Abstract
For a long time, the news media has played a crucial role not only as an information provider, but also as an influential source of opinion and commentary. Nowadays, platforms such as Twitter provide an alternative to the traditional one-way interaction, enabling users to voice their opinions. Hence, one can obtain a more comprehensive picture of the range of perspectives on real-world events by considering both news and social media sources. In this paper, we compare mainstream news and Twitter data on 18 well-known real-world events from six different categories. We propose the event-based authoring model (EvA), a novel probabilistic model to capture the content characteristics of an event with respect to aspect, category and background word distributions. These results allow us to analyze the real-world events in different perspectives.
L. Wang and Z. Guo—Contributed equally.
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Acknowledgements
The authors wish to acknowledge the support provided by the National Natural Science Foundation of China (61503217, 91546203), the Key Research and Development Program of Shandong Province of China (2017CXGC0605) and China Scholarship Council (201606220187). Gerard de Melo’s research is funded in part by ARO grant W911NF-17-C-0098 (DARPA SocialSim).
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Wang, L., Guo, Z., Wang, Y., Cui, Z., Liu, S., de Melo, G. (2018). Social Media vs. News Media: Analyzing Real-World Events from Different Perspectives. In: Hartmann, S., Ma, H., Hameurlain, A., Pernul, G., Wagner, R. (eds) Database and Expert Systems Applications. DEXA 2018. Lecture Notes in Computer Science(), vol 11030. Springer, Cham. https://doi.org/10.1007/978-3-319-98812-2_43
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