Project By: Deepthi, Gagana, Kalyani, Rahul, Satyajeet, Sushmitha
Sentiment Analysis on ChatGPT
ChatGPT is a language model generates natural language responses to a given prompt or input
In January 2023, ChatGPT acquired 100 million monthly active users
User’s Feedback:
Positive – Expressing gratitude and praising the ability to provide information
Neutral – Using as a convenient tool without expressing any emotions
Negative – Expressing frustration and showing concerns over its impact on human employment
Data Collection : Scraping tweets from Twitter
Data Preprocessing : Duplication removal, lowercasing and noise removal (punctuation, stopwords, URLs, @users)
Extracting features : Retrieving geographical info from a user’s profile location and timestamp info
Categorizing and Classifying : Classify tweets into positive, neutral, or negative and Identifying the most discussed topics related to ChatGPT
Data Visualization: Graphically represent the extracted data
1 .Clone the repo first from github .
2 .After cloning ,you need to few pip installs to have all necessary tools .
pip install seaborn
pip install matplotlib
pip install numpy
pip install pandas
pip install textblob
pip install nltk
pip install nrclex
pip install geopy langdetect
pip install tqdm certifi
pip install googletrans==3.1.0a0
pip install wordcloud
pip install re
pip install collections
pip install emoji
pip install plotly
3.After all the libraries are successfully installed, unzip the file and import the project.
4.Run main.py and
5.From nltk download popup download all
6.GetMostreq.py to get The 10 most frequently most occurred words in Tweets and Identifying the most frequently discussed topic in twitter about ChatGPT
