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Detecting Emerging Stories & Emotions in the Public Debate

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.

webLyzard technology

November 26, 2020
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  1. Detecting Emerging Stories & Emotions in the Public Debate Web

    Intelligence Applications in Health, Sustainability and Politics Arno Scharl, [email protected] www.modul.ac.at/nmt
  2. Sentiment Share of Voice Brand Reputation Measuring Impact and Social

    Perceptions Success Metrics WYSDOM Success Metric Wheel of Emotions
  3. 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
  4. Sentiment Share of Voice Brand Reputation Measuring Impact and Social

    Perceptions Success Metrics WYSDOM Success Metric Wheel of Emotions
  5. 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
  6. 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
  7. 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 [email protected]
  8. Detecting Emerging Stories & Emotions in the Public Debate Web

    Intelligence Applications in Health, Sustainability and Politics Arno Scharl, [email protected] www.modul.ac.at/nmt