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A system that detects the most frequently occurring hash tags and named-entities from the live Twitter data stream and calculate sentiment values in real-time

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Realtime Twitter Analysis

A system that detects the most frequently occurring hash tags and named-entities from the live Twitter data stream and calculate sentiment values in real-time

Details

  • utilized Apache Storm to get and process realtime Twitter data
  • used Stanford NLP to do sentiment analysis on Twitter data
  • optimize the performance by parallelizing all the bolts

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A system that detects the most frequently occurring hash tags and named-entities from the live Twitter data stream and calculate sentiment values in real-time

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