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RETRACTED ARTICLE: Data mining and visualization of data-driven news in the era of big data

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This article was retracted on 05 December 2022

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Abstract

With the continuous deepening of study of data mining, the application area of data mining gradually expanded, its influence also spread to the media industry. Data visualization technology has changed the traditional narrative mode, make the news becomes a product that be produced. This paper analyzes the history of computer aided reporting to data news, the main models of data news visualization, and the process of data news production through data mining. The study found that data news focuses on the way of data processing in the entire news workflow, it involves not only classical computer graphics technology, image-processing technology and computer audio technology, but also more data analysis and visual processing technologies based on new media and cloud computing involved in. Research data mining and visualization of data-driven journalism can help journalists use big data to do news work better, deepen people’s cognition of news events, find the logic which cannot be reflected in traditional news, and maximize the connotation of news report.

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References

  1. Wen, W., Li, B.: Data news reports in the big data era: taking the Guardian newspaper as an example. Mod. Commun. 35(5), 139–142 (2013)

    Google Scholar 

  2. Steve, Lohr.: The age of big data. New York Times, New York (11 Feb 2012)

  3. Li, D., Wang, S.: On spatial data mining and knowledge discovery (SDMKD). Geomat. Inf. Sci. Wuhan Univ. 26(6), 491–499 (2001)

    Google Scholar 

  4. Li, D.R., Cheng, T.K.D.G.: Knowledge Discovery from Gishie Canadian Conference on GIS, Ottawa, pp. 1001–1012 (1994)

  5. Zhao, D.: Data mining: principles, methods and application. Mod. Libr. Inf. Technol. 16(6), 41–44 (2000)

    Google Scholar 

  6. Fayyad, U.M., Piatetsky-Shapiro, G., Smyth, P., et al.: Advances in Knowledge Discovery and Data Mining, p. 18. AAAI Press, Cambridge (1996)

    Google Scholar 

  7. Witten, I.H.: Data Mining—Practical Machine Learning Tools and Techniques, 2nd edn. Machinery Industry Press, South Norwalk (2005)

    MATH  Google Scholar 

  8. Chen, M.S., Han, J., Yu, P.S.: Data mining: an overview from database perspective. IEEE Trans. Knowl. Data Eng. 8, 866–883 (1996)

    Article  Google Scholar 

  9. Han, J., Kamber, M.: Data Mining: Concepts and Techniques. Academic Press, San Francisco (2001)

    MATH  Google Scholar 

  10. Graham Rowe, D.: Big Data: The Next Google. Nature, UK. http://www.Nature.com/news/2008/080903/full/455008a.html (2008)

  11. Jiang, X., Zhou, D.: A new data mining processing model. Comput. Mod. 2, 18–20 (2003)

    Google Scholar 

  12. Wang, L.: The summarization of present situation of data mining research. Books Inf. 5, 41–46 (2008)

    Google Scholar 

  13. Lewis, S.C.: Journalism in an era of big data. Digit. J. 3, 321–330 (2015)

    Google Scholar 

  14. Parasie, S., Dagiral, E.: Data-driven journalism and the public good: “computer-assisted-reporters” and “programmer-journalists” in Chicago. New Media Soc. 15(6), 853–871 (2013)

    Article  Google Scholar 

  15. Wang, K.: Visualization of sports journalism in the era of big data: advantages and challenges. Sports Res. Educ. 31(1), 13–17 (2016)

    Google Scholar 

  16. Anderson, C.W.: Between the unique and the pattern: historical tensions in our understanding of quantitative journalism. Digit. J. 3, 349–363 (2014)

    Google Scholar 

  17. Lang, J., Yang, H.: Data news: the innovation path of news visualization communication in the big data era. Mod. Commun. 3, 32–36 (2014)

    Google Scholar 

  18. Gray, J., Chambers, L., Bounegru, L.: The Data Journalism Handbook. O’Reilly Media, Sebastopol (2012)

    Google Scholar 

  19. Fang, J., Yan, W.: Data news from a global perspective: philosophy and practice. Int. Press 35(6), 73–83 (2013)

    Google Scholar 

  20. Rodgers, Y.: Data News Trend: Releasing the Power of Visual Report: Facts are Sacred: The Power of Data. Renmin University of China press, Beijing (2015)

    Google Scholar 

  21. Dove, G., Jones, S.: Narrative visualization: sharing insights into complex data. Interf. Hum. Comput. Interact. 1, 21–23 (2012)

    Google Scholar 

  22. Rodríguez, M.T., Devezas T.: Telling Stories with Data Visualization. Workshop, pp. 7–11 (2015)

  23. Erdmann, E., Boczek, K., Koppers, L., et al.: Machine learning meets data-driven journalism: boosting international understanding and transparency in news coverage. (2016)

  24. Lei, Y.: Cross Media Journalism Theory and Practice, vol. 134. Renmin University of China press, Beijing (2006)

    Google Scholar 

  25. http://www.NYtimes.com/interactive/2012/05/17/business/dealbook/howtheFacebookofferingcompares

  26. Baiquan, D.: Data news: value and limitation. 7, 6–10 (2014)

  27. Chen, S.: Visualization model and path optimization of data news visualization in big data background. Publishing Wide-Angle, 10, 62–64 (2017)

  28. Tabary, C., Provost, A.M., Trottier, A.: Data journalism’s actors, practices and skills: a case study from Quebec. J. Theory Pract. Crit. 17(1), 41–47 (2016)

    Google Scholar 

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Correspondence to Zongjun Wang.

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Qi, E., Yang, X. & Wang, Z. RETRACTED ARTICLE: Data mining and visualization of data-driven news in the era of big data. Cluster Comput 22 (Suppl 4), 10333–10346 (2019). https://doi.org/10.1007/s10586-017-1348-8

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  • DOI: https://doi.org/10.1007/s10586-017-1348-8

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