Spain)

  • Elena CRESPO GARCÍA

    (UNED/Universidad de La Laguna; Camino La Hornera, 37, 38200, San Cristóbal de La Laguna, Spain)

Abstract

The concatenation of several crises and challenges in Europe (financial crisis, pandemic, war, housing and higher prices, digital challenges like artificial intelligence, ageing population and migrations) is reshaping the European political landscape and discourse. The entire morphology of party systems in each country radically changed with respect to the last days of the past century. New political forces appear at both sides of the political spectrum. On the other hand, digital technologies provide the most prominent political scenarios for interaction and opinion where public concerns meet new political proposals. This article explores the intersection between public concerns, the political messaging of new leaders and parties, and political polarization within the EU. The main goal of the research is to conduct an exploratory analysis of online search trends across the 27 European countries, many of which have experienced increasing political polarization in recent years. In this first attempt, the focus is on the growing influence of right-wing parties that are gaining political momentum across Europe. Regarding public concerns, several key topics are explored, driven by factors such as economic uncertainty, immigration concerns, and dissatisfaction with traditional political elites. In order to deeply analyse these trends, the work goes beyond traditional time series techniques. Using ARFIMA (Autoregressive Fractionally Integrated Moving Average) models, this research captures long-memory patterns in online search trends, providing a perspective on the temporal persistence and predictability of political topics on the Internet.

Suggested Citation

  • Milena TRENTA & Josué GUTIÉRREZ BARROSO & Lenin RODRÍGUEZ PEÑATE & Elena CRESPO GARCÍA, 2025. "Europe On Edge: Mapping Right-Wing Influence And Public Sentiment Across The Eu," REVISTA ADMINISTRATIE SI MANAGEMENT PUBLIC, Faculty of Administration and Public Management, Academy of Economic Studies, Bucharest, Romania, vol. 2025(45), pages 6-26.
  • Handle: RePEc:rom:rampas:v:2025:y:2025:i:45:p:6-26
    DOI: https://doi.org/10.24818/amp/2025.45-01
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    References listed on IDEAS

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    1. Sowell, Fallaw, 1992. "Maximum likelihood estimation of stationary univariate fractionally integrated time series models," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 165-188.
    2. John Geweke & Susan Porter‐Hudak, 1983. "The Estimation And Application Of Long Memory Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 4(4), pages 221-238, July.
    3. Doornik, Jurgen A. & Ooms, Marius, 2003. "Computational aspects of maximum likelihood estimation of autoregressive fractionally integrated moving average models," Computational Statistics & Data Analysis, Elsevier, vol. 42(3), pages 333-348, March.
    4. C. W. J. Granger & Roselyne Joyeux, 1980. "An Introduction To Long‐Memory Time Series Models And Fractional Differencing," Journal of Time Series Analysis, Wiley Blackwell, vol. 1(1), pages 15-29, January.
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    Keywords

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    JEL classification:

    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • Z18 - Other Special Topics - - Cultural Economics - - - Public Policy

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