<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Google Trends, despite its controversial nature for some authors, can be considered an illustrative tool in exploring the political inclinations of a given audience. In the current European Union context, understanding the views and opinions of the public is of paramount importance. Through the analysis of search trends, Google Trends can provide valuable insights into the popularity of political parties in the context of the European Union along with other jurisdictions and how these trends change over time. Furthermore, by incorporating fractal dimensions and ARFIMA (Autoregressive Fractionally Integrated Moving Average) analysis into the data obtained, it is possible to reveal previously non-evident relationships, thereby providing a more comprehensive understanding of the audience‘s political leanings and their interest in specific political parties. The aim of this exploratory study is to assess the potential of ARFIMA, applied to Google Trends data, in characterizing political parties. Preliminary results indicate that this apparatus can be useful for that purpose.</p>
</abstract>

Google Trends, despite its controversial nature for some authors, can be considered an illustrative tool in exploring the political inclinations of a given audience. In the current European Union context, understanding the views and opinions of the public is of paramount importance. Through the analysis of search trends, Google Trends can provide valuable insights into the popularity of political parties in the context of the European Union along with other jurisdictions and how these trends change over time. Furthermore, by incorporating fractal dimensions and ARFIMA (Autoregressive Fractionally Integrated Moving Average) analysis into the data obtained, it is possible to reveal previously non-evident relationships, thereby providing a more comprehensive understanding of the audience‘s political leanings and their interest in specific political parties. The aim of this exploratory study is to assess the potential of ARFIMA, applied to Google Trends data, in characterizing political parties. Preliminary results indicate that this apparatus can be useful for that purpose.

Google Trends of political parties in Europe: a fractal exploration

Empresa y Turismo – Universidad de La Laguna

Central European Journal of Public Policy

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"Google Trends of political parties in Europe: a fractal exploration"}

Google Trends, despite its controversial nature for some authors, can be considered an illustrative tool in exploring the political inclinations of a given...

Google Trends of political parties in Europe: a fractal exploration

Online veröffentlicht: 14. Apr. 2024

Seitenbereich: 24 - 36

Eingereicht: 15. Feb. 2023

Akzeptiert: 08. Jan. 2024

DOI: https://doi.org/10.2478/cejpp-2024-0002

Schlüsselwörter
Google Trends, political parties, European Union, fractal dimensions, ARFIMA analysis

© 2024 Josue Gutierrez-Barroso et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Google Trends of political parties in Europe: a fractal exploration

Online veröffentlicht: 14. Apr. 2024

Seitenbereich: 24 - 36

Eingereicht: 15. Feb. 2023

Akzeptiert: 08. Jan. 2024

DOI: https://doi.org/10.2478/cejpp-2024-0002

SchlüsselwörterGoogle Trends, political parties, European Union, fractal dimensions, ARFIMA analysis

© 2024 Josue Gutierrez-Barroso et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Google Trends, political parties, European Union, fractal dimensions, ARFIMA analysis