Future digital perspectives: MU faculty develops pioneering analytics platform for TV content

Leading media technology experts from MODUL University Vienna and across Europe have joined forces to enable TV providers to be more agile and responsive to increasing competition from new digital media. Their declared goal is to develop a “trans-vector platform” that provides TV providers with fast, reliable information on who consumes their content as well as when, where and how they do so. It will provide decision support regarding future publication of content on social networks and digital distribution channels, and where content adaptation is likely to pay off.

Targeted Adaptation

Dr. Lyndon Nixon, CTO of MODUL Technology and Assistant Professor at the Department of New Media Technology comments: “TV providers have to distribute their content through multiple channels such as social media, mobile apps, hybrid TV and digital archives. But compared to print media – which face similar pressures – their content is technically much more complex. Deciding which content should be adapted and in what way is therefore essential for meeting the demands of consumers in a cost-effective manner.”

This is where the ReTV project comes in. The project is coordinated by Vrije Universiteit Amsterdam, with MODUL Technology and webLyzard leading the R&D efforts and technical development, in collaboration with project partners from Germany, Switzerland, Greece and the Netherlands. The cooperative project is divided into three clearly defined sections, the results of which will be of significant value to TV providers. In addition to the “aggregation”, i.e. the creation of a steadily growing respository of TV-related online content, the “analysis” and “adaptation” of such content are key elements of the project.

Aggregation & Annotation

More than 10,000 hours of video content and over 50 million documents will be collected and processed from news sources, social media and TV station websites every month. This huge volume of data will then be automatically analysed, and relevant metadata will be annotated to every document. Besides “hard” facts, such as links, names and salient visual features, the metadata will contain an automatic evaluation of online mood regarding the topics, persons or organisations mentioned in the content.

Analysis & Adaptation

Professor Arno Scharl, Managing Director of webLyzard, describes how ReTV works: “In the analysis stage, the webLyzard platform is used to capture content trends across news and social media channels. This allows recommendations regarding both the adaptation of existing content and the focus for new productions. Thereby ReTV will help optimise advertising strategies, for example by referencing relevant topics that are currently being actively discussed by consumers.”

ReTV will also provide predictions and suggestions regarding the optimal distribution schedule and the expected success of original and adapted content. The ongoing collection and processing of relevant data from a wide range of sources will enable the system to learn. Deviations between predicted and actual success will trigger automated optimisations. Upon successful completion of the project, ReTV will strengthen the competitive situation of European media companies in today’s networked, global market for video content.