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BRUSSELS OFFICE : +32 (0)2 895 5909

EIT Digital SenseMaking service to assess web
© Kaboompics / Karolina

EIT Digital SenseMaking service to assess web ‘chatter’

06/09/17Science & Technology

EIT Digital is to launch its SenseMaking Service Innovation Activity to determine the causes and effects of web discussions, such as Twitter, Tumblr, blogs and other networking sites.

The service delivers an analysis by making text data quantitatively and qualitatively understandable by linking its most important topics and concepts to existing knowledge bases like Wikipedia or customer-specific ontologies.

Its prime commercial use areas will include market research, business intelligence, election forecasting, emergency response and management, topic stickiness or popularity prediction, and trend identification.

The innovation activity Leader, Sarunas Girdzijauskas, Associate Professor at KTH Royal Institute of Technology, Sweden, said: “The SenseMaking innovation activity will respond to demand by providing a web service that rapidly answers user requests regarding expected trending scenarios for given topics that are expressed as a set of input keywords.

“Our competitive advantage is the automatic and transparent topic extraction, allowing the linking of unstructured natural text to existing knowledge bases and to the underlying social graphs of web chatter. This allows the detection of causal social network communities and events, the integration of various and different knowledge bases, and comparison of data-driven and knowledge-based analysis in the same interface.”

The SenseMaking service will provide information on the share of data covered by the respective topics, the sentiment towards the topic, as well as accurate predictions on how the topic might spread or stick in the near future.

Dr Magnus Sahlgren, the business champion of the SenseMaking activity, co-founder and Chief Scientist of Gavagai, said: “The SenseMaking service can detect spikes of discussions on certain topics from online chatter and social media. It breaks them down into subtopics and detects sets of similar discussion spikes by using temporal topic similarity graph analysis.

“Further, it will provide an analysis of the underlying social networks which produced the events, such as news websites, politicians, blogs, web-trolls, and so on, depending on the issue. SenseMaking will be the tool to help decision makers make more sense from web chatter data, and predict the effects of social media on their campaigns, products, and so on, before it is too late to take action.”

Pan European Networks Ltd