PERSONALITY PREDICTION IN TWEETS

Implementation Details:
-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. Naive Bayes and Logistics regression are applied, Plots are arrived
For the taken dataset, x-train and x-test and y-train & y-test are arrived.
from which te error is calculated for both technique

4. tweet.csv is taken as input and person.csv is extracted

This is the collection of unique autor and his total tweets, with positive and negative counts, and polarity aggregation. From which personality is arrived.

tweet_author
tweet_count
tweet_positive
tweet_negative
polarity
personality

Python Demo