Big Data and the Online Media: Basic Approach and Strategies of Use

For citation: Vartanov S.A. (2017) Bol'shie dannye v onlayn-SMI: podkhody i strategii ispol'zovaniya [Big Data and the Online Media: Basic Approach and Strategies of Use]. Mediaskop4. (in Russian). Available at: http://www.mediascope.ru/2375

© Sergey A. Vartanov

PhD (Physics and Mathematics), Associate Professor at the Chair of Econometrics and Mathematical Methods of Economics, Moscow School of Economics of Lomonosov Moscow State University (Moscow, Russia), sergvart@gmail.com

Abstract

The growing penetration of various gadgets into our everyday life and its increasing digitalization have resulted in the fact that everything we do can be, in this way or another, registered and saved as logs of the devices we interact with. This is not only the case of traditional web visit logs, used by any browser, or cookies, which help to restore almost all the information about the internet user's activity. We are also speaking about other media consumption which also is now performed via digital devices – for example, digital television set-top boxes or Smart TV sets.

Processing of digital receivers return path data is not the only example of big data analysis in the media industry. Another type of big data, which is as important for the industry as return path data and surpasses it in terms of amount and complexity of analysis, is the data gathered from the online media audience. In this area, there are many more methods of data analysis and many more ways to use the obtained results than in the case of RPD. Furthermore, online media widely use Big Data not only in audience research, but also in data journalism. The main goal of this article is to identify the most important types of Big Data that may be used by online media and to understand the main ways they manipulate these data.

The structure of the article is as follows. At first we describe two primary branches of Big Data usage strategies which are developed by some remarkable online media (like the Financial Times, Sacramento Bee, Huffington Post etc.). These are the audience-oriented and content-oriented types of Big Data usage strategies. The audience-oriented strategies are based mainly on involving the data generated by the audience online media consumption and their online behavior in the marketing action of these media. The content-oriented strategies assume that these data are handled to improve the content of the media. This type of Big Data usage is closely related to the data journalism. In the conclusion of the article we are discussing emergent technologies of Big Data analysis which may be used to create new content for online media.

Keywords: Internet, Big Data, media research, data journalism.

Notes

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