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Found 22 papers, 2 papers with code
CIC NLP at SMM4H 2022: a BERT-based approach for classification of social media forum posts
This paper describes our submissions for the Social Media Mining for Health (SMM4H) 2022 shared tasks.
GS_DravidianLangTech@2025: Women Targeted Abusive Texts Detection on Social Media
The increasing misuse of social media has become a concern; however, technological solutions are being developed to moderate its content effectively.
Advancing Sentiment Analysis in Tamil-English Code-Mixed Texts: Challenges and Transformer-Based Solutions
The sentiment analysis task in Tamil-English code-mixed texts has been explored using advanced transformer-based models.
Enhancing Multi-Label Emotion Analysis and Corresponding Intensities for Ethiopian Languages
As users express different emotions simultaneously in a single instance, annotating emotions in a multilabel setting such as the EthioEmo (Belay et al., 2025) dataset effectively captures this dynamic.
CULEMO: Cultural Lenses on Emotion -- Benchmarking LLMs for Cross-Cultural Emotion Understanding
We use this benchmark to evaluate several state-of-the-art LLMs on culture-aware emotion prediction and sentiment analysis tasks.
Comparative Approaches to Sentiment Analysis Using Datasets in Major European and Arabic Languages
This study explores transformer-based models such as BERT, mBERT, and XLM-R for multi-lingual sentiment analysis across diverse linguistic structures.
Advanced Machine Learning Techniques for Social Support Detection on Social Media
Additionally, we achieved a 0. 4\% increase in the macro F1 score for the second task and a 0. 7\% increase for the third task, compared to previous work utilizing traditional machine learning with psycholinguistic and unigram-based TF-IDF values.
Evaluating the Capabilities of Large Language Models for Multi-label Emotion Understanding
The results show that accurate multi-label emotion classification is still insufficient even for high-resource languages such as English, and there is a large gap between the performance of high-resource and low-resource languages.
Ethio-Fake: Cutting-Edge Approaches to Combat Fake News in Under-Resourced Languages Using Explainable AI
Assessment of the outcomes of the experiments shows that the ensemble learning approach has the highest accuracy, achieving a 0. 99 F1 score.
Exploring Sentiment Dynamics and Predictive Behaviors in Cryptocurrency Discussions by Few-Shot Learning with Large Language Models
This study performs analysis of Predictive statements, Hope speech, and Regret Detection behaviors within cryptocurrency-related discussions, leveraging advanced natural language processing techniques.
Analyzing Emotional Trends from X platform using SenticNet: A Comparative Analysis with Cryptocurrency Price
This study delves into the relationship between emotional trends from X platform data and the market dynamics of well-known cryptocurrencies Cardano, Binance, Fantom, Matic, and Ripple over the period from October 2022 to March 2023.
NLP Progress in Indigenous Latin American Languages
The paper focuses on the marginalization of indigenous language communities in the face of rapid technological advancements.
EthioMT: Parallel Corpus for Low-resource Ethiopian Languages
Recent research in natural language processing (NLP) has achieved impressive performance in tasks such as machine translation (MT), news classification, and question-answering in high-resource languages.
EthioLLM: Multilingual Large Language Models for Ethiopian Languages with Task Evaluation
We open-source our multilingual language models, new benchmark datasets for various downstream tasks, and task-specific fine-tuned language models and discuss the performance of the models.
First Attempt at Building Parallel Corpora for Machine Translation of Northeast India's Very Low-Resource Languages
This paper presents the creation of initial bilingual corpora for thirteen very low-resource languages of India, all from Northeast India.
SpaDeLeF: A Dataset for Hierarchical Classification of Lexical Functions for Collocations in Spanish
In this paper, we present a dataset of most frequent Spanish verb-noun collocations and sentences where they occur, each collocation is assigned to one of 37 lexical functions defined as classes for a hierarchical classification task.
Automatic Translation of Hate Speech to Non-hate Speech in Social Media Texts
In this paper, we investigate the issue of hate speech by presenting a novel task of translating hate speech into non-hate speech text while preserving its meaning.
Enhancing Translation for Indigenous Languages: Experiments with Multilingual Models
This paper describes CIC NLP's submission to the AmericasNLP 2023 Shared Task on machine translation systems for indigenous languages of the Americas.
Parallel Corpus for Indigenous Language Translation: Spanish-Mazatec and Spanish-Mixtec
In this paper, we present a parallel Spanish-Mazatec and Spanish-Mixtec corpus for machine translation (MT) tasks, where Mazatec and Mixtec are two indigenous Mexican languages.
Natural Language Processing in Ethiopian Languages: Current State, Challenges, and Opportunities
This survey delves into the current state of natural language processing (NLP) for four Ethiopian languages: Amharic, Afaan Oromo, Tigrinya, and Wolaytta.
Transformer-based Model for Word Level Language Identification in Code-mixed Kannada-English Texts
Using code-mixed data in natural language processing (NLP) research currently gets a lot of attention.
The Effect of Normalization for Bi-directional Amharic-English Neural Machine Translation
Machine translation (MT) is one of the main tasks in natural language processing whose objective is to translate texts automatically from one natural language to another.
