"This research is proposing a new approach for the faith-based media institutions in the creation and production of content. The solution proposed by this research is a text mining content analysis tool that uses data mining techniques including Association, Clustering and Classification in the disc
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overy of new content that is lying within the already existing text. These three combined with term frequency and inverse document frequency (TF-IDF) plus other machine learning techniques will be able to reveal different connections between different sets of data hence aiding the creation of new content for the media institution." (Abstract)
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"Democratic nations around the globe are facing increasing levels of false and misleading information circulating on social media and news websites, propagating alternative sociopolitical realities. One of the most innovative actors in this process has been the Russian state, whose disinformation ca
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mpaigns have influenced elections and shaped political discourse globally. A key element of these campaigns is the content produced by state-funded outlets like RT and Sputnik, whose articles are republished by underfunded or sympathetic local media, as well as coordinated groups that attempt to shape mainstream political narratives. Using a tailored text-as-data approach, we examine the thematic and linguistic differences in articles produced by U.S. and Russian state-funded and mainstream outlets in Serbia. We use 11 features (frames and in-text characteristics) to construct an article country-source classifier with a high degree of accuracy. The article contributes toward an understanding of the structural characteristics of Russian statefunded news in the Western Balkans, enhances the application of computational text analysis in Serbian, and provides suggestions for the application of text-as-data methods to the study of online disinformation." (Abstract)
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"This report outlines the methodology and processes of the Radio Content Analysis Tool, a prototype developed by Pulse Lab Kampala to analyse public radio content in Uganda and explore its value for informing development of UN projects and programmes on the ground. It distills the technology behind
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the creation of the Radio Content Analysis Tool and presents the lessons learned along the way. The report also details the results of several pilot studies that were conducted together with partners from the Government, UN agencies and academia to understand the validity and value of unfiltered public radio discussions for development [...] By sampling different indigenous languages, types of broadcasters, and locations within Uganda, the pilot studies assess the potential uses of radio talk across five topics: perceptions towards refugees in Uganda, the impact of small-scale disasters on livelihoods, perceptions around the delivery of healthcare services, understanding the spread of infectious diseases, and monitoring the effectiveness of awareness raising radio campaigns." (Executive summary)
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"Mecodify is an open-source tool created as part of the Media Conflict and Democratization Project (http://mecodem.eu) to help gather, analyse and visualise Twitter data for use by social science scholars. The name describes what it does, i.e., Message Codification by converting messages to systemat
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ic structures, tables, graphs and quantifiable content. The platform remains in constant development and the first version (1.0) is currently being used for the research purposes indicated in the website above. The software mainly uses PHP and Javascript and has used several open-source libraries including but not limited to HighCharts, TwitterAPIExchange, D3Js for various components of the platform." (https://github.com/wsaqaf/mecodify)
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