Emotion Detection and Recognition from texts are recent fields of research that are closely related to Emotion Analysis. Emotion Analysis aims at detecting and recognizing feelings through the expressions from sentences, such as anger, surprise, joy, fear, sadness, love etc.

Sep 20, 2023 · We conducted experiments with a lexicon-based approach and classic methods of machine learning, appropriate for text processing, such as Naïve Bayes (NB), support vector machine (SVM) and with deep learning using neural networks (NN) to develop a model for detecting emotions in a text.

Natural language processing (NLP) techniques can be used to analyze text data and identify the emotions expressed in it. The aim of this project is to develop a model that uses NLP techniques to accurately detect emotions in text data. The model can be used for sentiment analysis, customer feedback analysis, and social media monitoring.

In this paper, we present a comprehensive study on leveraging deep learning techniques for text- based emotion recognition. Our approach encompasses the entire pipeline, starting from data collection and preprocessing to model training and evaluation.

This Jupyter Notebook implements a machine learning pipeline to detect emotions from textual data. It leverages natural language processing (NLP) techniques for text cleaning and feature engineering, followed by logistic regression for emotion classification.

Aug 23, 2022 · In this article, we have proposed a hybrid (machine learning + deep learning) model to identify emotions in text. Convolutional neural network (CNN) and Bi-GRU were exploited as deep learning techniques. Support vector machine is used as …

The ability to identify emotions in text is essential for a range of applications, including sentiment analysis, customer feedback analysis, and monitoring mental health. In recent years, machine learning algorithms have become more widely utilized to automatically classify text into distinct emotion categories.

Feb 19, 2021 · In this article, I will take you through how to solve the problem of text emotions detection with machine learning using Python. In machine learning, the detection of textual emotions is the problem of content-based classification, which is …

Sep 20, 2023 · Our research demonstrates the potential of machine learning approaches to detect emotions from a text and improve human-machine interaction.

Jan 1, 2024 · Emotion detection using machine learning-based approaches can be broadly divided into four types: supervised learning, unsupervised learning, and semisupervised learning. A supervised learning algorithm analyzes the training data and derives a function that it uses to map new examples [21].