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Projet Twitter Sentiment Analysis

Technologies

Scikit-learn, Spark, AWS EMR, S3, Lambda, Kinesis, API Gateway, MQTT, React JS, RDS (Postgres SQL).

Website: here

Define a problem you want to solve

Our main purpose is to build a powerful platform system for real-time data analysis of tweets on twitter trends. We also want to analyse all the tweets of 2017 based on a downloaded sample of data (average of 6 To). All this data analysis will be accessible via a web interface that will be developed. We want to build a powerful system of sentiments analysis by making a database structure of tweets which is relevant about impacts and effects. The system should provide a faster way to execute Machine Learning methodologies behind data extracted from Twitter. Analysis news actuality by getting an analysis on actual trends with real stream data and building an efficient web interface to get results easily and keep a control on data continuously. We also wanted to make a comparison of sentiment analysis methods, for which we have taken a publication and tried to improve the results obtained and to propose new methods.

Exemple for the real stream architecture

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