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Performed sentiment analysis on tweets posted in real-time using twitter’s API. Stored the tweets using Apache Kafka in the intermediate step and used Apache Spark streaming to process them. Stored the output sentiment using Elastic Search indices and visualized the results using Kibana.

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Live-Twitter-Sentiment-Analysis

Performed sentiment analysis on tweets posted in real-time using twitter’s API. Stored the tweets using Apache Kafka in the intermediate step and used Apache Spark streaming to process them. Stored the output sentiment using Elastic Search indices and visualized the results using Kibana.

To run the python files you first need to setup the Apache Spark, Apache Kafka, Elastic search and Twitter developer account.

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Performed sentiment analysis on tweets posted in real-time using twitter’s API. Stored the tweets using Apache Kafka in the intermediate step and used Apache Spark streaming to process them. Stored the output sentiment using Elastic Search indices and visualized the results using Kibana.

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