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FIRE 2022: Kolkata, India - Working Notes
- Kripabandhu Ghosh, Thomas Mandl, Prasenjit Majumder, Mandar Mitra:
Working Notes of FIRE 2022 - Forum for Information Retrieval Evaluation, Kolkata, India, December 9-13, 2022. CEUR Workshop Proceedings 3395, CEUR-WS.org 2023 - Preface.
Information Retrieval in Software Engineering (IRSE)
- Srijoni Majumdar, Ayan Bandyopadhyay, Samiran Chattopadhyay, Partha Pratim Das, Paul D. Clough, Prasenjit Majumder:
Overview of the IRSE track at FIRE 2022: Information Retrieval in Software Engineering. 1-9 - Bikram Ghosh, Pankaj Chowdhury, Utpal Sarkar:
Prediction of Useless and irrelevant Comments in C Language as per Surrounding Code Context. 10-14 - Mithun Das, Subhadeep Chatterjee:
Exploring Transformer-Based Models for Automatic Useful Code Comments Detection. 15-23 - Koyel Ghosh, Apurbalal Senapati:
Information Retrieval in Software Engineering utilizing a pre-trained BERT model. 24-28 - Sagar Joshi, Sumanth Balaji, Aditya Hari, Abhijeeth Singam, Vasudeva Varma:
Efficacy of Pretrained Architectures for Code Comment Usefulness Prediction. 29-33 - Aritra Mitra:
Evaluating Usefulness of C Comments using SVM and Naïve Bayes Classifier. 34-38 - Debjyoti Paul, Bitan Biswas, Rudrani Paul:
Using Transformer-based Pre-trained Language Model for Automated Evaluation of Comments to Aid Software Maintenance. 39-52 - Soumen Paul:
Source Code Comment Classification using Logistic Regression and Support Vector Machine. 53-59 - Sruthi S, Tanmay Basu:
Identification of the Relevance of Comments in Codes Using Bag of Words and Transformer Based Models. 60-65 - Yogesh Kumar Sahu, Ayan Das:
Automatic comment usefulness judgement via SVM and ANN using contextual token representations. 66-73 - Amisha Shingala, Namrata Shroff:
Comments in Source Code: A classification approach. 74-79
Sentiment analysis and homophobia detection of youtube comments in code-mixed Dravidian languages
- Kogilavani Shanmugavadivel, Malliga Subramanian, Prasanna Kumar Kumaresan, Bharathi Raja Chakravarthi, B. Bharathi, Subalalitha Chinnaudayar Navaneethakrishnan, Lavanya Sambath Kumar, Thomas Mandl, Rahul Ponnusamy, Vasanth Palanikumar, Manoj Balaji Jagadeeshan:
Overview of the Shared Task on Sentiment Analysis and Homophobia Detection of YouTube Comments in Code-Mixed Dravidian Languages. 80-91 - Sunil Saumya, Vanshita Jha, Shankar Biradar:
Sentiment and Homophobia Detection on YouTube using Ensemble Machine Learning Techniques. 92-99 - N. Muhammad Fadil, Lavanya S. K:
Sentiment Analysis of YouTube comments in Dravidian Code-Mixed Language using Deep Neural Network. 100-105 - Deepalakshmi Manikandan, Malliga Subramanian, Kogilavani Shanmugavadivel:
A System For Detecting Abusive Contents Against LGBT Community Using Deep Learning Based Transformer Models. 106-116 - Pranith P, V. Samhita, D. Sarath, Durairaj Thenmozhi:
Homophobia and Transphobia Detection of Youtube Comments in Code-Mixed Dravidian Languages using Deep learning. 117-123 - Josephine Varsha, B. Bharathi, A. Meenakshi:
Sentiment Analysis and Homophobia detection of YouTube comments in Code-Mixed Dravidian Languages using machine learning and transformer models. 124-137 - Manoj Balaji J, Chinmaya HS:
A Study on Sentimental Analysis, Homophobia-Transphobia Detection for Dravidian Languages. 138-146 - Asha Hegde, Hosahalli Lakshmaiah Shashirekha:
Leveraging Dynamic Meta Embedding for Sentiment Analysis and Detection of Homophobic/Transphobic Content in Code-mixed Dravidian Languages. 147-156 - Sushil Ugursandi, Anand Kumar M:
Sentiment Analysis and Homophobia detection of YouTube comments. 157-168 - Sivaprasath S, Lavanya Sambath Kumar, Sajeetha Thavareesan:
Homophobia, Transphobia Detection in Tamil, Malayalam, English Languages using Logistic Regression and Code-Mixed Data using AWD-LSTM. 169-176 - Aaron Samuel A, Lavanya Sambath Kumar, Subalalitha Chinnaudayar Navaneethakrishnan, Ratnasingam Sakuntharaj:
A Sequential DNN for Sentiment Analysis of Dravidian Code-Mixed Language Comments on YouTube. 177-183 - Supriya Chanda, Anshika Mishra, Sukomal Pal:
Sentiment Analysis and Homophobia detection of Code-Mixed Dravidian Languages leveraging pre-trained model and word-level language tag. 184-195 - Filip Nilsson, Sana Sabah Al-Azzawi, György Kovács:
Leveraging Sentiment Data for the Detection of Homophobic/Transphobic Content in a Multi-Task, Multi-Lingual Setting Using Transformers. 196-207
Anaphora Resolution from Social Media Text in Indian Languages (SocAnaRes-IL)
- Sobha Lalitha Devi:
Anaphora Resolution from Social Media Text in Indian Languages (SocAnaRes-IL) : 2 nd Edition-Overview. 208-214 - Vijay Kumari, Shaz Furniturewala, Gautam Bhambhani, Yashvardhan Sharma:
Anaphora Resolution from Social Media Text. 215-219
EmoThreat: Emotions & Threat Detection in Urdu
- Sabur Butt, Maaz Amjad, Fazlourrahman Balouchzahi, Noman Ashraf, Rajesh Sharma, Grigori Sidorov, Alexander F. Gelbukh:
Overview of EmoThreat: Emotions and Threat Detection in Urdu at FIRE 2022. 220-230 - Dejah Madhusankar, Avanthika Karthikeyan, Bharathi B:
Multi-Label Emotion Classification in Urdu. 231-237 - Anik Basu Bhaumik, Mithun Das:
Emotions & Threat Detection in Urdu using Transformer Based Models. 238-246 - José Antonio García-Díaz, Manuel Valencia-García, Gema Alcaraz-Mármol, Rafael Valencia-García:
Exploring Language Independent Linguistic Features and Transformers in a Multi-label Emotion Detection Challenge in Urdu using Nastalīq Script. 247-255 - Asha Hegde, Hosahalli Lakshmaiah Shashirekha:
Learning Models for Emotion Analysis and Threatening Language Detection in Urdu Tweets. 256-265 - Sakshi Kalra, Kushank Maheshwari, Saransh Goel, Yashvardhan Sharma:
Emotional Threat Speech Detection in Urdu Language using BERT Variants. 266-275 - Sakshi Kalra, Saransh Goel, Kushank Maheshwari, Yashvardhan Sharma, Shresht Bhowmick:
Applying TF-IDF and BERT-based Variants under Multilabel Classification for Emotion Detection in Urdu Language. 276-285 - Bin Wang, Hui Ning:
Notebook for Emotions & Threat Detection in Urdu @ FIRE 2022. 286-290 - Mingcan Guo, Zhongyuan Han, Leilei Kong, Zhijie Zhang, Zengyao Li, Haoyang Chen, Haoliang Qi:
Advantages of XLM-R Model for Urdu Sentiment Multi-Classification. 291-297 - Bénédicte Diot-Parvaz Ahmad, Pierre Magistry, Ilaine Wang, Damien Nouvel:
Leveraging BERT, MWE, and ML Models to Detect Emotions and Threats in Urdu. 298-308
Information Retrieval from Microblogs during Disasters (IRMiDis)
- Soham Poddar, Moumita Basu, Saptarshi Ghosh, Kripabandhu Ghosh:
Overview of the FIRE 2022 track: Information Retrieval from Microblogs during Disasters (IRMiDis). 309-313 - Vishal Nair:
Classification of Covid-19 Vaccine Opinion and Detection of Symptom-Reporting on Twitter Using Neural Networks. 314-319 - Sumanth Balaji, Sagar Joshi, Aditya Hari, Abhijeeth Singam, Vasudeva Varma:
COVID-19 vaccine stance classification from tweets. 320-324 - Shivangi Bithel:
CTC: COVID-19 Tweet Classification using CT-BERT. 325-330 - Kaustav Das:
Need for Vision: A data-centric approach towards analysing impact of COVID-19. 331-336 - Rashi Sharma, Harsh Tita:
Covid-19 Vaccine Stance Detection using Natural Language Processing and Machine Learning Algorithms. 337-345 - Sumana Madasu:
Classification of COVID-19 Tweets. 346-348 - Subinay Adhikary:
A Machine Learning Approach for COVID-19 Tweet Classification. 349-353 - Karabo Johannes Ntwaagae, Nkwebi Peace Motlogelwa, Edwin Thuma, Tebo Leburu-Dingalo, Gontlafetse Mosweunyane:
A Classification Approach to Detect Public Sentiments towards COVID-19 Vaccines. 354-360 - Akshit Bansal, Rohit Jain, Jatin Bedi:
Detecting COVID-19 Vaccine Stance and Symptom Reporting from Tweets using Contextual Embeddings. 361-368
Indian Language Summarization (ILSUM)
- Shrey Satapara, Bhavan Modha, Sandip Modha, Parth Mehta:
Findings of the First Shared Task on Indian Language Summarization (ILSUM): Approaches Challenges and the Path Ahead. 369-382 - Sangita Singh, Jyoti Prakash Singh, Akshay Deepak:
Deep Learning based Abstractive Summarization for English Language. 383-392 - Ashok Urlana, Sahil Manoj Bhatt, Nirmal Surange, Manish Shrivastava:
Indian Language Summarization using Pretrained Sequence-to-Sequence Models. 393-402 - Abinaya N, Anbukkarasi S, Varadhaganapathy S:
Extractive Text Summarization Using Word Frequency Algorithm for English Text. 403-408 - Arjit Agarwal, Soham Naik, Sheetal S. Sonawane:
Abstractive Text Summarization for Hindi Language using IndicBART. 409-417 - Kirti Kumari, Ranjana Kumari:
An Extractive Approach for Automated Summarization of Indian Languages using Clustering Techniques. 418-423 - Aishwarya Krishnakumar, Fathima Naushin A R, Mrithula K. L, B. Bharathi:
Text summarization for Indian languages using pre-trained models. 424-434 - Dhaval Taunk, Vasudeva Varma:
Summarizing Indian Languages using Multilingual Transformers based Models. 435-442 - Shayak Chakraborty, Darsh Kaushik, Sahinur Rahman Laskar, Partha Pakray:
Exploring Text Summarization Models for Indian Languages. 443-448 - Rahul Tangsali, Aabha Pingle, Aditya Vyawahare, Isha Joshi, Raviraj Joshi:
Implementing Deep Learning-Based Approaches for Article Summarization in Indian Languages. 449-463 - Doppalapudi Venkata Pavan Kumar, Srigadha Shreyas Raj, Pradeepika Verma, Sukomal Pal:
Extractive Text Summarization using Meta-heuristic Approach. 464-474
Hate Speech and Offensive Content Identification in English and Indo-Aryan Languages (HASOC)
- Sandip Modha, Thomas Mandl, Prasenjit Majumder, Shrey Satapara, Tithi Patel, Hiren Madhu:
Overview of the HASOC Subtrack at FIRE 2022: Identification of Conversational Hate-Speech in Hindi-English Code-Mixed and German Language. 475-488 - Tharindu Ranasinghe, Kai North, Damith Premasiri, Marcos Zampieri:
Overview of the HASOC Subtrack at FIRE 2022: Offensive Language Identification in Marathi. 489-501 - Supriya Chanda, Sacchit D. Sheth, Sukomal Pal:
Coarse and Fine-Grained Conversational Hate Speech and Offensive Content Identification in Code-Mixed Languages using Fine-Tuned Multilingual Embedding. 502-512 - Neeraj Kumar Singh, Utpal Garain:
An Analysis of Transformer-based Models for Code-mixed Conversational Hate-speech Identification. 513-521 - Tanmay Chavan, Shantanu Patankar, Aditya Kane, Omkar Gokhale, Raviraj Joshi:
A Twitter BERT Approach for Offensive Language Detection in Marathi. 522-528 - Dikshitha Vani V, B. Bharathi:
Hate Speech and Offensive Content Identification in Multiple Languages using machine learning algorithms. 529-541 - Gunjan Kumar, Jyoti Prakash Singh:
Hate Speech and Offensive Content Identification in English and Indo-Aryan Languages using Machine Learning Models. 542-551 - Maria Luisa Ripoll, Fadi Hassan, Joseph Attieh, Guillem Collell, Abdessalam Bouchekif:
Multi-Lingual Contextual Hate Speech Detection Using Transformer-Based Ensembles. 552-562 - Koyel Ghosh, Apurbalal Senapati, Utpal Garain:
Baseline BERT models for Conversational Hate Speech Detection in Code-mixed tweets utilizing Data Augmentation and Offensive Language Identification in Marathi. 563-574 - Kirti Kumari, Jyoti Prakash Singh:
Machine Learning Approach for Hate Speech and Offensive Content Identification in English and Indo Aryan Code-Mixed Languages. 575-583 - Yves Bestgen:
Confirming the Effectiveness of a Simple Language-Agnostic Yet Very Strong System for Hate Speech and Offensive Content Identification. 584-589 - Tebo Leburu-Dingalo, Karabo Johannes Ntwaagae, Nkwebi Peace Motlogelwa, Edwin Thuma, Monkgogi Mudongo:
Application of XLM-RoBERTa for Multi-Class Classification of Conversational Hate Speech. 590-595 - Sakshi Kalra, Kushank Maheshwari, Saransh Goel, Yashvardhan Sharma:
Hate Speech Detection in Marathi and Code-Mixed Languages using TF-IDF and Transformers-Based BERT-Variants. 596-610 - Haoyang Chen, Zhongyuan Han, Leilei Kong, Zhijie Zhang, Zengyao Li, Mingcan Guo, Haoliang Qi:
Mixture Models based on BERT for Hate Speech Detection. 611-616
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