Abstract
The InVID Multimodal Analytics Dashboard is a visual content exploration and retrieval system to analyze user-generated video content from social media platforms including YouTube, Twitter, Facebook, Reddit, Vimeo, and Dailymotion. It uses automated knowledge extraction methods to analyze each of the collected postings and stores the extracted metadata for later analyses. The real-time synchronization mechanisms of the dashboard help to track information flows within the resulting information space. Cluster analysis is used to group related postings and detect evolving stories, to be analyzed along multiple semantic dimensions such as sentiment and geographic location. Data journalists can not only visualize the latest trends across communication channels, but also identify opinion leaders (persons or organizations) as well as the relations among these opinion leaders.
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Acknowledgements
The multimodal analytics dashboard presented in this chapter has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No 687786. The authors would like to thank the researchers and software engineers of webLyzard technology gmbh, MODUL Technology GmbH, the Department of New Media Technology at MODUL University Vienna, and the Swiss Institute for Information Science at HTW Chur for their continued efforts to improve and extend the platform, as well as for their feedback on earlier versions of this article.
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Scharl, A., Hubmann-Haidvogel, A., Göbel, M., Schäfer, T., Fischl, D., Nixon, L. (2019). Multimodal Analytics Dashboard for Story Detection and Visualization. In: Mezaris, V., Nixon, L., Papadopoulos, S., Teyssou, D. (eds) Video Verification in the Fake News Era. Springer, Cham. https://doi.org/10.1007/978-3-030-26752-0_10
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DOI: https://doi.org/10.1007/978-3-030-26752-0_10
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