In this project i have done live Twitter Sentiment Analysis with NLTK and produced the result through live graph.
Natural language processing (NLP) is an area of computer science and artificial intelligence concerned with the interactions between computers and human (natural) languages, in particular how to program computers to process and analyze large amounts of natural language data. It is the branch of machine learning which is about analyzing any text and handling predictive analysis.
The Natural Language Toolkit (NLTK) is a platform used for building Python programs that work with human language data for applying in statistical natural language processing (NLP). It contains text processing libraries for tokenization, parsing, classification, stemming, tagging and semantic reasoning.
Visualization have a greater impact than just a few words. It is better grasped and understood. And yes reading blogs do help you a lot. You discover new things and new technology. I came across NLP and when i came to know about it. I got inclined towards it and the idea of working on it strike my mind. Visualizing through graph the live Twitter Sentiment got my attention and i started working on it.
Steps that were implemented are:-
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Getting Data from Twitter Streaming API
- Step 1: Getting Twitter API keys
- Step 2: Connecting to Twitter Streaming API and downloading data
- Step 3: Mining the tweets
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Entering the phase or words whose relevant tweets you want to stream
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Ploting those live stream on live graph
- When we gave the word happy .The live graph that is been created using live data coming from Twitter streaming API has a graph with increaing y-axis showing postive tweet for happy word:
- When we gave the word covid19.The live that is been created using live data coming from Twitter streaming API has a graph with decreaing y-axis showing negative tweet for a covid19 word:
- Live Twitter Sentiment Analysis by Edmauryaishu medium post
