Many organizations have been reported to create and monitoring targeted Twitter streams to collect a bunch of information and understand according to user's view. Targeted Twitter stream is main usually constructed by filtering tweets and that abused words with predefined selection criteria. Due to its invaluable business value of timely information from these tweets, it's a necessary to understand that abused word's language for a large body of downstream applications, such as named entity recognition (NER), event detecting and summarizing that particular word, opinion mining, sentiment analysis, and etc. In these proposed system application is develope which take tweet is a input and search semantic negative or illegal words from database. Generate report of that abusing words and send to cyber crime's site. Then depending on the tweet, track the related information of the person. Track all the tweets of that particular person and track that person through identification databases. Then take a action by cyber crime. And after that prevent the tweet.


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    Title :

    User tracking using tweet segmentation and word


    Contributors:


    Publication date :

    2017-04-01


    Size :

    312223 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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