Tweet-sentiment-Trendz

This web application is a scalable version of Tweettrendz. This application uses Twitter Streaming API to fetch tweets from the twitter hose in real-time with Geolocation & English Language Filtering and plot the tweets on a map along with the sentiment of the tweet.

Application utilises:

• Google Map API: Plotting the tweets on a map with customised Markers
• Elastic Search: Efficient searching of tweets based on keywords stored in JSON format on AWS ElasticSearch Service
• Textblob Sentiment Analysis API: This generates the positive, negative or neutral sentiment evaluation for the text of the submitted Tweet.
• Apache Kafka: A queueing service to store the streamed tweets making them available for consumption and notification service that notifies the subscriber of new available tweets.

Run the application:

• Download the project
• Add/Change Twitter, AWS, and MonkeyLearn API Keys in config.ini file.
• Run manage.py file

   python manage.py runserver

• Run sentiment.py and kafkatweets.py on AWS instance, if you have created one. Else, you can look onto the instructions below

Installation instruction of Apache Kafka on AWS:

• Install Kafka by downloading

  sudo apt-get install default-jre
  sudo apt-get install zookeeperd
  wget "http://mirror.cc.columbia.edu/pub/software/apache/kafka/0.10.2.0/kafka_2.11-0.10.2.0.tgz"
  tar -xzf kafka_2.11-0.10.2.0.tgz

• Run the Zookeeper

  cd kafka_2.11-0.10.2.0
  bin/zookeeper-server-start.sh config/zookeeper.properties

• In config/server.properties, add the following lines listeners=PLAINTEXT://:9092 advertise.listeners=PLAINTEXT://:9092 To save the read-only file,

  :w !sudo tee %
  O
  :q!

• Run the Kafka server on another Instaance's terminal

    KAFKA_HEAP_OPTS="-Xms512M -Xmx512M" bin/kafka-server-start.sh config/server.properties

• Finally, Run the below commands on different Instance's terminal

  python sentiment.py
  python kafkatweets.py