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title: "Workshop on Computational Approaches to Subjectivity,"
description: "All 37 papers of Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis 2017, the most cited first…"
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# 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](https://md.research.elamur.ai/free/en/venues/wassa/2017/)

1. **[Explaining Recurrent Neural Network Predictions in Sentiment Analysis ↗](https://aclanthology.org/W17-5221/)**Leila Arras, Grégoire Montavon, Klaus-Robert Müller et al.*352 citations*
2. **[WASSA-2017 Shared Task on Emotion Intensity](https://md.research.elamur.ai/free/en/papers/mohammad-2017-wassa-2017-shared-task-emotion/)**Saif Mohammad, Felipe Bravo-Marquez*270 citations · our summary*
3. **[Lexicon Integrated CNN Models with Attention for Sentiment Analysis ↗](https://aclanthology.org/W17-5220/)**Bonggun Shin, Timothy Lee, Jinho D. Choi*123 citations*
4. **[Investigating Redundancy in Emoji Use: Study on a Twitter Based Corpus ↗](https://aclanthology.org/W17-5216/)**Giulia Donato, Patrizia Paggio*94 citations*
5. **[Annotation, Modelling and Analysis of Fine-Grained Emotions on a Stance and Sentiment Detection Corpus](https://md.research.elamur.ai/free/en/papers/schuff-2017-annotation-modelling-analysis-fine-grained/)**Hendrik Schuff, Jeremy Barnes, Julian Mohme et al.*92 citations · our summary*
6. **[Unsupervised Aspect Term Extraction with B-LSTM & CRF using Automatically Labelled Datasets ↗](https://aclanthology.org/W17-5224/)**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 ↗](https://aclanthology.org/W17-5202/)**Jeremy Barnes, Roman Klinger, Sabine Schulte im Walde*70 citations*
8. **[Prayas at EmoInt 2017: An Ensemble of Deep Neural Architectures for Emotion Intensity Prediction in Tweets ↗](https://aclanthology.org/W17-5207/)**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 ↗](https://aclanthology.org/W17-5206/)**Maximilian Köper, Evgeny Kim, Roman Klinger*53 citations*
10. **[YNU-HPCC at EmoInt-2017: Using a CNN-LSTM Model for Sentiment Intensity Prediction ↗](https://aclanthology.org/W17-5227/)**You Zhang, Hang Yuan, Jin Wang et al.*31 citations*
11. **[Towards an integrated pipeline for aspect-based sentiment analysis in various domains ↗](https://aclanthology.org/W17-5218/)**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 ↗](https://aclanthology.org/W17-5213/)**Edison Marrese-Taylor, Jorge Balazs, Yutaka Matsuo*25 citations*
13. **[Seernet at EmoInt-2017: Tweet Emotion Intensity Estimator ↗](https://aclanthology.org/W17-5228/)**Venkatesh Duppada, Sushant Hiray*25 citations*
14. **[Did you ever read about Frogs drinking Coffee? Investigating the Compositionality of Multi-Emoji Expressions ↗](https://aclanthology.org/W17-5215/)**Rebeca Padilla López, Fabienne Cap*19 citations*
15. **[Forecasting Consumer Spending from Purchase Intentions Expressed on Social Media ↗](https://aclanthology.org/W17-5212/)**Viktor Pekar, Jane Binner*18 citations*
16. **[Modeling Temporal Progression of Emotional Status in Mental Health Forum: A Recurrent Neural Net Approach ↗](https://aclanthology.org/W17-5217/)**Kishaloy Halder, Lahari Poddar, Min-Yen Kan*18 citations*
17. **[YZU-NLP at EmoInt-2017: Determining Emotion Intensity Using a Bi-directional LSTM-CNN Model ↗](https://aclanthology.org/W17-5233/)**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 ↗](https://aclanthology.org/W17-5222/)**Egor Lakomkin, Chandrakant Bothe, Stefan Wermter*9 citations*
19. **[NSEmo at EmoInt-2017: An Ensemble to Predict Emotion Intensity in Tweets ↗](https://aclanthology.org/W17-5230/)**Sreekanth Madisetty, Maunendra Sankar Desarkar*9 citations*
20. **[Building a SentiWordNet for Odia ↗](https://aclanthology.org/W17-5219/)**Gaurav Mohanty, Abishek Kannan, Radhika Mamidi*8 citations*
21. **[IITP at EmoInt-2017: Measuring Intensity of Emotions using Sentence Embeddings and Optimized Features ↗](https://aclanthology.org/W17-5229/)**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 ↗](https://aclanthology.org/W17-5235/)**Vineet John, Olga Vechtomova*7 citations*
23. **[Ranking Right-Wing Extremist Social Media Profiles by Similarity to Democratic and Extremist Groups ↗](https://aclanthology.org/W17-5204/)**Matthias Hartung, Roman Klinger, Franziska Schmidtke et al.*6 citations*
24. **[Linguistic Reflexes of Well-Being and Happiness in Echo ↗](https://aclanthology.org/W17-5211/)**Jiaqi Wu, Marilyn Walker, Pranav Anand et al.*5 citations*
25. **[NUIG at EmoInt-2017: BiLSTM and SVR Ensemble to Detect Emotion Intensity ↗](https://aclanthology.org/W17-5223/)**Vladimir Andryushechkin, Ian Wood, James O' Neill*5 citations*
26. **[Textmining at EmoInt-2017: A Deep Learning Approach to Sentiment Intensity Scoring of English Tweets ↗](https://aclanthology.org/W17-5226/)**Hardik Meisheri, Rupsa Saha, Priyanka Sinha et al.*4 citations*
27. **[Tecnolengua Lingmotif at EmoInt-2017: A lexicon-based approach ↗](https://aclanthology.org/W17-5231/)**Antonio Moreno-Ortiz*3 citations*
28. **[Toward Stance Classification Based on Claim Microstructures ↗](https://aclanthology.org/W17-5210/)**Filip Boltužić, Jan Šnajder*3 citations*
29. **[Detecting Sarcasm Using Different Forms Of Incongruity](https://md.research.elamur.ai/free/en/papers/joshi-2017-detecting-sarcasm-different-forms-incongruity/)**Aditya Joshi*2 citations · our summary*
30. **[LIPN-UAM at EmoInt-2017:Combination of Lexicon-based features and Sentence-level Vector Representations for Emotion Intensity Determination ↗](https://aclanthology.org/W17-5236/)**Davide Buscaldi, Belem Priego*2 citations*
31. **[Towards Syntactic Iberian Polarity Classification ↗](https://aclanthology.org/W17-5209/)**David Vilares, Marcos Garcia, Miguel A. Alonso et al.*2 citations*
32. **[deepCybErNet at EmoInt-2017: Deep Emotion Intensities in Tweets ↗](https://aclanthology.org/W17-5237/)**Vinayakumar R, Premjith B, Sachin Kumar S et al.*2 citations*
33. **[DMGroup at EmoInt-2017: Emotion Intensity Using Ensemble Method ↗](https://aclanthology.org/W17-5234/)**Song Jiang, Xiaotian Han*1 citation*
34. **[EmoAtt at EmoInt-2017: Inner attention sentence embedding for Emotion Intensity ↗](https://aclanthology.org/W17-5232/)**Edison Marrese-Taylor, Yutaka Matsuo*1 citation*
35. **[PLN-PUCRS at EmoInt-2017: Psycholinguistic features for emotion intensity prediction in tweets ↗](https://aclanthology.org/W17-5225/)**Henrique Santos, Renata Vieira*1 citation*
36. **[Latest News in Computational Argumentation: Surfing on the Deep Learning Wave, Scuba Diving in the Abyss of Fundamental Questions ↗](https://aclanthology.org/W17-5208/)**Iryna Gurevych
37. **[Understanding human values and their emotional effect ↗](https://aclanthology.org/W17-5214/)**Alexandra Balahur
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