Sentiment Classifier of Tweets, based on Lambda Architecture.
This application makes use of Lambda Architecture to perform real-time sentiment analysis on Tweets in a big data scenario.
In order to run this application is needed a correct installation and configuration of the following technologies:
- JDK - 11 or above
- Apache Storm - 2.4.0
- Apache Hadoop - 3.2.4
- Apache HBase - 2.4.15
Other dependencies such as LingPipe and JavaFX are automatically added through Maven.
Before running the application it is required to add your BEARER_TOKEN to the configuration file src/main/resources/gui/credentials.json in order to access Twitter API v2. In case you don't have one you can request it here.
To run the application make sure that Apache Storm, Apache Hadoop and Apache HBase are currently running in your configuration, then launch src/main/java/gui/GUIStarter main() after compiling the project through Maven.
The usage of an IDE such as IntelliJ Idea is highly recommended.
This is the first page displayed when launching the application. Here you can enter the keywords you wish to analyze. When clicking Start Analysis the architecture is started.
This is the main page of the application where the real-time results of the analysis are reported. On the top-right corner the dedicated button allows to stop the architecture.
Here is reported a demo video of the application:
SentimentAnalysis.mp4
This work is a full term project for the course of Parallel Computing, held by professor Marco Bertini at University of Florence.
Further information over this implementation is available in the report.