Work

Emotion Classification from Text Data using NLP Techniques

Year: 2025

Type: article

Abstract: This paper presents an approach to emotion classification from textual data using Natural Language Processing (NLP) techniques. The study focuses on preprocessing text, feature extraction, and classification using supervised learning algorithms. The objective is to identify emotional states such as joy, sadness, anger, fear, and surprise from text data. Experimental results show that the proposed model achieves high accuracy and can be applied in sentiment analysis, mental health monitoring, and customer feedback evaluation.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.17356038

Authors: Syeda Rifat Batool (2022-SE-34), Syeda Rifat Batool (2022-SE-34), Ayesha Shafaqat (2022-SE-03), Ayesha Shafaqat (2022-SE-03)

Language: English

Topic: Sentiment Analysis and Opinion Mining

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W7091492696

FWCI:

Cites:

Cited by:

Related to: