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
- Sujay Bhalchandra, Nilesh D. Shinde, An exploratory study of factors influencing manufacturer-dealer relationship in Indian automobile industry , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- Suresh L. Chitragar, Occupational Structure of Population in the Malaprabha River Basin, Karnataka State, India; A Geographical Approach , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- Deneshkumar V, Jebitha R, Jithu G, Multistate modeling for estimating clinical outcomes of COVID-19 patients , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- Appu A, Does shopping values influence users behavioral intentions? Empirical evidence from Chennai malls , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- Saumya Trivedi, Amit Sinha, Satyendra P. Singh, Ramya Singh, A study on factors influencing lending decisions for MSMEs by scheduled commercial banks in the CGTSME scheme , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- Sanskriti Gandhi, Usha Asnani, Srivalli Natarajan, Chinmay Rao, Richa Agrawal, Evaluation of stability of fixation using conventional miniplate osteosynthesis in comminuted and non-comminuted Le Fort I, II, III fractures – A dynamic finite element analysis , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- Samara Ahmed, Adil E. Rajput, Denial, acceptance and intervention in society regarding female workplace bullying - A mental health study on social media , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- Tewoderos Legesse, Bekelech Sharew, Evaluation of white seeded sesame (Sesamum indicium L.) genotypes on growth and yield performance in Menit Goldya Woreda of West Omo Zone, SWE , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- B Supraja, B Ramachandra, N Venkatasubba Naidu, Analytical Method Development and Validation Analysis for Quantitative Assessment of Thifluzamide by HPLC Procedure , The Scientific Temper: Vol. 13 No. 01 (2022): The Scientific Temper
- Pravin P. Adivarekar1, Amarnath Prabhakaran A, Sukhwinder Sharma, Divya P, Muniyandy Elangovan, Ravi Rastogi, Automated machine learning and neural architecture optimization , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
<< < 14 15 16 17 18 19 20 21 22 23 > >>
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