Table of Contents

• Identifying Affective Events and the Reasons for their PolarityEllen Riloff. 1 [doi]
• Deep contextualized word representations for detecting sarcasm and ironySuzana Ilic, Edison Marrese-Taylor, Jorge A. Balazs, Yutaka Matsuo. 2-7 [doi]
• Implicit Subjective and Sentimental Usages in Multi-sense Word EmbeddingsYuqi Sun, Haoyue Shi, Junfeng Hu. 8-13 [doi]
• Language Independent Sentiment Analysis with Sentiment-Specific Word EmbeddingsCarl Saroufim, Akram Almatarky, Mohammad Abdelhady. 14-23 [doi]
• Creating a Dataset for Multilingual Fine-grained Emotion-detection Using Gamification-based AnnotationEmily Öhman, Kaisla Kajava, Jörg Tiedemann, Timo Honkela. 24-30 [doi]
• IEST: WASSA-2018 Implicit Emotions Shared TaskRoman Klinger, Orphée De Clercq, Saif Mohammad, Alexandra Balahur. 31-42 [doi]
• Amobee at IEST 2018: Transfer Learning from Language ModelsAlon Rozental, Daniel Fleischer, Zohar Kelrich. 43-49 [doi]
• IIIDYT at IEST 2018: Implicit Emotion Classification With Deep Contextualized Word RepresentationsJorge A. Balazs, Edison Marrese-Taylor, Yutaka Matsuo. 50-56 [doi]
• NTUA-SLP at IEST 2018: Ensemble of Neural Transfer Methods for Implicit Emotion ClassificationAlexandra Chronopoulou, Aikaterini Margatina, Christos Baziotis, Alexandros Potamianos. 57-64 [doi]
• Sentiment analysis under temporal shiftJan Lukes, Anders Søgaard. 65-71 [doi]
• Not Just Depressed: Bipolar Disorder Prediction on RedditIvan Sekulic, Matej Gjurkovic, Jan Snajder. 72-78 [doi]
• Topic-Specific Sentiment Analysis Can Help Identify Political IdeologySumit Bhatia, Deepak P. 79-84 [doi]
• Saying no but meaning yes: negation and sentiment analysis in BasqueJon Alkorta, Koldo Gojenola, Mikel Iruskieta. 85-90 [doi]
• Leveraging Writing Systems Change for Deep Learning Based Chinese Emotion AnalysisRong Xiang, Yunfei Long, Qin Lu, Dan Xiong, I-Hsuan Chen. 91-96 [doi]
• Ternary Twitter Sentiment Classification with Distant Supervision and Sentiment-Specific Word EmbeddingsMats Byrkjeland, Frederik Gørvell de Lichtenberg, Björn Gambäck. 97-106 [doi]
• Linking News Sentiment to Microblogs: A Distributional Semantics Approach to Enhance Microblog Sentiment ClassificationTobias Daudert, Paul Buitelaar. 107-115 [doi]
• Aspect Based Sentiment Analysis into the WildCaroline Brun, Vassilina Nikoulina. 116-122 [doi]
• The Role of Emotions in Native Language IdentificationIlia Markov, Vivi Nastase, Carlo Strapparava, Grigori Sidorov. 123-129 [doi]
• Self-Attention: A Better Building Block for Sentiment Analysis Neural Network ClassifiersArtaches Ambartsoumian, Fred Popowich. 130-139 [doi]
• Dual Memory Network Model for Biased Product Review ClassificationYunfei Long, Mingyu Ma, Qin Lu, Rong Xiang, Chu-Ren Huang. 140-148 [doi]
• Measuring Issue Ownership using Word EmbeddingsAmaru Cuba Gyllensten, Magnus Sahlgren. 149-155 [doi]
• Sentiment Expression Boundaries in Sentiment Polarity ClassificationRasoul Kaljahi, Jennifer Foster. 156-166 [doi]
• Exploring and Learning Suicidal Ideation Connotations on Social Media with Deep LearningRamit Sawhney, Prachi Manchanda, Puneet Mathur, Rajiv Ratn Shah, Raj Singh. 167-175 [doi]
• UTFPR at IEST 2018: Exploring Character-to-Word Composition for Emotion AnalysisGustavo Paetzold. 176-181 [doi]
• HUMIR at IEST-2018: Lexicon-Sensitive and Left-Right Context-Sensitive BiLSTM for Implicit Emotion RecognitionBehzad Naderalvojoud, Alaettin Ucan, Ebru Akcapinar Sezer. 182-188 [doi]
• NLP at IEST 2018: BiLSTM-Attention and LSTM-Attention via Soft Voting in Emotion ClassificationQimin Zhou, Hao Wu. 189-194 [doi]
• SINAI at IEST 2018: Neural Encoding of Emotional External Knowledge for Emotion ClassificationFlor Miriam Plaza del Arco, Eugenio Martínez-Cámara, Maite Martín, Luis Alfonso Ureña López. 195-200 [doi]
• EmoNLP at IEST 2018: An Ensemble of Deep Learning Models and Gradient Boosting Regression Tree for Implicit Emotion Prediction in TweetsMan Liu. 201-204 [doi]
• HGSGNLP at IEST 2018: An Ensemble of Machine Learning and Deep Neural Architectures for Implicit Emotion Classification in TweetsWenting Wang, Man Lan. 205-210 [doi]
• DataSEARCH at IEST 2018: Multiple Word Embedding based Models for Implicit Emotion Classification of Tweets with Deep LearningYasas Senarath, Uthayasanker Thayasivam. 211-216 [doi]
• NL-FIIT at IEST-2018: Emotion Recognition utilizing Neural Networks and Multi-level PreprocessingSamuel Pecar, Michal Farkas, Marián Simko, Peter Lacko, Mária Bieliková. 217-223 [doi]
• UWB at IEST 2018: Emotion Prediction in Tweets with Bidirectional Long Short-Term Memory Neural NetworkPavel Pribán, Jirí Martínek. 224-230 [doi]
• USI-IR at IEST 2018: Sequence Modeling and Pseudo-Relevance Feedback for Implicit Emotion DetectionEsteban Rissola, Anastasia Giachanou, Fabio Crestani. 231-234 [doi]
• EmotiKLUE at IEST 2018: Topic-Informed Classification of Implicit EmotionsThomas Proisl, Philipp Heinrich, Besim Kabashi, Stefan Evert. 235-242 [doi]
• BrainT at IEST 2018: Fine-tuning Multiclass Perceptron For Implicit Emotion ClassificationVachagan Gratian, Marina Haid. 243-247 [doi]
• Disney at IEST 2018: Predicting Emotions using an EnsembleWojciech Witon, Pierre Colombo, Ashutosh Modi, Mubbasir Kapadia. 248-253 [doi]
• Sentylic at IEST 2018: Gated Recurrent Neural Network and Capsule Network Based Approach for Implicit Emotion DetectionPrabod Rathnayaka, Supun Abeysinghe, Chamod Samarajeewa, Isura Manchanayake, Malaka Walpola. 254-259 [doi]
• Fast Approach to Build an Automatic Sentiment Annotator for Legal Domain using Transfer LearningViraj Salaka, Menuka Warushavithana, Nisansa de Silva, Amal Shehan Perera, Gathika Ratnayaka, Thejan Rupasinghe. 260-265 [doi]
• What Makes You Stressed? Finding Reasons From TweetsReshmi Gopalakrishna Pillai, Mike Thelwall, Constantin Orasan. 266-272 [doi]
• EmojiGAN: learning emojis distributions with a generative modelBogdan Mazoure, Thang Doan, Saibal Ray. 273-279 [doi]
• Identifying Opinion-Topics and Polarity of Parliamentary Debate MotionsGavin Abercrombie, Riza Theresa Batista-Navarro. 280-285 [doi]
• Homonym Detection For Humor Recognition In Short TextSven van den Beukel, Lora Aroyo. 286-291 [doi]
• Emo2Vec: Learning Generalized Emotion Representation by Multi-task TrainingPeng Xu, Andrea Madotto, Chien-Sheng Wu, Ji-Ho Park, Pascale Fung. 292-298 [doi]
• Learning representations for sentiment classification using Multi-task frameworkHardik Meisheri, Harshad Khadilkar. 299-308 [doi]
• Super Characters: A Conversion from Sentiment Classification to Image ClassificationBaohua Sun, Lin Yang, Patrick Dong, Wenhan Zhang, Jason Dong, Charles Young. 309-315 [doi]
• Learning Comment Controversy Prediction in Web Discussions Using Incidentally Supervised Multi-Task CNNsNils Rethmeier, Marc Hübner, Leonhard Hennig. 316-321 [doi]
• Words Worth: Verbal Content and Hirability Impressions in YouTube Video ResumesSkanda Muralidhar, Laurent Son Nguyen, Daniel Gatica-Perez. 322-327 [doi]
• Predicting Adolescents' Educational Track from Chat Messages on Dutch Social MediaLisa Hilte, Walter Daelemans, Reinhild Vandekerckhove. 328-334 [doi]
• Arabizi sentiment analysis based on transliteration and automatic corpus annotationImane Guellil, Ahsan Adeel, Faiçal Azouaou, Fodil Benali, Ala-Eddine Hachani, Amir Hussain. 335-341 [doi]
• UBC-NLP at IEST 2018: Learning Implicit Emotion With an Ensemble of Language ModelsHassan Alhuzali, Mohamed Elaraby, Muhammad Abdul-Mageed. 342-347 [doi]