Sarcasm detection in comments from Reddit
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Updated
Jul 18, 2018 - Jupyter Notebook
Sarcasm detection in comments from Reddit
Class Project (7th Semester, IR&TM course)
NLP | Zero to Hero Course Tensorflow| Text classification Model to understand sentiments in text.
An NLP based APP includes features for spam detection, sentiment analysis, stress detection, hate and offensive content detection, and sarcasm detection. It leverages Natural Language Processing (NLP) techniques and machine learning models to analyze and classify text inputs. Table of Contents
Repository of the Project 5: Sarcasm detection in sentences using neural networks, word embeddings and padding. Performing data cleaning & preparation, data visualization and creating a user input as well as a small website using Streamlit.
Multilingual sarcasm detector for detecting sarcasm from news article titles
Project made in Jupyter Notebook with "News Headlines Dataset For Sarcasm Detection" from Kaggle.
The code for "Sarcasm Detection with Commonsense Knowledge"
A deep learning approach for detecting sarcasm in Headlines
Text Mining and Sarcasm Detection on News Data
A project consisting of analysis of sarcasm in text using Natural Language Processing techniques. It highlights the importance of context and punctuation in sarcasm detection. Different deep learning models are applied and compared to get the best accuracy in sarcasm detection.
Sarcasm detection model, trained on Sarcasm on Reddit Dataset.
This is an NLP project, where I am attempting to detect sarcasm in social networks in Persian language.
Different Analytics about sarcasm on posts from Reddit using NLP techniques
[LREC-COLING'24] Source code for the paper "When Do More Contexts Help with Sarcasm Recognition?"
Detecting sarcasm in Reddit comments
A sarcasm detector based on state of the art NLP techniques. The implementation is based on the Encoder model and incorporates a few variations. The website uses a backend made using FLASK and deployed using Heroku .The readme contains comprehensive details about the project!
Sarcasm detection in textual data using different feature embeddings and models.
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