Trends in examining data journalism research: A systematic literature review in 2010-2023
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Current studies of data journalism ideally produce knowledge about the use of data as news sources. The problem is that studies in data journalism are still partial; therefore, state of the art of data journalism is not well-known. This study aims to identify and analyze research topics, research methods, and frameworks in data journalism research in 2010-2023. Based on specific criteria, 76 primary studies were selected. This study uses a systematic literature review to analyze and answer the research questions that have been formulated. The results show that data journalism research focuses on topics: practical studies, theoretical studies, politics, education, visualization, storytelling, data journalism and new media, objectivity, sports, innovation, and crime reporting. The research methods are interviews, content analysis, case studies, mixed methods, surveys, ethnography, action research, thematic analysis, discourse analysis, grounded, and experiments. The frameworks identified are the Veglis and Maniou framework, Borges-Rey framework, and Lewis framework. This study concludes the topic of practical studies appears dominant because data journalism is a new phenomenon so its practices are important to research. The interview method is mostly used because it is familiar to researchers from various disciplines. The identification of these three frameworks shows the limited systematic study of data journalism.
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