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FIRE 2021: Virtual Event / Gandhinagar, India - Working Notes
- Parth Mehta, Thomas Mandl, Prasenjit Majumder, Mandar Mitra:
Working Notes of FIRE 2021 - Forum for Information Retrieval Evaluation, Gandhinagar, India, December 13-17, 2021. CEUR Workshop Proceedings 3159, CEUR-WS.org 2022 - Preface.
Hate Speech and Offensive Content Detection (HASOC)
- Thomas Mandl, Sandip Modha, Gautam Kishore Shahi, Hiren Madhu, Shrey Satapara, Prasenjit Majumder, Johannes Schäfer, Tharindu Ranasinghe, Marcos Zampieri, Durgesh Nandini, Amit Kumar Jaiswal:
Overview of the HASOC Subtrack at FIRE 2021: HateSpeech and Offensive Content Identification in English and Indo-Aryan Languages. 1-19 - Shrey Satapara, Sandip Modha, Thomas Mandl, Hiren Madhu, Prasenjit Majumder:
Overview of the HASOC Subtrack at FIRE 2021: Conversational Hate Speech Detection in Code-mixed language. 20-31 - Somnath Banerjee, Maulindu Sarkar, Nancy Agrawal, Punyajoy Saha, Mithun Das:
Exploring Transformer Based Models to Identify Hate Speech and Offensive Content in English and Indo-Aryan Languages. 32-43 - Necva Bölücü, Pelin Canbay:
Hate Speech and Offensive Content Identification with Graph Convolutional Networks. 44-51 - Anna Glazkova, Michael Kadantsev, Maksim Glazkov:
Fine-tuning of Pre-trained Transformers for Hate Offensive and Profane Content Detection in English and Marathi. 52-62 - Zaki Mustafa Farooqi, Sreyan Ghosh, Rajiv Ratn Shah:
Leveraging Transformers for Hate Speech Detection in Conversational Code-Mixed Tweets. 63-74 - Camilo Caparrós-Laiz, José Antonio García-Díaz, Rafael Valencia-García:
Detecting Hate Speech on English and Indo-Aryan Languages with BERT and Ensemble learning. 75-81 - Yves Bestgen:
A Simple Language-Agnostic yet Strong Baseline System for Hate Speech and Offensive Content Identification. 82-91 - Kalaivani Adaikkan, Thenmozhi Durairaj:
Multilingual Hate Speech and Offensive Language Detection in English Hindi and Marathi languages. 92-103 - Ritesh Kumar, Vishesh Gupta, Rajendra Pamula:
Hate Speech and Offensive Content Identification in English Tweets. 104-109 - Purva Mankar, Akshaya Gangurde, Deptii Chaudhari, Ambika Pawar:
Machine Learning Models for Hate Speech and Offensive Language Identification for Indo-Aryan Language: Hindi. 110-120 - Sourav Das, Prasanta Mandal, Sanjay Chatterji:
Probabilistic Impact Score Generation using Ktrain-BERT to Identify Hate Words from Twitter Discussions. 121-131 - Asha Hegde, Mudoor Devadas Anusha, Hosahalli Lakshmaiah Shashirekha:
Ensemble Based Machine Learning Models for Hate Speech and Offensive Content Identification. 132-141 - Swetha Saseendran, Sudharshan R, Sreedhar V, Sharan Giri:
Classification of Hate Speech and Offensive Content using an approach based on DistilBERT. 142-153 - Yifan Xu, Hui Ning, Yutong Sun:
Hate Speech and Offensive Content Identification Based on Self-Attention. 154-160 - Aditya Kadam, Anmol Goel, Jivitesh Jain, Jushaan Singh Kalra, Mallika Subramanian, Manvith Reddy, Prashant Kodali, T. H. Arjun, Manish Shrivastava, Ponnurangam Kumaraguru:
Battling Hateful Content in Indic Languages HASOC'21. 161-172 - Salar Mohtaj, Vera Schmitt, Sebastian Möller:
A Feature Extraction Based Model for Hate Speech Identification. 173-181 - Krishanu Maity, Abhishek Kumar, Sriparna Saha:
Attention Based BERT-FastText Model for Hate Speech and Offensive Content Identification in English and Hindi Languages. 182-190 - Yongyi Kui:
Detect Hate and Offensive Content in English and Indo-Aryan Languages based on Transformer. 191-199 - Sakshi Kalra, Kalit Naresh Inani, Yashvardhan Sharma, Gajendra Singh Chauhan:
Applying Transfer Learning using BERT-Based Models for Hate Speech Detection. 200-208 - Sudharsana Kannan, Jelena Mitrovic:
Hatespeech and Offensive Content Detection in Hindi Language using C-BiGRU. 209-216 - Ravindra Nayak, Raviraj Joshi:
Contextual Hate Speech Detection in Code Mixed Text using Transformer Based Approaches. 217-225 - Md Saroar Jahan, Mourad Oussalah, Jhuma Kabir Mim, Mominul Islam:
Offensive Language Identification Using Hindi-English Code-Mixed Tweets and Code-Mixed Data Augmentation. 226-238 - Abhishek Velankar, Hrushikesh Patil, Amol Gore, Shubham Salunke, Raviraj Joshi:
Hate and Offensive Speech Detection in Hindi and Marathi. 239-247 - Nkwebi Peace Motlogelwa, Edwin Thuma, Monkgogi Mudongo, Tebo Leburu-Dingalo, Gontlafetse Mosweunyane:
Leveraging Text Generated from Emojis for Hate Speech and Offensive Content Identification. 248-253 - Jun Zeng, Li Xu, Hao Wu:
ALBERT for Hate Speech and Offensive Content Identification. 254-261 - Md Saroar Jahan, Djamila Romaissa Beddiar, Mourad Oussalah, Nabil Arhab, Yazid Bounab:
Hate and Offensive Language Detection using BERT for English Subtask A. 262-272 - Mayuresh Nene, Kai North, Tharindu Ranasinghe, Marcos Zampieri:
Transformer Models for Offensive Language Identification in Marathi. 273-282 - Kinga Gémes
, Ádám Kovács, Markus Reichel, Gábor Recski:
Offensive Text Detection on English Twitter with Deep Learning Models and Rule-Based Systems. 283-296 - Flor Miriam Plaza del Arco, Sercan Halat, Sebastian Padó, Roman Klinger:
Multi-Task Learning with Sentiment Emotion and Target Detection to Recognize Hate Speech and Offensive Language. 297-318 - Wentao Yu, Benedikt T. Boenninghoff, Dorothea Kolossa:
Hybrid Representation Fusion for Twitter Hate Speech Identification. 319-329 - Shikha Mundra, Nikhil Singh, Namita Mittal:
Fine-tune BERT to Classify Hate Speech in Hindi English Code-Mixed Text. 330-337 - Ishali Jadhav, Aditi Kanade, Vishesh Waghmare, Deptii Chaudhari:
Hate and Offensive Speech Detection in Hindi Twitter Corpus. 338-348 - Arka Mitra, Priyanshu Sankhala:
Multilingual Hate Speech and Offensive Content Detection using Modified Cross-entropy Loss. 349-356 - Rodrigo Souza Wilkens, Dimitri Ognibene:
biCourage: ngram and syntax GCNs for Hate Speech detection. 357-366 - Palash Nandi, Dipankar Das:
Detection of Hate or Offensive Phrase using Magnified Tf-Idf. 367-378 - Disha Gajbhiye, Swapnil Deshpande, Prerna Ghante, Abhijeet Kale, Deptii Chaudhari:
Machine Learning Models for Hate Speech Identification in Marathi Language. 379-386 - Suyash Sangwan, Lipika Dey, Mohammad Shakir:
Gated Multi-task learning framework for text classification. 387-395 - Deepakindresh N, Rohan Avireddy, Aakash Ambalavanan, B. Radhika Selvamani:
Hate Speech Detection using LIME guided Ensemble Method and DistilBERT. 396-411 - Sherzod Hakimov, Ralph Ewerth:
Combining Textual Features for the Detection of Hateful and Offensive Language. 412-418 - Mehar Bhatia, Tenzin Singhay Bhotia, Akshat Agarwal, Prakash Ramesh, Shubham Gupta, Kumar Shridhar, Felix Laumann, Ayushman Dash:
One to Rule Them All: Towards Joint Indic Language Hate Speech Detection. 419-431 - Anirudh Anand, Jeet Golecha, Bharathi B, Bhuvana Jayaraman, Mirnalinee T. T:
Machine Learning Based Hate Speech Identification for English and Indo-Aryan Languages. 432-438 - Abhinav Kumar, Pradeep Kumar Roy, Sunil Saumya:
An Ensemble Approach for Hate and Offensive Language Identification in English and Indo-Aryan Languages. 439-445 - Supriya Chanda, S. Ujjwal, Shayak Das, Sukomal Pal:
Fine-tuning Pre-Trained Transformer based model for Hate Speech and Offensive Content Identification in English Indo-Aryan and Code-Mixed (English-Hindi) languages. 446-458 - Shyam Ratan, Sonal Sinha, Siddharth Singh:
SVM for Hate Speech and Offensive Content Detection. 459-466 - Ratnavel Rajalakshmi, Faerie Mattins, Srivarshan S, Preethi Reddy, M. Anand Kumar:
Hate Speech and Offensive Content Identification in Hindi and Marathi Language Tweets using Ensemble Techniques. 467-479 - Ratnavel Rajalakshmi, Srivarshan S, Faerie Mattins, Kaarthik E, Prithvi Seshadri, M. Anand Kumar:
Conversational Hate-Speech detection in Code-Mixed Hindi-English Tweets. 480-490 - Basavraj Chinagundi, Muskaan Singh, Tirthankar Ghosal, Prashant Singh Rana, Guneet Singh Kohli:
Classification of Hate Offensive and Profane content from Tweets using an Ensemble of Deep Contextualized and Domain Specific Representations. 491-500 - Yaakov HaCohen-Kerner, Moshe Uzan:
Detecting Offensive Language in English Hindi and Marathi using Classical Supervised Machine Learning Methods and Word/Char N-grams. 501-507 - Surya Agustian, Reski Saputra, Aidil Fadhilah:
Feature Selection with Pretrained-BERT for Hate Speech and Offensive Content Identification in English and Hindi Languages. 508-516
Artificial Intelligence for Legal Assistance (AILA)
- Vedant Parikh, Upal Bhattacharya, Parth Mehta, Ayan Bandyopadhyay, Paheli Bhattacharya, Kripabandhu Ghosh, Saptarshi Ghosh, Arindam Pal, Arnab Bhattacharya, Prasenjit Majumder:
Overview of the Third Shared Task on Artificial Intelligence for Legal Assistance at FIRE 2021. 517-526 - Sourav Dutta:
Categorizing Roles of Legal Texts via Sequence Tagging on Domain-Specific Language Models. 527-533 - Deepthi Sudharsan, Asmitha U, Premjith B, Soman K. P:
DistilRoBERTa Based Sentence Embedding for Rhetorical Role Labelling of Legal Case Documents. 534-540 - Shaz Furniturewala, Racchit Jain, Vijay Kumari, Yashvardhan Sharma:
Legal Text Classification and Summarization using Transformers and Joint Text Features. 541-546 - Arka Mitra:
Classification on Sentence Embeddings for LegalAssistance. 547-552 - Deepali Jain, Malaya Dutta Borah, Anupam Biswas:
Summarization of Indian Legal Judgement Documents via Ensembling of Contextual Embedding based MLP Models. 553-561 - Sai Shridhar Balamurali, Kayalvizhi S, Thenmozhi D:
Simple Transformers in Rhetoric Role Labelling for Legal Judgements. 562-567 - Siddhartha Rusiya, Aditya Sharma, Debajyoti Debbarma, Samarjit Debbarma:
Rhetorical Role Labelling for Legal Judgements and Legal Document Summarization. 568-574 - Tebo Leburu-Dingalo, Edwin Thuma, Gontlafetse Mosweunyane, Nkwebi Peace Motlogelwa:
Rhetorical Role Labelling for Legal Judgements using fastText Classifier. 575-580 - Guneet Singh Kohli, Prabsimran Kaur, Jatin Bedi:
Automatic Detection of Rhetorical Role Labels using ERNIE2.0 and RoBERTa. 581-588
Offensive Language Identification for Dravidian Languages in Code-Mixed Text
- Bharathi Raja Chakravarthi, Prasanna Kumar Kumaresan, Ratnasingam Sakuntharaj, Anand Kumar Madasamy, Sajeetha Thavareesan, B. Premjith, Sreelakshmi K, Subalalitha Chinnaudayar Navaneethakrishnan, John P. McCrae, Thomas Mandl:
Overview of the HASOC-DravidianCodeMix Shared Task on Offensive Language Detection in Tamil and Malayalam. 589-602 - Fazlourrahman Balouchzahi, S. Bashang, Grigori Sidorov, H. L. Shashirekha:
CoMaTa OLI- Code-Mixed Malayalam and Tamil Offensive Language Identification. 603-614 - Snehaan Bhawal, Pradeep Roy, Abhinav Kumar:
Hate Speech and Offensive Language Identification on Multilingual Code Mixed Text using BERT. 615-624 - Pawan Kalyan Jada, Konthala Yasaswini, Karthik Puranik, Anbukkarasi Sampath, Sathiyaraj Thangasamy, Kingston Pal Thamburaj:
Analyzing Social Media Content for Detection of Offensive Text. 625-635 - Anu Priya, Abhinav Kumar:
Hate and Offensive Content Identification from Dravidian Social Media Posts: A Deep Learning Approach. 636-642 - Jyoti Kumari, Abhinav Kumar:
Offensive Language Identification on Multilingual Code Mixing Text. 643-650 - Divya S, Sripriya N:
Transformer Based Model For Offensive Content Recognition In Dravidian Languages. 651-658 - Sean Benhur, Kanchana Sivanraju:
Pretrained Transformers for Offensive Language Identification in Tanglish. 659-666 - Kalaivani Adaikkan, Thenmozhi Durairaj, Aravindan Chandrabose:
TOLD: Tamil Offensive Language Detection in Code-Mixed Social Media Comments using MBERT with Features based Selection. 667-679 - Shankar Biradar, Sunil Saumya, Arun Chauhan:
mBERT Based Model for Identification of Offensive Content in South Indian Languages. 680-687 - Bhuvana Jayaraman, Mirnalinee T. T, Karthik Raja Anandan, Aarthi Suresh Kumar, Anirudh Anand:
Offensive Text Prediction using Machine Learning and Deep Learning Approaches. 688-695 - B. S. N. V. Chaitanya, Karri Anjali:
Transformer Ensemble System for Detection of Offensive Content in Dravidian Languages. 696-704 - Jerin Mahibha C, Kayalvizhi Sampath, Durairaj Thenmozhi, Arunima S.:
Offensive Language Identification using Machine Learning and Deep Learning Techniques. 705-713 - Suchismita Tripathy, Ameya Pathak, Yashvardhan Sharma:
Offensive Language Classification of Code-Mixed Tamil with Keras. 714-719 - Malliga Subramanian, Shanmuga Vadivel Kogilavani, Antonette Shibani, Adhithiya G. J, Deepti Ravi, Gowthamkrishnan S:
Detection Offensive Tamil Texts using Machine Learning and Multilingual Transformers Models. 720-728 - R. Ramesh Kannan, Ratnavel Rajalakshmi, Lokesh Kumar:
IndicBERT Based Approach for Sentiment Analysis on Code-Mixed Tamil Tweets. 729-736 - Abhishek Kumar Gautam, Bharathi B:
RNN's VS TRANSFORMERS: Training Language Models on Deficit Datasets. 737-743
Abusive and Threatening Language Detection Task in Urdu
- Maaz Amjad, Alisa Zhila, Grigori Sidorov, Andrey Labunets, Sabur Butt, Hamza Imam Amjad, Oxana Vitman, Alexander F. Gelbukh:
Overview of Abusive and Threatening Language Detection in Urdu at FIRE 2021. 744-762 - Muhammad Humayoun:
Abusive and Threatening Language Detection in Urdu using Supervised Machine Learning and Feature Combinations. 763-773 - Muhammad Owais Raza, Qaisar Khan, Ghulam Muhammad Soomro:
Urdu Abusive Language Detection using Machine Learning. 774-783 - Abhinav Kumar, Sunil Saumya, Pradeep Kumar Roy:
Abusive and Threatening Language Detection from Urdu Social Media Posts: A machine learning approach. 784-790 - Mithun Das, Somnath Banerjee, Punyajoy Saha:
Abusive and Threatening Language Detection in Urdu using Boosting Based and BERT Based Models: A Comparative Approach. 791-798 - Sakshi Kalra, Yash Bansal, Yashvardhan Sharma:
Detection of Abusive Records by Analyzing the Tweets in Urdu Language Exploring Transformer Based Models. 799-805 - K. A. Karthikraja, Aarthi Suresh Kumar, B. Bharathi, Jayaraman Bhuvana, T. T. Mirnalinee:
Abusive and Threatening Language Detection in Native Urdu Script Tweets Exploring Four Conventional Machine Learning Techniques and MLP. 806-812 - Sakshi Kalra, Mehul Agrawal, Yashvardhan Sharma:
Detection of Threat Records by Analyzing the Tweets in Urdu Language Exploring Deep Learning Transformer - Based Models. 813-819
Arabic Misogyny Identification (ArMI)
- Hala Mulki, Bilal Ghanem:
ArMI at FIRE 2021: Overview of the First Shared Task on Arabic Misogyny Identification. 820-830 - Abhinav Kumar, Pradeep Kumar Roy, Jyoti Prakash Singh:
A Deep Learning Approach for Identification of Arabic Misogyny from Tweets. 831-838 - Fazlourrahman Balouchzahi, Grigori Sidorov, Hosahalli Lakshmaiah Shashirekha:
Arabic Misogyny Identification. 839-846 - Istabrak Abbes, Eya Nakache, Moez BenHajhmida:
Context-aware Language Modeling for Arabic Misogyny Identification. 847-851 - Abdelkader El Mahdaouy, Abdellah El Mekki, Ahmed Oumar, Hajar Mousannif, Ismail Berrada:
Deep Multi-Task Models for Misogyny Identification and Categorization on Arabic Social Media. 852-860 - Abdusalam Nwesri, Stephen Wu, Harmain Harmain:
Detecting Misogyny in Arabic Tweets. 861-866 - Abir Messaoudi, Chayma Fourati, Mayssa Kchaou, Hatem Haddad:
iCompass Working Notes for Arabic Misogyny Identification. 867-871
Sentiment Analysis of Dravidian Languages in Code-Mixed Text
- Bharathi Raja Chakravarthi, Ruba Priyadharshini, Sajeetha Thavareesan, Dhivya Chinnappa, Durairaj Thenmozhi, Elizabeth Sherly, John P. McCrae, Adeep Hande, Rahul Ponnusamy, Shubhanker Banerjee, Charangan Vasantharajan:
Findings of the Sentiment Analysis of Dravidian Languages in Code-Mixed Text. 872-886 - Fazlourrahman Balouchzahi, Hosahalli Lakshmaiah Shashirekha, Grigori Sidorov:
CoSaD- Code-Mixed Sentiments Analysis for Dravidian Languages. 887-898 - Rashmi K. B., Guruprasad H. S., Shambhavi B. R:
Sentiment Classification on Bilingual Code-Mixed Texts for Dravidian Languages using Machine Learning Methods. 899-907 - Satyam Dutta, Himanshi Agrawal, Pradeep Kumar Roy:
Sentiment Analysis on Multilingual Code-Mixed Kannada Language. 908-918 - Yang Bai
Automatic Detecting the Sentiment of Code-Mixed Text by Pre-training Model. 919-925 - Pawan Kalyan Jada, D. Sashidhar Reddy, Konthala Yasaswini, Arunaggiri Pandian K, Prabakaran Chandran, Anbukkarasi Sampath, Sathiyaraj Thangasamy:
Transformer based Sentiment Analysis in Dravidian Languages. 926-938 - Karthik Puranik, Bharathi B, Senthil Kumar B:
Transliterate or Translate? Sentiment Analysis of Code-Mixed Text in Dravidian Languages. 939-949 - Abhinav Kumar, Sunil Saumya, Jyoti Prakash Singh:
An Ensemble-Based Model for Sentiment Analysis of Dravidian Code-Mixed Social Media Posts. 950-958 - Jyoti Kumari, Abhinav Kumar:
A Deep Neural Network-based Model for the Sentiment Analysis of Dravidian Code-mixed Social Media Posts. 959-966 - Dhanasekaran Prasannakumaran, Jappeswaran Balasubramanian Sideshwar, Durairaj Thenmozhi:
ECMAG - Ensemble of CNN and Multi-Head Attention with Bi-GRU for Sentiment Analysis in Code-Mixed Data. 967-975 - Prabhu Ram. N, Meeradevi T, Vibin Mammen Vinod, Gothainayaki A, Anusha S, Agalya T:
Comparative Analysis for Offensive Language Identification of Tamil Text using SVM and Logistic Classifier. 976-983 - Prasad A. Joshi, Varsha M. Pathak:
Sentiment Analysis on Code-mixed Dravidian Languages A Non-Linguistic Approach. 984-995 - Mudoor Devadas Anusha, Hosahalli Lakshmaiah Shashirekha:
BiLSTM-Sentiments Analysis in Code Mixed Dravidian Languages. 996-1004 - N. Sripriya, S. Divya:
Sentiment Analysis Model For Code-Mixed Tamil Language. 1005-1010 - Ankit Kumar Mishra, Sunil Saumya, Abhinav Kumar:
Sentiment Analysis of Dravidian-CodeMix Language. 1011-1019 - Kalaivani Adaikkan, Durairaj Thenmozhi:
Multilingual Sentiment Analysis in Tamil Malayalam and Kannada code-mixed social media posts using MBERT. 1020-1028 - Pavan Kumar P. H. V, Premjith B, Sanjanasri J. P., Soman K. P:
Deep Learning Based Sentiment analysis for MalayalamTamil and Kannada languages. 1029-1037 - B. Bharathi, G. U. Samyuktha:
Machine Learning Based Approach for Sentiment Analysis on Multilingual Code Mixing Text. 1038-1043 - Pradeep Kumar Roy, Abhinav Kumar:
Sentiment Analysis on Tamil Code-Mixed Text using Bi-LSTM. 1044-1050 - Supriya Chanda, Rajat Pratap Singh, Sukomal Pal:
Is Meta Embedding Better than Pre-Trained Word Embedding to Perform Sentiment Analysis for Dravidian Languages in Code-Mixed Text? 1051-1060 - K. Nimmi, B. Janet:
Voting Ensemble Model Based Malayalam-English Sentiment Analysis on Code-Mixed Data. 1061-1068 - Yandrapati Prakash Babu, Eswari Rajagopal:
Sentiment Analysis on Dravidian Code-Mixed YouTube Comments using Paraphrase XLM-RoBERTa Model. 1069-1076 - Sanjeepan Sivapiran, Charangan Vasantharajan, Uthayasanker Thayasivam:
Sentiment Analysis in Dravidian Code-Mixed YouTube Comments and Posts. 1077-1084 - S. R. Mithun Kumar, Nihal Reddy, Aruna Malapati, Lov Kumar:
An Ensemble Model for Sentiment Classification on Code-Mixed Data in Dravidian Languages. 1085-1093 - Jerin Mahibha C, Kayalvizhi Sampath, Durairaj Thenmozhi:
Sentiment Analysis using Cross Lingual Word Embedding Model. 1094-1100
Fake News Detection in the Urdu Language (UrduFake)
- Maaz Amjad, Sabur Butt, Hamza Imam Amjad, Alisa Zhila, Grigori Sidorov, Alexander F. Gelbukh:
Overview of the Shared Task on Fake News Detection in Urdu at FIRE 2021. 1101-1116 - Fazlourrahman Balouchzahi, Hosahalli Lakshmaiah Shashirekha, Grigori Sidorov:
Ensembled Feature Selection for Urdu Fake News Detection. 1117-1126 - Iqra Ameer, Claudia Porto Capetillo, Helena Gómez-Adorno, Grigori Sidorov:
Automatic Fake News Detection in Urdu Language using Transformers. 1127-1134 - Muhammad Abdullah Ilyas, Khurram Shahzad:
Urdu Fake News Detection using TF-IDF Features and TextCNN. 1135-1141 - Hammad Akram, Khurram Shahzad:
Ensembling Machine Learning Models for Urdu Fake News Detection. 1142-1149 - Hamada Nayel, Ghada Amer:
A Simple N-Gram Model for Urdu Fake News Detection. 1150-1155 - Muhammad Humayoun:
The 2021 Urdu Fake News Detection Task using Supervised Machine Learning and Feature Combinations. 1156-1161 - Yaakov HaCohen-Kerner, Natan Manor, Netanel Bashan, Elyasaf Dimant:
Detecting Fake News in URDU using Classical Supervised Machine Learning Methods and Word/Char N-grams. 1162-1167 - Abhinav Kumar, Jyoti Kumari:
A Machine Learning Approach for Fake News Detection from Urdu Social Media Posts. 1168-1174 - Sakshi Kalraa, Preetika Vermaa, Yashvardhan Sharma, Gajendra Singh Chauhan:
Ensembling of Various Transformer Based Models for the Fake News Detection Task in the Urdu Language. 1175-1181 - Snehaan Bhawal, Pradeep Kumar Roy:
Fake News Detection in Urdu Language using BERT. 1182-1189 - Asha Hegde, Hosahalli Lakshmaiah Shashirekha:
Urdu Fake News Detection Using Ensemble of Machine Learning Models. 1190-1198
Information Retrieval from Microblogs during Disasters (IRMiDis)
- Shivangi Bithel, Samidha Verma:
VaccineBERT: BERT for COVID-19 Vaccine Tweet Classification. 1199-1203 - Sumit Anand, Mehuly Chakraborthy, Diptaraj Sen:
Identifying Situational Information during Mass Emergency. 1204-1209 - Meghna Chakraborty, Sk. Aftab Aman:
COVID Vaccine Stance Classification. 1210-1215 - Abhinav Kumar, Pradeep Kumar Roy, Jyoti Prakash Singh:
Bidirectional Encoder Representations from Transformers for the COVID-19 vaccine stance classification. 1216-1220 - Poulami Ghosh, Sayani Ghosh:
Analyzing COVID-19 Vaccination. 1221-1226 - Aayush Chowdhury, Aman Choudhary, Aishwarya Roy:
Retrieval of Actionable Information during Mass Emergency: A Classification Approach. 1227-1232
Causality-driven Ad hoc Information Retrieval (CAIR)
- Suchana Datta, Debasis Ganguly, Dwaipayan Roy, Derek Greene:
Overview of the Causality-driven Adhoc Information Retrieval (CAIR) task at FIRE-2021. 1233-1237 - Pankaj Dadure, Partha Pakray, Sivaji Bandyopadhyay:
Causal Document Retrieval: An Analytical Investigation. 1238-1245 - Dhairya Dalal, Sharmi Dev Gupta, Bentolhoda Binaei:
A Semantic Search Pipeline for Causality-driven Adhoc Information Retrieval. 1246-1254
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