Understanding Web Publications in the Digital Age by Applying Media Intelligence
DOI:
https://doi.org/https://doi.org/10.37075/RP.2025.4.02Keywords:
Data analysis, Online publications, Media intelligence, Big data, Digital media ecosystemAbstract
The article explores approaches for analyzing online publications from leading television media in Bulgaria, utilizing modern big data processing methods. By combining quantitative and qualitative analytical techniques, it demonstrates the potential for extracting meaning and identifying trends in the digital media landscape. The study highlights the importance of the concept of media intelligence in analyzing online content and contributes to a better understanding of transformations within the media ecosystem. These approaches also offer practical guidelines for improving the analysis and management of media content.References
Albanese, F. and Pinto, S. and Semeshenko, V. and Balenzuela, P. (2020). Analyzing mass media influence using natural language processing and time series analysis. Journal of Physics: Complexity, 1(2), 025005. DOI: https://doi.org/10.1088/2632-072X/ab8784
Angova, S. and Valchanov, I. (2018). New online media business models. Yearbook of UNWE, 287--306.
Boyanov, L. (2021). A Conceptual Approach for Industrial Internet of Things Assessment. Yearbook of UNWE, 97--107.
Bock, A. and Palladino, A. and Smith-Heisters, S. and Boardman, I. and Pellegrini, E. and Bienenstock, E. J. and Valenti, A. (2021). An NLP approach to quantify dynamic salience of predefined topics in a text corpus. arXiv. DOI: https://doi.org/10.48550/arXiv.2108.07345
Hedley, J. and jsoup contributors (2023). jsoup: Java HTML Parser (Version 1.17.2).
Shu, K. and Mahudeswaran, D. and Wang, S. and Lee, D. and Liu, H. (2019). FakeNewsNet: A Data Repository with News Content, Social Context and Spatialtemporal Information for Studying Fake News on Social Media. Big Data, 8(3), 171--188. DOI: https://doi.org/10.48550/arXiv.1809.01286
Spinde, T. (2021). An Interdisciplinary Approach for the Automated Detection and Visualization of Media Bias in News Articles. 2021 International Conference on Data Mining Workshops (ICDMW) (Ed. NA), pp. 1096--1103. DOI: https://doi.org/10.48550/arXiv.2112.13352
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Copyright (c) 2025 Plamen Milev (Author)
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