SemEval2022 Patronizing and Condescending Language (PCL) Detection

Overview

SemEval2022 Patronizing and Condescending Language (PCL) Detection

License: MIT

This task is from SemEval 2022.

What is Patronizing and Condescending Language (PCL)?

We all are patronizing and condescending sometimes. And of course, we all are susceptible to be condescended and patronized by others. But some groups are, unfortunately, more used to be referred to with this undervaluing treatment. The so-called vulnerable communities seem to be the perfect target for charity and pity-driven texts, condescension and patronization in news stories.

PCL is often involuntary and unconscious and the authors using such language are usually trying to help the communities in need, by raising awareness, moving the audience to action or standing for the rights of the under-represented. But PCL can potentially be very harmful, as it feeds tereotypes, routinizes discrimination and drives to greater exclusion.

For more details about the task check out here.

Abstract

Software implementation

All source code used to generate the results and figures in the paper are in the code folder. The calculations and figure generation are all run inside Jupyter notebooks. The data used in this study is available upon request.

Getting the code

You can download a copy of all the files in this repository by cloning the git repository:

git clone https://github.com/daniel-saeedi/PCL_Detection_SemEval2022.git

or download a zip archive.

Dependencies

Run this command to install dependencies:

pip3 install -r requirements.txt
Owner
Daniel Saeedi
I major in Computer Engineering at University of Tehran.
Daniel Saeedi
Safe Local Motion Planning with Self-Supervised Freespace Forecasting, CVPR 2021

Safe Local Motion Planning with Self-Supervised Freespace Forecasting By Peiyun Hu, Aaron Huang, John Dolan, David Held, and Deva Ramanan Citing us Yo

Peiyun Hu 90 Dec 01, 2022
Code release to accompany paper "Geometry-Aware Gradient Algorithms for Neural Architecture Search."

Geometry-Aware Gradient Algorithms for Neural Architecture Search This repository contains the code required to run the experiments for the DARTS sear

18 May 27, 2022
Implementation of association rules mining algorithms (Apriori|FPGrowth) using python.

Association Rules Mining Using Python Implementation of association rules mining algorithms (Apriori|FPGrowth) using python. As a part of hw1 code in

Pre 2 Nov 10, 2021
Virtual Dance Reality Stage is a feature that offers you to share a stage with another user virtually.

Virtual Dance Reality Stage is a feature that offers you to share a stage with another user virtually. It uses the concept of Image Background Removal using DeepLab Architecture (based on Semantic Se

Devashi Choudhary 5 Aug 24, 2022
Weak-supervised Visual Geo-localization via Attention-based Knowledge Distillation

Weak-supervised Visual Geo-localization via Attention-based Knowledge Distillation Introduction WAKD is a PyTorch implementation for our ICPR-2022 pap

2 Oct 20, 2022
A light and fast one class detection framework for edge devices. We provide face detector, head detector, pedestrian detector, vehicle detector......

A Light and Fast Face Detector for Edge Devices Big News: LFD, which is a big update of LFFD, now is released (2021.03.09). It is strongly recommended

YonghaoHe 1.3k Dec 25, 2022
Iranian Cars Detection using Yolov5s, PyTorch

Iranian Cars Detection using Yolov5 Train 1- git clone https://github.com/ultralytics/yolov5 cd yolov5 pip install -r requirements.txt 2- Dataset ../

Nahid Ebrahimian 22 Dec 05, 2022
Back to the Feature: Learning Robust Camera Localization from Pixels to Pose (CVPR 2021)

Back to the Feature with PixLoc We introduce PixLoc, a neural network for end-to-end learning of camera localization from an image and a 3D model via

Computer Vision and Geometry Lab 610 Jan 05, 2023
PClean: A Domain-Specific Probabilistic Programming Language for Bayesian Data Cleaning

PClean: A Domain-Specific Probabilistic Programming Language for Bayesian Data Cleaning Warning: This is a rapidly evolving research prototype.

MIT Probabilistic Computing Project 190 Dec 27, 2022
Data pipelines for both TensorFlow and PyTorch!

rapidnlp-datasets Data pipelines for both TensorFlow and PyTorch ! If you want to load public datasets, try: tensorflow/datasets huggingface/datasets

1 Dec 08, 2021
An open source Python package for plasma science that is under development

PlasmaPy PlasmaPy is an open source, community-developed Python 3.7+ package for plasma science. PlasmaPy intends to be for plasma science what Astrop

PlasmaPy 444 Jan 07, 2023
Nested Graph Neural Network (NGNN) is a general framework to improve a base GNN's expressive power and performance

Nested Graph Neural Networks About Nested Graph Neural Network (NGNN) is a general framework to improve a base GNN's expressive power and performance.

Muhan Zhang 38 Jan 05, 2023
NAS-Bench-x11 and the Power of Learning Curves

NAS-Bench-x11 NAS-Bench-x11 and the Power of Learning Curves Shen Yan, Colin White, Yash Savani, Frank Hutter. NeurIPS 2021. Surrogate NAS benchmarks

AutoML-Freiburg-Hannover 13 Nov 18, 2022
A Repository of Community-Driven Natural Instructions

A Repository of Community-Driven Natural Instructions TLDR; this repository maintains a community effort to create a large collection of tasks and the

AI2 244 Jan 04, 2023
Official Code Release for Container : Context Aggregation Network

Container: Context Aggregation Network Official Code Release for Container : Context Aggregation Network Comparion between CNN, MLP-Mixer and Transfor

peng gao 42 Nov 17, 2021
A cross-lingual COVID-19 fake news dataset

CrossFake An English-Chinese COVID-19 fake&real news dataset from the ICDMW 2021 paper below: Cross-lingual COVID-19 Fake News Detection. Jiangshu Du,

Yingtong Dou 11 Dec 01, 2022
Code for Greedy Gradient Ensemble for Visual Question Answering (ICCV 2021, Oral)

Greedy Gradient Ensemble for De-biased VQA Code release for "Greedy Gradient Ensemble for Robust Visual Question Answering" (ICCV 2021, Oral). GGE can

21 Jun 29, 2022
Using Random Effects to Account for High-Cardinality Categorical Features and Repeated Measures in Deep Neural Networks

LMMNN Using Random Effects to Account for High-Cardinality Categorical Features and Repeated Measures in Deep Neural Networks This is the working dire

Giora Simchoni 10 Nov 02, 2022
Pytorch implementation of the paper "Optimization as a Model for Few-Shot Learning"

Optimization as a Model for Few-Shot Learning This repo provides a Pytorch implementation for the Optimization as a Model for Few-Shot Learning paper.

Albert Berenguel Centeno 238 Jan 04, 2023
Modeling Category-Selective Cortical Regions with Topographic Variational Autoencoders

Modeling Category-Selective Cortical Regions with Topographic Variational Autoencoders

1 Oct 11, 2021