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Big Data Technologies in Research and Analysis of Media Audience: Prospects and Experience of Foreign Projects

Student: Mariia Kozyreva

Supervisor: Alexander Sharikov

Faculty: Faculty of Communications, Media, and Design

Educational Programme: Media Communications (Bachelor)

Final Grade: 10

Year of Graduation: 2020

At the moment there is no single methodology for using the Big Data technologies to analyze the audience of digital media, there are no unified metrics for assessing the interaction of the audience with the content of different formats and no developed practices of creating a holistic audience's portrait. Such methodological uncertainty throttles the development of a digital media content policy and affects advertising revenue. This study was aimed at a comprehensive analysis of Big Data technologies usage in measurements of the foreign media audience. The study has described the expert opinion about the Big Data technologies that are used in digital media audience analysis. We elaborated on the topic of the cost-effectiveness of such technologies for media. We also identified the major reasons why key players on the foreign digital media market support the idea of the single metric system. Hence, the hypothesis of our research was formulated as follows: we suggest that foreign projects may encounter methodological uncertainty in the study of media audiences due to discrepancies in metrics, approaches, and data; therefore, presumably, foreign projects may be interested in the Big Data usage to analyze media audiences, exchange information and create a single meter to overcome such methodological uncertainty. Research led us to the following conclusion: a number of foreign media companies that we studied often collect data using the Big Data technology (for processing audience data, as well as for content creation purposes, e.g. for visualizing and building journalistic narrative). Most experts emphasized that the Big Data as a tool often does not allow to establish a clear causal relationship, and it is not always possible to predict in advance whether it will be possible to get useful knowledge from the available data. However, experts identify several key reasons that hinder the exchange of such audience data: 1) The possible insecurity of such an exchange; in the case of a leak the company's reputation can be destroyed; 2) The absence of the industrial dialogue; 3) The long-term benefits are higher when companies keep their data closed for other market players. The attitude towards the topic of a single measurement system also remained ambiguous. Expert opinions can be divided into three categories: 1) A single measurement system would bring progress and benefit for the advertisers and content creators. Unified metrics are necessary and useful, but it seems impossible to develop one toolkit; 2) Due to the lack of competition, a single measurement system would provide a lower quality of the measurement results; 3) The boundaries between different types of media are blurring in the digital environment, and this is the reason why the phenomenon of the single measurement system soon will lose its relevance - there is no way to create single metrics for convergent media. Media measurements will upgrade to the level of every specific contact with the audience member (measured by the Big Data technologies). A further challenge is to provide a global system of metrics to estimate the media audience. To cope with the absence of a single methodology, there is a need to think about the unified “currencies” for digital projects. Within this research, a lot of effort was aimed at gaining the objective picture on the topic. However, certain limitations were inevitable. These limitations are described as under. The study was concentrated on the representatives of this list of fields: “search engines”, “traditional media”, “providers of the technological solution”, “advertising agencies”, “publishers”, “educational projects”. For further research, other spheres may be analyzed. The data collected via the in-depth interview may not be totally objective because it is connected with the personal experience of an expert. The results cannot be extrapolated on the entire industry because they are case-based on the experience of the specific company.

Full text (added May 12, 2020)

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