The paper gives the outline of key analyses and methods, accommodating at that point again enterprise structural planning change and based on social system approach. Social system is a place where individuals exchange and share data related to the current events all over the world .This behavior that point again of clients made us focus on this logic that handling these substance might commercial us to the extraction the current subject of interest between the users. Applying data clustering system like post Text-Frequency-based approach over these content might leads us up to the mark be that as it may there will be some shot of false positives. We propose a likelihood model that can catch both normal saying behavior that point again of a customer and too the recurrence of clients happening in their mentions. It too lives up to expectations great indeed the substance of the messages are non-literary data like pictures and so forth .The proposed mention-abnormality based approaches can distinguish new points at slightest as early as text-abnormality based approaches, and in some cases much previous at the point when the subject is poorly identified by the literary substance in the posts.

Change Point Detection, Abnormality Scores, Notice

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