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result in a dynamic tag cloud. To do this, we design and implement a Web interface that allows multiple users to input keywords and visualize their aggregate results in real time. Also, we empirically compare the results of dynamic tag clouds to ensure that they are visualized correctly. Through this research, the users can
This paper describes a methodology approach and a tool dedicated to the exploration of the Twitter social stream by combining different contextual parameters such as time, keywords, gender or the opinion. The exploration can be made in two main modes depending on the fact that the phenomenon is either known or not
the public users (voters), collected by means of crawling during the course of election. In order to gain useful insights about the US elections, we scored the sentiments for each tweet using different metrics and performed a time series analysis for candidates and different topics (identified by specific keywords). In
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.