shre1000 / sentiment-analysis-of-twitter-data-using-pyspark-and-live-graphs Goto Github PK

In this project, Sentiment Analysis Application is developed using Pyspark which is combination of Apache Spark and Python. This application fetches Twitter data in live stream and classifies tweets into positive and negative categories. For sentiment classification of tweets, machine learning model (Voting Mechanism) has been developed. Spark’s ability to perform well on iterative algorithms makes it ideal for implementing machine learning techniques as, at their vast majority, machine learning algorithms are based on iterative jobs. Further, live visualization of results is done using Flask and Chart.js technology. Visualization gives the ability to combine data in order to create new insight.