Abstract
Nowadays, any person, company or public institution uses and exploits different channels to share private or public information with other people (friends, customers, relatives, etc.) or institutions. This context has changed the journalism, thus, the major newspapers report news not just on its own web site, but also on several social media such as Twitter or YouTube. The use of multiple communication media stimulates the need for integration and analysis of the content published globally and not just at the level of a single medium. An analysis to achieve a comprehensive overview of the information that reaches the end users and how they consume the information is needed. This analysis should identify the main topics in the news flow and reveal the mechanisms of publication of news on different media (e.g. news timeline). Currently, most of the work on this area is still focused on a single medium. So, an analysis across different media (channels) should improve the result of topic detection. This paper shows the application of a graph analytical approach, called Keygraph, to a set of very heterogeneous documents such as the news published on various media. A preliminary evaluation on the news published in a 5 days period was able to identify the main topics within the publications of a single newspaper, and also within the publications of 20 newspapers on several on-line channels.
The research presented in this paper was partially funded by Keystone Action COST IC1302.
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Notes
- 1.
ISTAT http://tinyurl.com/jc5sfc8.
- 2.
The code of the version 2.2 of March 2014 is available on-line at http://keygraph.codeplex.com/.
- 3.
- 4.
- 5.
The average circulations of each newspaper refer to February 2015 as reported by the Italian Federation of Newspaper Publishers (Federazione Italiana Editori Giornali available at http://www.fieg.it).
- 6.
As the content available on web sites and Facebook news is greater than the content on Twitter news, the number of shared keywords is different according to the channel: 5 if news is published on a Website or on Facebook, 3 if news is published on Twitter.
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Po, L., Rollo, F., Trillo Lado, R. (2017). Topic Detection in Multichannel Italian Newspapers. In: Calì, A., Gorgan, D., Ugarte, M. (eds) Semantic Keyword-Based Search on Structured Data Sources. IKC 2016. Lecture Notes in Computer Science(), vol 10151. Springer, Cham. https://doi.org/10.1007/978-3-319-53640-8_6
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