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ORCID13th SemEval@NAACL-HLT 2019: Minneapolis, MN, USA
- Jonathan May, Ekaterina Shutova, Aurélie Herbelot, Xiaodan Zhu, Marianna Apidianaki, Saif M. Mohammad:
Proceedings of the 13th International Workshop on Semantic Evaluation, SemEval@NAACL-HLT 2019, Minneapolis, MN, USA, June 6-7, 2019. Association for Computational Linguistics 2019, ISBN 978-1-950737-06-2 - Daniel Hershcovich, Zohar Aizenbud, Leshem Choshen, Elior Sulem, Ari Rappoport, Omri Abend
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SemEval-2019 Task 1: Cross-lingual Semantic Parsing with UCCA. 1-10 - Wei Jiang, Zhenghua Li, Yu Zhang, Min Zhang:
HLT@SUDA at SemEval-2019 Task 1: UCCA Graph Parsing as Constituent Tree Parsing. 11-15 - Behrang QasemiZadeh, Miriam R. L. Petruck, Regina Stodden, Laura Kallmeyer, Marie Candito:
SemEval-2019 Task 2: Unsupervised Lexical Frame Induction. 16-30 - Nikolay Arefyev, Boris Sheludko, Adis Davletov, Dmitry Kharchev, Alex Nevidomsky, Alexander Panchenko:
Neural GRANNy at SemEval-2019 Task 2: A combined approach for better modeling of semantic relationships in semantic frame induction. 31-38 - Ankush Chatterjee, Kedhar Nath Narahari, Meghana Joshi, Puneet Agrawal:
SemEval-2019 Task 3: EmoContext Contextual Emotion Detection in Text. 39-48 - Chenyang Huang, Amine Trabelsi, Osmar R. Zaïane:
ANA at SemEval-2019 Task 3: Contextual Emotion detection in Conversations through hierarchical LSTMs and BERT. 49-53 - Valerio Basile, Cristina Bosco, Elisabetta Fersini, Debora Nozza, Viviana Patti, Francisco Manuel Rangel Pardo, Paolo Rosso, Manuela Sanguinetti:
SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter. 54-63 - Juan Manuel Pérez, Franco M. Luque:
Atalaya at SemEval 2019 Task 5: Robust Embeddings for Tweet Classification. 64-69 - Vijayasaradhi Indurthi, Bakhtiyar Syed, Manish Shrivastava, Nikhil Chakravartula, Manish Gupta, Vasudeva Varma:
FERMI at SemEval-2019 Task 5: Using Sentence embeddings to Identify Hate Speech Against Immigrants and Women in Twitter. 70-74 - Marcos Zampieri, Shervin Malmasi, Preslav Nakov, Sara Rosenthal, Noura Farra, Ritesh Kumar:
SemEval-2019 Task 6: Identifying and Categorizing Offensive Language in Social Media (OffensEval). 75-86 - Ping Liu, Wen Li, Liang Zou:
NULI at SemEval-2019 Task 6: Transfer Learning for Offensive Language Detection using Bidirectional Transformers. 87-91 - Weimin Lyu, Sheng Huang, Abdul Rafae Khan, Shengqiang Zhang, Weiwei Sun, Jia Xu:
CUNY-PKU Parser at SemEval-2019 Task 1: Cross-Lingual Semantic Parsing with UCCA. 92-96 - Dang Tuan Nguyen, Trung Tran:
DANGNT@UIT.VNU-HCM at SemEval 2019 Task 1: Graph Transformation System from Stanford Basic Dependencies to Universal Conceptual Cognitive Annotation (UCCA). 97-101 - Shiva Taslimipoor, Omid Rohanian, Sara Moze:
GCN-Sem at SemEval-2019 Task 1: Semantic Parsing using Graph Convolutional and Recurrent Neural Networks. 102-106 - Gabriel Marzinotto, Johannes Heinecke, Géraldine Damnati:
MaskParse@Deskin at SemEval-2019 Task 1: Cross-lingual UCCA Semantic Parsing using Recursive Masked Sequence Tagging. 107-112 - Tobias Pütz, Kevin Glocker:
Tüpa at SemEval-2019 Task1: (Almost) feature-free Semantic Parsing. 113-118 - Dian Yu, Kenji Sagae:
UC Davis at SemEval-2019 Task 1: DAG Semantic Parsing with Attention-based Decoder. 119-124 - Saba Anwar, Dmitry Ustalov, Nikolay Arefyev, Simone Paolo Ponzetto, Chris Biemann, Alexander Panchenko:
HHMM at SemEval-2019 Task 2: Unsupervised Frame Induction using Contextualized Word Embeddings. 125-129 - Eugénio Ribeiro, Vânia Mendonça, Ricardo Ribeiro, David Martins de Matos, Alberto Sardinha, Ana Lúcia Santos, Luísa Coheur:
L2F/INESC-ID at SemEval-2019 Task 2: Unsupervised Lexical Semantic Frame Induction using Contextualized Word Representations. 130-136 - Vachagan Gratian:
BrainEE at SemEval-2019 Task 3: Ensembling Linear Classifiers for Emotion Prediction. 137-141 - Genta Indra Winata, Andrea Madotto, Zhaojiang Lin, Jamin Shin, Yan Xu, Peng Xu, Pascale Fung:
CAiRE_HKUST at SemEval-2019 Task 3: Hierarchical Attention for Dialogue Emotion Classification. 142-147 - Yves Bestgen:
CECL at SemEval-2019 Task 3: Using Surface Learning for Detecting Emotion in Textual Conversations. 148-152 - Elham Mohammadi, Hessam Amini, Leila Kosseim:
CLaC Lab at SemEval-2019 Task 3: Contextual Emotion Detection Using a Combination of Neural Networks and SVM. 153-158 - Joseph Cummings, Jason R. Wilson:
CLARK at SemEval-2019 Task 3: Exploring the Role of Context to Identify Emotion in a Short Conversation. 159-163 - Changjie Li, Yun Xing:
CLP at SemEval-2019 Task 3: Multi-Encoder in Hierarchical Attention Networks for Contextual Emotion Detection. 164-168 - Ana Valeria González-Garduño, Victor Petrén Bach Hansen, Joachim Bingel, Isabelle Augenstein, Anders Søgaard:
CoAStaL at SemEval-2019 Task 3: Affect Classification in Dialogue using Attentive BiLSTMs. 169-174 - Rafal Poswiata:
ConSSED at SemEval-2019 Task 3: Configurable Semantic and Sentiment Emotion Detector. 175-179 - Michal Perelkiewicz:
CX-ST-RNM at SemEval-2019 Task 3: Fusion of Recurrent Neural Networks Based on Contextualized and Static Word Representations for Contextual Emotion Detection. 180-184 - Akansha Jain, Ishita Aggarwal, Ankit Singh:
ParallelDots at SemEval-2019 Task 3: Domain Adaptation with feature embeddings for Contextual Emotion Analysis. 185-189 - Harsh Patel:
E-LSTM at SemEval-2019 Task 3: Semantic and Sentimental Features Retention for Emotion Detection in Text. 190-194 - José-Ángel González, Lluís-F. Hurtado, Ferran Pla:
ELiRF-UPV at SemEval-2019 Task 3: Snapshot Ensemble of Hierarchical Convolutional Neural Networks for Contextual Emotion Detection. 195-199 - Hani Al-Omari, Malak Abdullah, Nabeel Bassam:
EmoDet at SemEval-2019 Task 3: Emotion Detection in Text using Deep Learning. 200-204 - Nikhil Chakravartula, Vijayasaradhi Indurthi:
EMOMINER at SemEval-2019 Task 3: A Stacked BiLSTM Architecture for Contextual Emotion Detection in Text. 205-209 - Sergey Smetanin:
EmoSense at SemEval-2019 Task 3: Bidirectional LSTM Network for Contextual Emotion Detection in Textual Conversations. 210-214 - Abdessalam Bouchekif, Praveen Joshi, Latifa Bouchekif, Haithem Afli:
EPITA-ADAPT at SemEval-2019 Task 3: Detecting emotions in textual conversations using deep learning models combination. 215-219 - Joan Xiao:
Figure Eight at SemEval-2019 Task 3: Ensemble of Transfer Learning Methods for Contextual Emotion Detection. 220-224 - Bogdan Dumitru:
GenSMT at SemEval-2019 Task 3: Contextual Emotion Detection in tweets using multi task generic approach. 225-229 - Shabnam Tafreshi, Mona T. Diab:
GWU NLP Lab at SemEval-2019 Task 3 : EmoContext: Effectiveness ofContextual Information in Models for Emotion Detection inSentence-level at Multi-genre Corpus. 230-235 - Arik Pamnani, Rajat Goel, Jayesh Choudhari, Mayank Singh:
IIT Gandhinagar at SemEval-2019 Task 3: Contextual Emotion Detection Using Deep Learning. 236-240 - Jasabanta Patro, Nitin Choudhary, Kalpit Chittora, Animesh Mukherjee:
KGPChamps at SemEval-2019 Task 3: A deep learning approach to detect emotions in the dialog utterances. 241-246 - Nourah Alswaidan, Mohamed El Bachir Menai:
KSU at SemEval-2019 Task 3: Hybrid Features for Emotion Recognition in Textual Conversation. 247-250 - Waleed Ragheb, Jérôme Azé, Sandra Bringay, Maximilien Servajean:
LIRMM-Advanse at SemEval-2019 Task 3: Attentive Conversation Modeling for Emotion Detection and Classification. 251-255 - Yoonhyung Lee, Yanghoon Kim, Kyomin Jung:
MILAB at SemEval-2019 Task 3: Multi-View Turn-by-Turn Model for Context-Aware Sentiment Analysis. 256-260 - Chandrakant Bothe, Stefan Wermter:
MoonGrad at SemEval-2019 Task 3: Ensemble BiRNNs for Contextual Emotion Detection in Dialogues. 261-265 - Parag Agrawal, Anshuman Suri:
NELEC at SemEval-2019 Task 3: Think Twice Before Going Deep. 266-271 - Michal Farkas, Peter Lacko:
NL-FIIT at SemEval-2019 Task 3: Emotion Detection From Conversational Triplets Using Hierarchical Encoders. 272-276 - Rolandos Alexandros Potamias, Georgios Siolas:
NTUA-ISLab at SemEval-2019 Task 3: Determining emotions in contextual conversations with deep learning. 277-281 - Peixiang Zhong, Chunyan Miao:
ntuer at SemEval-2019 Task 3: Emotion Classification with Word and Sentence Representations in RCNN. 282-286 - Luyao Ma, Long Zhang, Wei Ye, Wenhui Hu:
PKUSE at SemEval-2019 Task 3: Emotion Detection with Emotion-Oriented Neural Attention Network. 287-291 - Andrew Nguyen, Tobin South, Nigel G. Bean, Jonathan Tuke, Lewis Mitchell:
Podlab at SemEval-2019 Task 3: The Importance of Being Shallow. 292-296 - Zinedine Rebiai, Simon Andersen, Antoine Debrenne, Victor Lafargue:
SCIA at SemEval-2019 Task 3: Sentiment Analysis in Textual Conversations Using Deep Learning. 297-301 - Jacob Anderson:
Sentim at SemEval-2019 Task 3: Convolutional Neural Networks For Sentiment in Conversations. 302-306 - Flor Miriam Plaza del Arco, M. Dolores Molina-González, Maite Martín-Valdivia, Luis Alfonso Ureña López:
SINAI at SemEval-2019 Task 3: Using affective features for emotion classification in textual conversations. 307-311 - Sanghwan Bae, Jihun Choi, Sang-goo Lee:
SNU IDS at SemEval-2019 Task 3: Addressing Training-Test Class Distribution Mismatch in Conversational Classification. 312-317 - B. Senthil Kumar, D. Thenmozhi, Chandrabose Aravindan, Srinethe Sharavanan:
SSN_NLP at SemEval-2019 Task 3: Contextual Emotion Identification from Textual Conversation using Seq2Seq Deep Neural Network. 318-323 - Marco Polignano, Marco de Gemmis, Giovanni Semeraro:
SWAP at SemEval-2019 Task 3: Emotion detection in conversations through Tweets, CNN and LSTM deep neural networks. 324-329 - Angelo Basile, Marc Franco-Salvador, Neha Pawar, Sanja Stajner, Mara Chinea-Rios, Yassine Benajiba:
SymantoResearch at SemEval-2019 Task 3: Combined Neural Models for Emotion Classification in Human-Chatbot Conversations. 330-334 - Sourabh Maity:
TDBot at SemEval-2019 Task 3: Context Aware Emotion Detection Using A Conditioned Classification Approach. 335-339 - Suyu Ge, Tao Qi, Chuhan Wu, Yongfeng Huang:
THU_NGN at SemEval-2019 Task 3: Dialog Emotion Classification using Attentional LSTM-CNN. 340-344 - Xihao Liang, Ye Ma, Mingxing Xu:
THU-HCSI at SemEval-2019 Task 3: Hierarchical Ensemble Classification of Contextual Emotion in Conversation. 345-349 - Zhishen Yang, Sam Vijlbrief, Naoaki Okazaki:
TokyoTech_NLP at SemEval-2019 Task 3: Emotion-related Symbols in Emotion Detection. 350-354 - Cristian Simionescu, Ingrid Stoleru, Diana Lucaci, Gheorghe Balan, Iulian Bute, Adrian Iftene:
UAIC at SemEval-2019 Task 3: Extracting Much from Little. 355-359 - Dawei Li, Jin Wang, Xuejie Zhang:
YUN-HPCC at SemEval-2019 Task 3: Multi-Step Ensemble Neural Network for Sentiment Analysis in Textual Conversation. 360-364 - Umme Aymun Siddiqua, Abu Nowshed Chy, Masaki Aono:
KDEHatEval at SemEval-2019 Task 5: A Neural Network Model for Detecting Hate Speech in Twitter. 365-370 - Arup Baruah, Ferdous A. Barbhuiya, Kuntal Dey:
ABARUAH at SemEval-2019 Task 5 : Bi-directional LSTM for Hate Speech Detection. 371-376 - Alon Rozental, Dadi Biton:
Amobee at SemEval-2019 Tasks 5 and 6: Multiple Choice CNN Over Contextual Embedding. 377-381 - Iqra Ameer, Muhammad Hammad Fahim Siddiqui, Grigori Sidorov, Alexander F. Gelbukh:
CIC at SemEval-2019 Task 5: Simple Yet Very Efficient Approach to Hate Speech Detection, Aggressive Behavior Detection, and Target Classification in Twitter. 382-386 - Sattam Almatarneh, Pablo Gamallo, Francisco J. Ribadas-Pena:
CiTIUS-COLE at SemEval-2019 Task 5: Combining Linguistic Features to Identify Hate Speech Against Immigrants and Women on Multilingual Tweets. 387-390 - Mike Zhang, Roy David, Leon Graumans, Gerben Timmerman:
Grunn2019 at SemEval-2019 Task 5: Shared Task on Multilingual Detection of Hate. 391-395 - Diego Benito, Oscar Araque, Carlos Angel Iglesias:
GSI-UPM at SemEval-2019 Task 5: Semantic Similarity and Word Embeddings for Multilingual Detection of Hate Speech Against Immigrants and Women on Twitter. 396-403 - Nikhil Chakravartula:
HATEMINER at SemEval-2019 Task 5: Hate speech detection against Immigrants and Women in Twitter using a Multinomial Naive Bayes Classifier. 404-408 - Victor Nina-Alcocer:
HATERecognizer at SemEval-2019 Task 5: Using Features and Neural Networks to Face Hate Recognition. 409-415 - Gretel Liz De la Peña:
GL at SemEval-2019 Task 5: Identifying hateful tweets with a deep learning approach. 416-419 - Alison Ribeiro, Nádia Félix F. da Silva:
INF-HatEval at SemEval-2019 Task 5: Convolutional Neural Networks for Hate Speech Detection Against Women and Immigrants on Twitter. 420-425 - Yaakov HaCohen-Kerner, Elyashiv Shayovitz, Shalom Rochman, Eli Cahn, Gal Didi, Ziv Ben-David:
JCTDHS at SemEval-2019 Task 5: Detection of Hate Speech in Tweets using Deep Learning Methods, Character N-gram Features, and Preprocessing Methods. 426-430 - Kevin Winter, Roman Kern:
Know-Center at SemEval-2019 Task 5: Multilingual Hate Speech Detection on Twitter using CNNs. 431-435 - Nina Bauwelinck, Gilles Jacobs, Véronique Hoste, Els Lefever:
LT3 at SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter (hatEval). 436-440 - Huangpan Zhang, Michael Wojatzki, Tobias Horsmann, Torsten Zesch:
ltl.uni-due at SemEval-2019 Task 5: Simple but Effective Lexico-Semantic Features for Detecting Hate Speech in Twitter. 441-446 - Luis Enrique Argota Vega, Jorge Carlos Reyes-Magaña, Helena Gómez-Adorno, Gemma Bel-Enguix:
MineriaUNAM at SemEval-2019 Task 5: Detecting Hate Speech in Twitter using Multiple Features in a Combinatorial Framework. 447-452 - Abigail S. Gertner, John C. Henderson, Elizabeth M. Merkhofer, Amy Marsh, Ben Wellner, Guido Zarrella:
MITRE at SemEval-2019 Task 5: Transfer Learning for Multilingual Hate Speech Detection. 453-459 - Òscar Garibo i Orts:
Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter at SemEval-2019 Task 5: Frequency Analysis Interpolation for Hate in Speech Detection. 460-463 - Michal Bojkovský, Matús Pikuliak:
STUFIIT at SemEval-2019 Task 5: Multilingual Hate Speech Detection on Twitter with MUSE and ELMo Embeddings. 464-468 - Miriam Benballa, Sebastien Collet, Romain Picot-Clémente:
Saagie at Semeval-2019 Task 5: From Universal Text Embeddings and Classical Features to Domain-specific Text Classification. 469-475 - Flor Miriam Plaza del Arco, M. Dolores Molina-González, Maite Martín-Valdivia, Luis Alfonso Ureña López:
SINAI at SemEval-2019 Task 5: Ensemble learning to detect hate speech against inmigrants and women in English and Spanish tweets. 476-479 - Arturo Montejo-Ráez, Salud María Jiménez-Zafra, Miguel A. García-Cumbreras, Manuel Carlos Díaz-Galiano:
SINAI-DL at SemEval-2019 Task 5: Recurrent networks and data augmentation by paraphrasing. 480-483 - Aria Nourbakhsh, Frida Vermeer, Gijs Wiltvank, Rob van der Goot:
sthruggle at SemEval-2019 Task 5: An Ensemble Approach to Hate Speech Detection. 484-488 - Patricia Chiril, Farah Benamara Zitoune, Véronique Moriceau, Abhishek Kumar:
The binary trio at SemEval-2019 Task 5: Multitarget Hate Speech Detection in Tweets. 489-493 - Avishek Garain, Arpan Basu:
The Titans at SemEval-2019 Task 5: Detection of hate speech against immigrants and women in Twitter. 494-497 - Mihai Manolescu, Denise Löfflad, Adham Nasser Mohamed Saber, Masoumeh Moradipour Tari:
TuEval at SemEval-2019 Task 5: LSTM Approach to Hate Speech Detection in English and Spanish. 498-502 - Hala Mulki, Chedi Bechikh Ali, Hatem Haddad, Ismail Babaoglu:
Tw-StAR at SemEval-2019 Task 5: N-gram embeddings for Hate Speech Detection in Multilingual Tweets. 503-507 - Carlos Perelló, David Tomás, Alberto Garcia-Garcia, José García Rodríguez, José Camacho-Collados:
UA at SemEval-2019 Task 5: Setting A Strong Linear Baseline for Hate Speech Detection. 508-513 - Ali Hakimi Parizi, Milton King, Paul Cook:
UNBNLP at SemEval-2019 Task 5 and 6: Using Language Models to Detect Hate Speech and Offensive Language. 514-518 - Gustavo Henrique Paetzold, Marcos Zampieri, Shervin Malmasi:
UTFPR at SemEval-2019 Task 5: Hate Speech Identification with Recurrent Neural Networks. 519-523 - Kashyap Raiyani, Teresa Gonçalves, Paulo Quaresma, Vítor Beires Nogueira:
Vista.ue at SemEval-2019 Task 5: Single Multilingual Hate Speech Detection Model. 524-528 - Bin Wang, Haiyan Ding:
YNU NLP at SemEval-2019 Task 5: Attention and Capsule Ensemble for Identifying Hate Speech. 529-534 - Yunxia Ding, Xiaobing Zhou, Xuejie Zhang:
YNU_DYX at SemEval-2019 Task 5: A Stacked BiGRU Model Based on Capsule Network in Detection of Hate. 535-539 - Murali Sridharan, Swapna T. R.:
Amrita School of Engineering - CSE at SemEval-2019 Task 6: Manipulating Attention with Temporal Convolutional Neural Network for Offense Identification and Classification. 540-546 - Ritesh Kumar, Bhanodai Guggilla, Rajendra Pamula, Maheshwar Reddy Chennuru:
bhanodaig at SemEval-2019 Task 6: Categorizing Offensive Language in social media. 547-550 - Zhenghao Wu, Hao Zheng, Jianming Wang, Weifeng Su, Jefferson Fong:
BNU-HKBU UIC NLP Team 2 at SemEval-2019 Task 6: Detecting Offensive Language Using BERT model. 551-555 - Guy Aglionby, Christopher Davis, Pushkar Mishra, Andrew Caines, Helen Yannakoudakis, Marek Rei, Ekaterina Shutova, Paula Buttery:
CAMsterdam at SemEval-2019 Task 6: Neural and graph-based feature extraction for the identification of offensive tweets. 556-563 - Yaojie Zhang, Bing Xu, Tiejun Zhao:
CN-HIT-MI.T at SemEval-2019 Task 6: Offensive Language Identification Based on BiLSTM with Double Attention. 564-570 - John Pavlopoulos, Nithum Thain, Lucas Dixon, Ion Androutsopoulos:
ConvAI at SemEval-2019 Task 6: Offensive Language Identification and Categorization with Perspective and BERT. 571-576 - Sandip Modha, Prasenjit Majumder, Daksh Patel:
DA-LD-Hildesheim at SemEval-2019 Task 6: Tracking Offensive Content with Deep Learning using Shallow Representation. 577-581 - Gretel Liz De la Peña Sarracén, Paolo Rosso:
DeepAnalyzer at SemEval-2019 Task 6: A deep learning-based ensemble method for identifying offensive tweets. 582-586 - Prashant Kapil, Asif Ekbal, Dipankar Das:
NLP at SemEval-2019 Task 6: Detecting Offensive language using Neural Networks. 587-592 - Ted Pedersen:
Duluth at SemEval-2019 Task 6: Lexical Approaches to Identify and Categorize Offensive Tweets. 593-599 - Emad Kebriaei, Samaneh Karimi, Nazanin Sabri, Azadeh Shakery:
Emad at SemEval-2019 Task 6: Offensive Language Identification using Traditional Machine Learning and Deep Learning approaches. 600-603 - Andraz Pelicon, Matej Martinc, Petra Kralj Novak:
Embeddia at SemEval-2019 Task 6: Detecting Hate with Neural Network and Transfer Learning Approaches. 604-610 - Vijayasaradhi Indurthi, Bakhtiyar Syed, Manish Shrivastava, Manish Gupta, Vasudeva Varma:
Fermi at SemEval-2019 Task 6: Identifying and Categorizing Offensive Language in Social Media using Sentence Embeddings. 611-616 - Ehsan Doostmohammadi, Hossein Sameti, Ali Saffar:
Ghmerti at SemEval-2019 Task 6: A Deep Word- and Character-based Approach to Offensive Language Identification. 617-621 - Himanshu Bansal, Daniel Nagel, Anita Soloveva:
HAD-Tübingen at SemEval-2019 Task 6: Deep Learning Analysis of Offensive Language on Twitter: Identification and Categorization. 622-627 - Alexander Oberstraß, Julia Romberg, Anke Stoll, Stefan Conrad:
HHU at SemEval-2019 Task 6: Context Does Matter - Tackling Offensive Language Identification and Categorization with ELMo. 628-634 - Gabriel Florentin Patras, Diana Florina Lungu, Daniela Gîfu, Diana Trandabat:
Hope at SemEval-2019 Task 6: Mining social media language to discover offensive language. 635-638 - Mario Graff, Sabino Miranda-Jiménez, Eric Sadit Tellez, Daniela Alejandra Ochoa:
INGEOTEC at SemEval-2019 Task 5 and Task 6: A Genetic Programming Approach for Text Classification. 639-644