Media Cloud

Our Work

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Media Cloud is an open source platform for studying media ecosystems.

By tracking hundreds of millions of stories published online or broadcast via television, our suite of tools allows researchers to track how stories and ideas spread through media, and how different corners of the media ecosystem report on stories.

Our platform is designed to aggregate, analyze, deliver and visualize information, answering complex quantitative and qualitative questions about the content of online media.

Aggregate |  We have aggregated billions of online stories from an ever-growing set of 25,000 digital media sources. We ingest data via RSS feeds and a set of robots that spider the web to fetch information from a variety of sources in near real-time. We currently provide specific language support for 16 different languages: Danish, German, English, Spanish, Finnish, French, Hungarian, Italian, Lithuanian, Dutch, Norwegian, Portuguese, Romanian, Russian, Swedish, and Turkish, and are continuously adding additional language capabilities to our tools. If there are novel data sources that you are interested in researching, we can help develop a customized solution.

Analyze |  To query our extensive library of data, we have developed a suite of analytical tools that allow you to explore relationships between professional and citizen media, between online and offline sources. Our researchers can help you pursue a mixed-methods approach by combining text and link analysis with qualitative methods to map the evolution of an existing media frame or issue over time and to analyze the mobilization, roles, and interactions of various actors.

Deliver and Visualize | Our suite of tools provide opportunities to present data in formats that you can visualize in your own interfaces. These include the use of graphs, geographic maps, word clouds, network visualizations. For a deeper dive into the content of our large datasets, we can output and deliver our sources in formats that can suit additional research needs, from CSV files to rich visualizations.