Twitter Sentiment Analysis

🔹Overview:

Sentiment Analysis is one of the most common tasks in Data Science. The project objective to demonstrate sentiment analysis on tweets on specific topic/keyword and classify them into three different sentiments, using twitter API. This repository contains complete source code needed to run this project.

🔸Concepts:

• Natural Language Processing
• Sentiment Analysis

🔸Tools & Technologies:

• Python
• Twitter API
• Natural Language Toolkit
• Tweepy
• Textblob
• PyCharm
• Conda Environment

🔸Installation Guide:

• To install tweepy:

pip install tweepy

• To install textblob:

pip install textblob

🔹Implementation:

• Step 1: Set your Twitter Developer Account here to get started with.
• Step 2: Get your consumer key and access key for authentication purpose.
• Step 3: Run the twitter_sentiment_analyzer.py
• Step 4: Enter the topic/hashtag to retrieve the tweets, number to tweets to be analyzed and get the analysis report in form of Pie chart representation.

📌NOTE: To generate the API key and get the Authentication follow this steps.

🔹References:

Twitter API

🔹Contribution:

Contributions are always welcomed. Make sure you read the Contribution info before making pull request.

🔹Screenshots:

🔸Ouput (Entered Keyword-> Dogecoin):

🔸Pie chart representation of Analysis: