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Microblogging services like Twitter and Facebook collect millions of usergenerated content every moment about trending news, occurring events, and soon. Nevertheless, it is really a nightmare to find information of interestthrough the huge amount of available posts that are often noise and redundant.In general, social media analytics services have caught increasing attentionfrom both side research and industry. Specifically, the dynamic context ofmicroblogging requires to manage not only meaning of information but also theevolution of knowledge over the timeline. This work defines Time AwareKnowledge Extraction (briefly TAKE) methodology that relies on temporalextension of Fuzzy Formal Concept Analysis. In particular, a microblogsummarization algorithm has been defined filtering the concepts organized byTAKE in a time-dependent hierarchy. The algorithm addresses topic-basedsummarization on Twitter. Besides considering the timing of the concepts,another distinguish feature of the proposed microblog summarization frameworkis the possibility to have more or less detailed summary, according to theuser's needs, with good levels of quality and completeness as highlighted inthe experimental results.

Time Aware Knowledge Extraction for Microblog Summarization on Twitter