📰 Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis 2017: all accepted papers

37 papers · the most cited first · ← Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis 2017

1. Explaining Recurrent Neural Network Predictions in Sentiment Analysis ↗Leila Arras, Grégoire Montavon, Klaus-Robert Müller et al.352 citations
2. WASSA-2017 Shared Task on Emotion IntensitySaif Mohammad, Felipe Bravo-Marquez270 citations · our summary
3. Lexicon Integrated CNN Models with Attention for Sentiment Analysis ↗Bonggun Shin, Timothy Lee, Jinho D. Choi123 citations
4. Investigating Redundancy in Emoji Use: Study on a Twitter Based Corpus ↗Giulia Donato, Patrizia Paggio94 citations
5. Annotation, Modelling and Analysis of Fine-Grained Emotions on a Stance and Sentiment Detection CorpusHendrik Schuff, Jeremy Barnes, Julian Mohme et al.92 citations · our summary
6. Unsupervised Aspect Term Extraction with B-LSTM & CRF using Automatically Labelled Datasets ↗Athanasios Giannakopoulos, Claudiu Musat, Andreea Hossmann et al.71 citations
7. Assessing State-of-the-Art Sentiment Models on State-of-the-Art Sentiment Datasets ↗Jeremy Barnes, Roman Klinger, Sabine Schulte im Walde70 citations
8. Prayas at EmoInt 2017: An Ensemble of Deep Neural Architectures for Emotion Intensity Prediction in Tweets ↗Pranav Goel, Devang Kulshreshtha, Prayas Jain et al.63 citations
9. IMS at EmoInt-2017: Emotion Intensity Prediction with Affective Norms, Automatically Extended Resources and Deep Learning ↗Maximilian Köper, Evgeny Kim, Roman Klinger53 citations
10. YNU-HPCC at EmoInt-2017: Using a CNN-LSTM Model for Sentiment Intensity Prediction ↗You Zhang, Hang Yuan, Jin Wang et al.31 citations
11. Towards an integrated pipeline for aspect-based sentiment analysis in various domains ↗Orphée De Clercq, Els Lefever, Gilles Jacobs et al.28 citations
12. Mining fine-grained opinions on closed captions of YouTube videos with an attention-RNN ↗Edison Marrese-Taylor, Jorge Balazs, Yutaka Matsuo25 citations
13. Seernet at EmoInt-2017: Tweet Emotion Intensity Estimator ↗Venkatesh Duppada, Sushant Hiray25 citations
14. Did you ever read about Frogs drinking Coffee? Investigating the Compositionality of Multi-Emoji Expressions ↗Rebeca Padilla López, Fabienne Cap19 citations
15. Forecasting Consumer Spending from Purchase Intentions Expressed on Social Media ↗Viktor Pekar, Jane Binner18 citations
16. Modeling Temporal Progression of Emotional Status in Mental Health Forum: A Recurrent Neural Net Approach ↗Kishaloy Halder, Lahari Poddar, Min-Yen Kan18 citations
17. YZU-NLP at EmoInt-2017: Determining Emotion Intensity Using a Bi-directional LSTM-CNN Model ↗Yuanye He, Liang-Chih Yu, K. Robert Lai et al.16 citations
18. GradAscent at EmoInt-2017: Character and Word Level Recurrent Neural Network Models for Tweet Emotion Intensity Detection ↗Egor Lakomkin, Chandrakant Bothe, Stefan Wermter9 citations
19. NSEmo at EmoInt-2017: An Ensemble to Predict Emotion Intensity in Tweets ↗Sreekanth Madisetty, Maunendra Sankar Desarkar9 citations
20. Building a SentiWordNet for Odia ↗Gaurav Mohanty, Abishek Kannan, Radhika Mamidi8 citations
21. IITP at EmoInt-2017: Measuring Intensity of Emotions using Sentence Embeddings and Optimized Features ↗Md Shad Akhtar, Palaash Sawant, Asif Ekbal et al.8 citations
22. UWat-Emote at EmoInt-2017: Emotion Intensity Detection using Affect Clues, Sentiment Polarity and Word Embeddings ↗Vineet John, Olga Vechtomova7 citations
23. Ranking Right-Wing Extremist Social Media Profiles by Similarity to Democratic and Extremist Groups ↗Matthias Hartung, Roman Klinger, Franziska Schmidtke et al.6 citations
24. Linguistic Reflexes of Well-Being and Happiness in Echo ↗Jiaqi Wu, Marilyn Walker, Pranav Anand et al.5 citations
25. NUIG at EmoInt-2017: BiLSTM and SVR Ensemble to Detect Emotion Intensity ↗Vladimir Andryushechkin, Ian Wood, James O' Neill5 citations
26. Textmining at EmoInt-2017: A Deep Learning Approach to Sentiment Intensity Scoring of English Tweets ↗Hardik Meisheri, Rupsa Saha, Priyanka Sinha et al.4 citations
27. Tecnolengua Lingmotif at EmoInt-2017: A lexicon-based approach ↗Antonio Moreno-Ortiz3 citations
28. Toward Stance Classification Based on Claim Microstructures ↗Filip Boltužić, Jan Šnajder3 citations
29. Detecting Sarcasm Using Different Forms Of IncongruityAditya Joshi2 citations · our summary
30. LIPN-UAM at EmoInt-2017:Combination of Lexicon-based features and Sentence-level Vector Representations for Emotion Intensity Determination ↗Davide Buscaldi, Belem Priego2 citations
31. Towards Syntactic Iberian Polarity Classification ↗David Vilares, Marcos Garcia, Miguel A. Alonso et al.2 citations
32. deepCybErNet at EmoInt-2017: Deep Emotion Intensities in Tweets ↗Vinayakumar R, Premjith B, Sachin Kumar S et al.2 citations
33. DMGroup at EmoInt-2017: Emotion Intensity Using Ensemble Method ↗Song Jiang, Xiaotian Han1 citation
34. EmoAtt at EmoInt-2017: Inner attention sentence embedding for Emotion Intensity ↗Edison Marrese-Taylor, Yutaka Matsuo1 citation
35. PLN-PUCRS at EmoInt-2017: Psycholinguistic features for emotion intensity prediction in tweets ↗Henrique Santos, Renata Vieira1 citation
36. Latest News in Computational Argumentation: Surfing on the Deep Learning Wave, Scuba Diving in the Abyss of Fundamental Questions ↗Iryna Gurevych
37. Understanding human values and their emotional effect ↗Alexandra Balahur

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