Search Results for author:
Found 12 papers, 1 papers with code
CIC@LT-EDI-ACL2022: Are transformers the only hope? Hope speech detection for Spanish and English comments
Hope is an inherent part of human life and essential for improving the quality of life.
MUCS@LT-EDI-EACL2021:CoHope-Hope Speech Detection for Equality, Diversity, and Inclusion in Code-Mixed Texts
Three models namely, CoHope-ML, CoHope-NN, and CoHope-TL based on Ensemble of classifiers, Keras Neural Network (NN) and BiLSTM with Conv1d model respectively are proposed for the shared task.
MUCIC at ComMA@ICON: Multilingual Gender Biased and Communal Language Identification Using N-grams and Multilingual Sentence Encoders
These approaches obtained the highest performance in the shared task for Meitei, Bangla, and Multilingual texts with instance-F1 scores of 0. 350, 0. 412, and 0. 380 respectively using Pre-aggregation of labels.
MUCS@TechDOfication using FineTuned Vectors and n-grams
The increase in domain specific text processing applications are demanding tools and techniques for domain specific Text Classification (TC) which may be helpful in many downstream applications like Machine Translation, Summarization, Question Answering etc.
MUCIC@LT-EDI-ACL2022: Hope Speech Detection using Data Re-Sampling and 1D Conv-LSTM
Spreading positive vibes or hope content on social media may help many people to get motivated in their life.
LA-SACo: A Study of Learning Approaches for Sentiments Analysis inCode-Mixing Texts
Sentiments/opinions/reviews’ of users posted on social media are the valuable information that have motivated researchers to analyze them to get better insight and feedbacks about any product such as a video in Instagram, a movie in Netflix, or even new brand car introduced by BMW.
MUCS@DravidianLangTech-EACL2021:COOLI-Code-Mixing Offensive Language Identification
This paper describes the models submitted by the team MUCS for Offensive Language Identification in Dravidian Languages-EACL 2021 shared task that aims at identifying and classifying code-mixed texts of three language pairs namely, Kannada-English (Kn-En), Malayalam-English (Ma-En), and Tamil-English (Ta-En) into six predefined categories (5 categories in Ma-En language pair).
MUCIC@TamilNLP-ACL2022: Abusive Comment Detection in Tamil Language using 1D Conv-LSTM
To address the automatic detection of abusive languages in online platforms, this paper describes the models submitted by our team - MUCIC to the shared task on “Abusive Comment Detection in Tamil-ACL 2022”.
NLP Progress in Indigenous Latin American Languages
The paper focuses on the marginalization of indigenous language communities in the face of rapid technological advancements.
GuReT: Distinguishing Guilt and Regret related Text
The intricate relationship between human decision-making and emotions, particularly guilt and regret, has significant implications on behavior and well-being.
ReDDIT: Regret Detection and Domain Identification from Text
In this paper, we present a study of regret and its expression on social media platforms.
PolyHope: Two-Level Hope Speech Detection from Tweets
This strict annotation process resulted in promising performance for simple machine learning classifiers with only bi-grams; however, binary and multiclass hope speech detection results reveal that contextual embedding models have higher performance in this dataset.
