Twitter sentiment analysis using five machine learning techniques

Twitter Sentiment Analysis using 5 Machine learning Techniques

Implementation Details:
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1. Twitter data is collected for topic “apple” and stored as twitter.json file. The data will be added in the same file for execution of Twitterdata.py

2. Collected tweets from json file is extracted stored as tweet.csv
data extracted from each tweet are

tweet_id
tweet_time
tweet_author
tweet_author_id
tweet_language
tweet_text
polarity
tweet_sentiment

More 1000 tweets are collected

3. 5 machine learning techniques were applied

1.Naive Bayes
2.Logistics regression
3.SVM technique
4.Random forest and
5.K-means Clustering

Plots are arrived
For the taken dataset, x-train and x-test and y-train & y-test are arrived.

from which te error rate is calculated for all techniques

4. Accuracy for all techniques is arrived and plotted.

Python Demo

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