Detecting Emerging Stories & Emotions in the Public Debate

Research Seminar - Prof. Arno Scharl of MODUL University Vienna's Department of New Media Technology presents emotion detection algorithms developed in the ReTV Project as well as visual analytics features of the Evolve H2020 Big Data Innovation Action - including Web Intelligence applications in health, sustainability and politics.

Transcript

1. Detecting Emerging Stories & Emotions in the Public Debate Web Intelligence Applications in Health, Sustainability and Politics Arno Scharl, scharl@modul.ac.at www.modul.ac.at/nmt
3. Sentiment Share of Voice Brand Reputation Measuring Impact and Social Perceptions Success Metrics WYSDOM Success Metric Wheel of Emotions
4. US Election 2020 Web Monitor us2020.weblyzard.com Developed at the Department of New Media Technology of MODUL University Vienna; powered by webLyzard technology www.weblyzard.com/us-election-2020-web-monitor
9. Sentiment Share of Voice Brand Reputation Measuring Impact and Social Perceptions Success Metrics WYSDOM Success Metric Wheel of Emotions
10. Wheel of Emotion Robert Plutchik
14. ReTV | www.weblyzard.com/retv Enhancing and Repurposing TV Content Media Partners: rbb|24, Zattoo, Sound & Vision EU Horizon 2020, 3.5 Mio EUR SONAR | www.weblyzard.com/sonar Semantic Repository for News Analytics Media Partner: ProSiebenSat.1 PULS 4 Google News Initiative, 225,000 EUR EVOLVE | www.weblyzard.com/evolve Leading the Big Data Revolution 19 European Technology & Use Case Partners EU Horizon 2020, 11.0 Mio EUR
15. UNEP Live Web Intelligence unep.ecoresearch.net Developed by the Department of New Media Technology of MODUL University Vienna; powered by webLyzard technology www.weblyzard.com/unep-live ▪ unep.ecoresearch.net
18. EcoMove | www.weblyzard.com/ecomove Predicting Mobility Bottlenecks Partners: webLyzard technology, MODUL University Vienna, Unwired Networks, NAST Consulting FFG Mobility of the Future EcoMove will develop knowledge-based solutions for efficient and environmentally sustainable movement in cities, providing customized information about available mobility options. Real- time recommendations for delaying, avoiding or taking alternative options will be presented visually to the users – city residents, visitors, and professional stakeholders – in order to prioritize “necessary” mobility. The City of Vienna will serve as the use case, but the developed methods will be generic and applicable to other cities and regions in follow-up projects. @weblyzard @moduluniversity scharl@modul.ac.at
20. Detecting Emerging Stories & Emotions in the Public Debate Web Intelligence Applications in Health, Sustainability and Politics Arno Scharl, scharl@modul.ac.at www.modul.ac.at/nmt