A machine-learning model, as well as preliminary data process and feature extraction algorithms that would allow to successfully identify signs of propaganda in text data and to solve a binary classification task are built. . The goal of this research is to build a machine-learning model, as well as preliminary ...
The goal of this research is to build a machine-learning model, as well as preliminary data process and feature extraction algorithms that would allow to successfully identify signs of propaganda in text data and to solve a binary clas- sification task. The task is presented in two forms: article level propaganda de-.
We present ProtoTEx, a novel white-box NLP classification architecture based on prototype networks. 1. Paper · Code · IITD at the WANLP 2022 Shared Task ... mbzuai-nlp/propaganda-codeswitched-text • • 23 May 2023. Yet, it is common to find a mix of multiple languages in social media communication, a phenomenon ...
[PDF] Detection of Propaganda from News Articles using Deep Learning
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The main objective of this work is to identify the presence of propaganda in the given news articles by examining the text for as many as 14 propaganda patterns with the help of Convolution Neural Networks. (CNN) with Glove word embedding. The use of CNN helps achieve high accuracy in the prediction rate for a given ...
This is due to the annotators' requirement to comprehend each propaganda technique, recall and identify suitable techniques for specific texts, and accurately label the text spans associated with each propaganda technique. The training process consists of three stages. For Stage 1 and Stage 2, both annotators were ...
This paper proposes a deep learning method in order to combine sentiment scores with traditional Word2Vec vectors which result in a sentiment aware representation containing semantic and emotional information, which, when used together, result in a more accurate propaganda classification model.
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This paper presents the system developed by the NGU_CNLP team for addressing the shared task on Propaganda Detection in Arabic at WANLP 2022. The team participated in the shared tasks' two sub-tasks which are: 1) Pro- paganda technique identification in text and 2). Propaganda technique span identification. In the.
A hybrid method based on learning rules and an ensemble of machine learning methods has been developed for sentiment analysis and covert propaganda. The proposed rule-based model allows choosing the class-based lexical approach or on collected dictionaries. The combination of the methods based on dictionaries and rules ...
Mar 18, 2024 · The article provides a comprehensive overview of modern approaches to detecting and countering fake news and propaganda using information technology, particularly focusing on Natural Language Processing (NLP), multimodal analysis, and machine learning. The review ...
Feb 20, 2023 · The present study proposes a propaganda detection framework as a binary classification model based on a news repository. Several feature models are explored to develop a robust model such as part-of-speech, LIWC, word uni-gram, Embeddings from.