Abstract
Microblogging platforms are at the core of what is known as the Live Web: the most dynamic, and fast changing portion of the web, where content is generated constantly by the users, in snippets of information. Therefore, the Live Web (or Now Web) is a good source of information for event detection, because it reflects what is happening in the physical world in a timely manner. Meanwhile, it introduces constraints and challenges: large volumes of unstructured, noisy data, which are also as diverse as the users and their interests. In this work we present a prototype User Interface (UI) of our TwInsight system, which deals with event detection of real-world phenomena from microblogs. Our system applies i) emotion extraction techniques on microblogs, and ii) location extraction techniques on user profiles. Combining these two, we convert highly unstructured content to thematically enriched, locational information, which we present to the user through a unified front-end. A separate area of the UI is used to show events to the user, as they are identified. Taking into account the characteristics of the setting, all of the components are updated along the temporal dimension. We discuss each part of our UI in detail, and present anecdotal evidence of its operation through two real-life event examples.
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Valkanas, G., Gunopulos, D. (2013). A UI Prototype for Emotion-Based Event Detection in the Live Web. In: Holzinger, A., Pasi, G. (eds) Human-Computer Interaction and Knowledge Discovery in Complex, Unstructured, Big Data. HCI-KDD 2013. Lecture Notes in Computer Science, vol 7947. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39146-0_9
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DOI: https://doi.org/10.1007/978-3-642-39146-0_9
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