Twitter Analytics application
Project goal: deploy near real-time Tweets' processing application that could support a social media campaign on Twitter
Key functionalities:
One of the main assumptions taken in the application design process was that the end users will be able to monitor in real time how their tweets are perceived by the community.
Application is using streaming API published by Twitter to gather all tweets related to monitored twitter accounts.
API is consumed by the python script build into the Django application, whose role is to parse data, store in PostgreSQL database and for archiving purposes save JSON messages to files stored in S3.
Application is using streaming API published by Twitter to gather all tweets related to monitored twitter accounts.
API is consumed by the python script build into the Django application, whose role is to parse data, store in PostgreSQL database and for archiving purposes save JSON messages to files stored in S3.
To deliver a flexible and comprehensive analysis of Twitter data, the interactive dashboard has been implemented with the use of Bokeh library.
End users are able to analyze data from different perspectives to gather insights they are interested in.
End users are able to analyze data from different perspectives to gather insights they are interested in.
Application supports end users with a comparison of monitored Twitter accounts to help them understand how Internet community reacts to communication strategies used by other Twitter users.
Solution architecture:
