Mapping the landscape of political advertising research: A comprehensive bibliometric analysis
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2024.15.4.42Keywords:
Bibliometric Analysis, Systematic Literature Review, Data Visualization, Political Advertising, Co-Citation AnalysisDimensions Badge
Issue
Section
License
Copyright (c) 2024 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
This study employs bibliometric analysis to provide a comprehensive overview of the research landscape in political advertising from 1972 to 2022. Drawing on a dataset of 668 papers from the Scopus database, the analysis utilizes the VOSviewer program to examine various facets of political advertising literature. Key findings include the dominance of developed countries, particularly the United States, in terms of research output and citations. Co-authorship patterns reveal extensive collaboration networks, with the United States serving as a central hub. The most productive authors and journals are identified, shedding light on influential contributors and publication outlets in the field. Furthermore, analysis of keyword occurrences highlights prevalent themes and topics, such as political communication, social media, and campaign strategies. Practical implications of the study include informing researchers, policymakers, and practitioners about the current state of political advertising research and identifying avenues for future inquiry. However, the study also acknowledges limitations such as database exclusivity, language bias, and methodological constraints inherent in bibliometric analysis. Overall, this study contributes to a deeper understanding of political advertising scholarship, emphasizing its global significance and potential for shaping political discourse and practice.Abstract
How to Cite
Downloads
Similar Articles
- Nitika, Kuldeep Chaudhary, A critical review of social media advertising literature: Visualization and bibliometric approach , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Raja Selvaraj, Manikandasaran S. Sundari, EAM: Enhanced authentication method to ensure the authenticity and integrity of the data in VM migration to the cloud environment , The Scientific Temper: Vol. 14 No. 01 (2023): The Scientific Temper
- Jayalakshmi K., M. Prabakaran, The role of big data in transforming human resource analytics: A literature review , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Kapil ahuja, Ekta Rani, Soniya Devi, Exploring the dynamic landscape of environmental, social, and governance literature by using bibliometric analysis , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- V. Babydeepa, K. Sindhu, Piecewise adaptive weighted smoothing-based multivariate rosenthal correlative target projection for lung and uterus cancer prediction with big data , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- V. Umadevi, S. Ranganathan, IoT based energy aware local approximated MapReduce fuzzy clustering for smart healthcare data transmission , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Anita M, Shakila S, Stochastic kernelized discriminant extreme learning machine classifier for big data predictive analytics , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Sawitri Devi, Raj Kumar, Unveiling scholarly insights: A bibliometric analysis of literature on gender bias at the workplace , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Shaik Khaleel Ahamed, Neerav Nishant, Ayyakkannu Selvaraj, Nisarg Gandhewar, Srithar A, K.K.Baseer, Investigating privacy-preserving machine learning for healthcare data sharing through federated learning , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- Sabeerath K, Manikandasaran S. Sundaram, BTEDD: Block-level tokens for efficient data deduplication in public cloud infrastructures , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
You may also start an advanced similarity search for this article.
Most read articles by the same author(s)
- Mohit, Rishi Chaudhry, Exploring the landscape of brand extensions: A bibliometric analysis of scholarly trends and insights , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper