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social media. Discovering keyword-based correlated networks of these large graphs is an important primitive in data analysis, from which users can pay more attention about their concerned information in the large graph. In this paper, we propose and define the problem of keyword-based correlated network computation over a
posted by over 740,070 users who discussed about trafficking crimes and issues. CyTraSS supports keyword search, sentiment analysis, message statistics summarization, and influential leader identification. Emotion expressed in social media messages is extracted and aggregated quantitatively to indicate community mood. We
Early adopters of social media have focused on marketing opportunities and are trying to create a presence in key social environments, but this isn't enough. This strategy is much like the initial stages of the Web, when companies thought it was sufficient to simply have a website. Building a Web presence requires a lot of work-building a social media presence requires even more work. Social networking...
news and social media, extract events related to food hazards, and then organize the data in a structured format for easy consumption. We define an information template for food hazard event based on data from the Korean Ministry of Food and Drug Safety (MFDS), and use the template to aggregate informative keywords from
The amount of media that is being uploaded to social sites (such as Twitter, Facebook and Instagram) is providing a wealth of visual data (images and videos) augmented with additional information such as keywords, timestamps and GPS coordinates. Tapastreet1 provides access in real-time to this visual
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