DIGITAL DARBARS: SPECTACLE, STAGECRAFT, AND VIRAL FALSEHOODS IN RAJASTHAN’S ELECTORAL CAMPAIGNS
DOI:
https://doi.org/10.29121/shodhkosh.v7.i2s.2026.7256Keywords:
Digital Political Communication, Electoral Campaigns, Social Media Engagement, Digital Darbars, Political Spectacle, Viral Misinformation, Algorithmic Amplification, Audience Polarization, Online Political Narratives, Election Communication AnalyticsAbstract [English]
The electronic media has revolutionized electoral campaigning because the campaigning process can propagate the political narratives at the same speed by using highly interactive and visual communication methods. Modern-day campaigns are utilizing more and more of digital stagecraft, multimedia narratives, and algorithm facilitated amplification to influence voter perception and mobilize political action. An electoral campaign in the state of Rajasthan serves as a good example of this change study since the traditional forms of political performances are being dragged round in the virtual world. In this paper, the Digital Darbars framework is a model that explains how a political spectacle, the production of the media and amplification of social media inter-relate to create viral political narratives in modern political campaigns. The analysis that examined the content of the campaign pages of the social media on the most popular platforms like Facebook, X (Twitter), Instagram, and YouTube. The trends of digital political communication were analyzed in the measures of quantitative engagement, content classification and sentiment analysis. Results also indicate that content associated with spectacle (rally videos and symbolic imagery and meme-centric narratives) will have a far more significant engagement than policy-focused messages do. The interaction dynamic with a growing importance of multimedia narrative is observed in visual medium to date in the political campaign. The misinformation is also demonstrated in the analysis to contribute to digital campaign ecosystems. It is easier to convert the media information and viral political memes and reach more people as opposed to the verified campaign messages, which will create more polarization of the audience. As the campaign events go through the Digital Darbar Ecosystem Model suggested, they are converted into viral narratives as they go through the media capture, platform amplification and audience interpretation stages. These findings imply that effective mitigation techniques of misinformation, effective platform regulation, and effective digital literacy ought to be adopted to secure democratic communication.
References
Campos-Valdés, C., Álvarez-Miranda, E., Morales Quiroga, M., Pereira, J., and Liberona Durán, F. (2021). The Impact of Candidates’ Profile and Campaign Decisions in Electoral Results: A Data Analytics Approach. Mathematics, 9(8), 902. https://doi.org/10.3390/math9080902 DOI: https://doi.org/10.3390/math9080902
Fiaz, F., Sajjad, S. M., Iqbal, Z., Yousaf, M., and Muhammad, Z. (2024). MetaSSI: A Framework for Personal Data Protection, Enhanced Cybersecurity and Privacy in Metaverse Virtual Reality Platforms. Future Internet, 16, 176. DOI: https://doi.org/10.3390/fi16050176
Finn, P., Bell, L. C., Tatum, A., and Leicht, C. V. (2024). Assessing ChatGPT as a Tool for Research on US State and Territory Politics. Political Studies Review. Advance online publication. https://doi.org/10.1177/14789299241268652 DOI: https://doi.org/10.1177/14789299241268652
Gholap, S., Shinde, H., Nigude, N., and Mali, A. (2025). Ai-Assisted Creativity: Balancing Innovation and Authenticity in the Digital Era. International Journal of Advances in Computer Engineering and Communication Technology, 14(1), 529–533. DOI: https://doi.org/10.65521/ijacect.v14i1.584
Grover, P., Kar, A., Dwivedi, Y. K., and Janssen, M. (2019). Polarization and Acculturation in US Election 2016 Outcomes—Can Twitter Analytics Predict Changes in Voting Preferences? Technological Forecasting and Social Change, 145, 438–460. DOI: https://doi.org/10.1016/j.techfore.2018.09.009
Irfan, M., Ali, S. T., Ijlal, H. S., Muhammad, Z., and Raza, S. (2024). Exploring the Synergistic Effects of Blockchain Integration with IoT and AI for Enhanced Transparency and security in Global Supply Chains. International Journal of Contemporary Issues in Social Sciences, 3, 1326–1338.
Islam, M. B. E., Haseeb, M., Batool, H., Ahtasham, N., and Muhammad, Z. (2024). AI Threats to Politics, Elections, and Democracy: A Blockchain-Based Deepfake Authenticity Verification Framework. Blockchains, 2(4), 458–481. https://doi.org/10.3390/blockchains2040020 DOI: https://doi.org/10.3390/blockchains2040020
König, P. (2020). Why Digital-Era Political Marketing is not the Death Knell for Democracy: On the Importance of Placing Political Microtargeting in the Context of Party Competition. Statistics, Politics and Policy, 11(1), 87–110. DOI: https://doi.org/10.1515/spp-2019-0006
Micha, E., and Shah, N. (2020). Can we Predict the Election Outcome from Sampled Votes? In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 34, 2176–2183). DOI: https://doi.org/10.1609/aaai.v34i02.5593
Puggioni, R. (2024). Coming out as Undocumented: Identity Celebrations and Political Change. Societies, 14, 130. DOI: https://doi.org/10.3390/soc14070130
Sernani, P., Cossiri, A., Di Cosimo, G., and Frontoni, E. (2025). Analyzing Digital Political Campaigning Through Machine Learning: An Exploratory Study for the Italian Campaign for European Union Parliament Election in 2024. Computers, 14(4), 126. https://doi.org/10.3390/computers14040126 DOI: https://doi.org/10.3390/computers14040126
Vlados, C. M. (2024). The Current Evolution of International Political Economy: Exploring the New Theoretical Divide Between New Globalization and Anti-Globalization. Societies, 14, 135. DOI: https://doi.org/10.3390/soc14080135
Wu, T., He, S., Liu, J., Sun, S., Liu, K., Han, Q. L., and Tang, Y. (2023). A Brief Overview of ChatGPT: The History, Status Quo and Potential Future Development. IEEE/CAA Journal of Automatica Sinica, 10(5), 1122–1136. DOI: https://doi.org/10.1109/JAS.2023.123618
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Copyright (c) 2026 Priyanka Maheshwari, Dr. Amit Verma, Dr. Sana Absar, Dr. Preeti Singh, Dr. Rajiv Pratap Singh, Dr. Shriprakash Pal, Dr. Chanchal Sachdeva Suri

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