Twitter Sentiment Analysis using Machine Learning Techniques: A Case Study of ChatGPT

Title

Twitter Sentiment Analysis using Machine Learning Techniques: A Case Study of ChatGPT

Creator

Kumari R.; Kumar S.

Description

ChatGPT is a powerful AI bot developed by OpenAI. This technology has the potential to generate a humanlike response. ChatGPT is a pre-trained system capable of generating chat and understanding human speech. This paper identified the responses of ChatGPT users through related tweets with the help of natural language processing and machine learning techniques. This paper uses textBlob, VADER and human annotation to find the sentiment of each tweet; countvectorizer is used for feature extraction and different machine learning algorithms to classify them into different classes. LeXmo is used to identify the various sentiment analyses, and it is observed that positive and trust emotions are higher than other sentiments. SVM with 10-fold cross-validation shows better results than other techniques. 2023 IEEE.

Source

Proceedings of IEEE InC4 2023 - 2023 IEEE International Conference on Contemporary Computing and Communications

Date

2023-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

chatGPT; NLP and ML Techniques); Sentiment analysis; Twitter Data Analysis

Coverage

Kumari R., (IFHE) University, ICFAI Business School (IBS) Bangalore Off-Campus Center of ICFAI Foundation for Higher Education, Bangalore, India; Kumar S., CHRIST (Deemed to Be University), Department of Computer Science and Engineering, Bangalore, India

Rights

Restricted Access

Relation

ISBN: 979-835033577-4

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/InC457730.2023.10262961

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174706225&doi=10.1109%2fInC457730.2023.10262961&partnerID=40&md5=fb0c26950ae77605c354ecf080a9f81d