Papers
TECHSSN at SemEval-2019 Task 6: Identifying and Categorizing Offensive Language in Tweets using Deep Neural Networks
Logesh Balasubramanian, Harshini Sathish Kumar, Geetika Bandlamudi et al.
Stop PropagHate at SemEval-2019 Tasks 5 and 6: Are abusive language classification results reproducible?
Paula Fortuna, Juan Soler-Company, Sérgio Nunes
SSN_NLP at SemEval-2019 Task 6: Offensive Language Identification in Social Media using Traditional and Deep Machine Learning Approaches
Thenmozhi D., Senthil Kumar B., Srinethe Sharavanan et al.
SINAI at SemEval-2019 Task 6: Incorporating lexicon knowledge into SVM learning to identify and categorize offensive language in social media
Flor Miriam Plaza-del-Arco, M. Dolores Molina-González, Maite Martin et al.
nlpUP at SemEval-2019 Task 6: A Deep Neural Language Model for Offensive Language Detection
Jelena Mitrović, Bastian Birkeneder, Michael Granitzer
NLPR@SRPOL at SemEval-2019 Task 6 and Task 5: Linguistically enhanced deep learning offensive sentence classifier
Alessandro Seganti, Helena Sobol, Iryna Orlova et al.
NLP@UIOWA at SemEval-2019 Task 6: Classifying the Crass using Multi-windowed CNNs
Jonathan Rusert, Padmini Srinivasan
NIT_Agartala_NLP_Team at SemEval-2019 Task 6: An Ensemble Approach to Identifying and Categorizing Offensive Language in Twitter Social Media Corpora
Steve Durairaj Swamy, Anupam Jamatia, Björn Gambäck et al.
Nikolov-Radivchev at SemEval-2019 Task 6: Offensive Tweet Classification with BERT and Ensembles
Alex Nikolov, Victor Radivchev
MIDAS at SemEval-2019 Task 6: Identifying Offensive Posts and Targeted Offense from Twitter
Debanjan Mahata, Haimin Zhang, Karan Uppal et al.
LTL-UDE at SemEval-2019 Task 6: BERT and Two-Vote Classification for Categorizing Offensiveness
Piush Aggarwal, Tobias Horsmann, Michael Wojatzki et al.
LaSTUS/TALN at SemEval-2019 Task 6: Identification and Categorization of Offensive Language in Social Media with Attention-based Bi-LSTM model
Lutfiye Seda Mut Altin, Àlex Bravo Serrano, Horacio Saggion
KMI-Coling at SemEval-2019 Task 6: Exploring N-grams for Offensive Language detection
Priya Rani, Atul Kr. Ojha
JU_ETCE_17_21 at SemEval-2019 Task 6: Efficient Machine Learning and Neural Network Approaches for Identifying and Categorizing Offensive Language in Tweets
Preeti Mukherjee, Mainak Pal, Somnath Banerjee et al.
JTML at SemEval-2019 Task 6: Offensive Tweets Identification using Convolutional Neural Networks
Johnny Torres, Carmen Vaca
jhan014 at SemEval-2019 Task 6: Identifying and Categorizing Offensive Language in Social Media
Jiahui Han, Shengtan Wu, Xinyu Liu
JCTICOL at SemEval-2019 Task 6: Classifying Offensive Language in Social Media using Deep Learning Methods, Word/Character N-gram Features, and Preprocessing Methods
Yaakov HaCohen-Kerner, Ziv Ben-David, Gal Didi et al.
INGEOTEC at SemEval-2019 Task 5 and Task 6: A Genetic Programming Approach for Text Classification
Mario Graff, Sabino Miranda-Jiménez, Eric Tellez et al.
Hope at SemEval-2019 Task 6: Mining social media language to discover offensive language
Gabriel Florentin Patras, Diana Florina Lungu, Daniela Gifu et al.
HHU at SemEval-2019 Task 6: Context Does Matter - Tackling Offensive Language Identification and Categorization with ELMo
Alexander Oberstrass, Julia Romberg, Anke Stoll et al.
HAD-Tübingen at SemEval-2019 Task 6: Deep Learning Analysis of Offensive Language on Twitter: Identification and Categorization
Himanshu Bansal, Daniel Nagel, Anita Soloveva
Ghmerti at SemEval-2019 Task 6: A Deep Word- and Character-based Approach to Offensive Language Identification
Ehsan Doostmohammadi, Hossein Sameti, Ali Saffar