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Found 13 papers, 6 papers with code
EmoPars: A Collection of 30K Emotion-Annotated Persian Social Media Texts
The wide reach of social media platforms, such as Twitter, have enabled many users to share their thoughts, opinions and emotions on various topics online.
AliEdalat at SemEval-2022 Task 4: Patronizing and Condescending Language Detection using Fine-tuned Language Models, BERT+BiGRU, and Ensemble Models
In PCL category detection, our model outperforms the baseline model and achieves an F1-score of 0. 2531.
Ranked #4 on
Binary Condescension Detection
on DPM
Binary Condescension Detection
Multi-label Condescension Detection
A Large-Scale Analysis of Persian Tweets Regarding Covid-19 Vaccination
The Covid-19 pandemic had an enormous effect on our lives, especially on people's interactions.
Persian Emotion Detection using ParsBERT and Imbalanced Data Handling Approaches
EmoPars and ArmanEmo are two new human-labeled emotion datasets for the Persian language.
UTNLP at SemEval-2022 Task 6: A Comparative Analysis of Sarcasm Detection Using Generative-based and Mutation-based Data Augmentation
Using RoBERTa and mutation-based data augmentation, our best approach achieved an F1-sarcastic of 0. 38 in the competition's evaluation phase.
Ranked #1 on
Sarcasm Detection
on iSarcasm
UTNLP at SemEval-2021 Task 5: A Comparative Analysis of Toxic Span Detection using Attention-based, Named Entity Recognition, and Ensemble Models
Detecting which parts of a sentence contribute to that sentence's toxicity -- rather than providing a sentence-level verdict of hatefulness -- would increase the interpretability of models and allow human moderators to better understand the outputs of the system.
Sentiment Analysis of Persian-English Code-mixed Texts
The rapid production of data on the internet and the need to understand how users are feeling from a business and research perspective has prompted the creation of numerous automatic monolingual sentiment detection systems.
Investigating the effects of Goodreads challenges on individuals reading habits
Sharing our goals with others and setting public challenges for ourselves is a topic that has been the center of many discussions.
Social and Information Networks
Hybrid Model for Anomaly Detection on Call Detail Records by Time Series Forecasting
In this paper, a new hybrid method is proposed based on various anomaly detection methods such as GARCH, K-means, and Neural Network to determine the anomalous data.
A Regression Framework for Predicting User's Next Location using Call Detail Records
In this paper, we propose a data processing framework to predict user next location.
Real-time Travel Time Estimation Using Matrix Factorization
Since this approach can solve the sparsity problem that arises from the absence of cars in many road segments in a specific time interval, matrix factorization is suitable for estimating the travel time.
Proposing a Model for Predicting Passenger Origin-Destination in Online Taxi-Hailing Systems
Due to the significance of transportation planning, traffic management, and dispatch optimization, predicting passenger origin-destination has emerged as a crucial requirement for intelligent transportation systems management.
Short-term Demand Forecasting for Online Car-hailing Services using Recurrent Neural Networks
Recurrent neural networks have become one of the most popular methods for time series forecasting, however, due to the variety of these networks, the question that which type is the most appropriate one for this task remains unsolved.
