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
```