Twitter data is very sparse and random. To get an idea of the topic on twitter, user must read through all the posts. This is very tedious and annoying. Each post is about 140 characters long. The summary of tweet in turn tells what the tweet is all about. This is a classic problem of Text Summarization.
We input from user trend which user wants to search for. We scrap the twitter data and find the posts regarding the topic and summarize it. We have solved this problem with techniques of Natural Language Processing and Information Retrieval.
A simple use case for this app will be to generate twitter summary on hourly basis.
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