---
title: "Workshop on Computational Approaches to Subjectivity"
description: "Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis 2017 — accepted papers: 3 papers in the…"
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# Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis 2017 — accepted papers

Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis 2017 is the 2017 edition of the Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, held in Copenhagen, Denmark, September 2017 (publisher: Association for Computational Linguistics). OpenAlex lists 37 papers of it; our library holds 3 with our summaries. Below: the most cited papers, every accepted paper, and ours with their topics, authors and institutions.

[**37** papers in the proceedings](#all) · [**3** works in our library](https://md.research.elamur.ai/free/en/venues/wassa/2017/#works) · [**500** citations of these works](https://md.research.elamur.ai/free/en/venues/wassa/2017/#works)**Copenhagen, Denmark** where it was held**September 2017** when

## Most cited papers

By their OpenAlex citations; a paper with our summary links to its page here, the others to the original.

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*

## All accepted papers (37)

The most cited first; 3 with our summary link to their page here, the others to the original.

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*

[See all 37 papers in Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis 2017 — accepted papers →](https://md.research.elamur.ai/free/en/venues/wassa/2017/papers/)

## Papers with our summary in our library (3)

The most cited first (OpenAlex citations plus our library's).

1. **[WASSA-2017 Shared Task on Emotion Intensity](https://md.research.elamur.ai/free/en/papers/mohammad-2017-wassa-2017-shared-task-emotion/) [Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis](https://md.research.elamur.ai/free/en/venues/wassa/)**Saif Mohammad, Felipe Bravo-Marquez*2017 · 369 citations*
2. **[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/) [Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis](https://md.research.elamur.ai/free/en/venues/wassa/)**Hendrik Schuff, Jeremy Barnes, Julian Mohme, et al.*2017 · 129 citations*
3. [**Detecting Sarcasm Using Different Forms Of Incongruity**Aditya Joshi*2017 · 2 citations*](https://md.research.elamur.ai/free/en/papers/joshi-2017-detecting-sarcasm-different-forms-incongruity/)

## Top topics

Topics of its works in our library, with the number of works on each.

[Sentiment & emotion (3)](https://md.research.elamur.ai/free/en/topics/sentiment-emotion/) · [English (1)](https://md.research.elamur.ai/free/en/topics/english/)

## Fields

[Computer Science (3)](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Psychology (2)](https://md.research.elamur.ai/free/en/shelves/psychology/) · [Arts and Humanities (1)](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/)

## Top authors

Authors with a page who published here most often: their works here, and the citations of those works.

[🧑‍🔬**Felipe Bravo-Marquez**1 work here · 369 citations](https://md.research.elamur.ai/free/en/authors/felipe-bravo-marquez/) · [🧑‍🔬**Saif Mohammad**1 work here · 369 citations](https://md.research.elamur.ai/free/en/authors/saif-mohammad/) · [🧑‍🔬**Hendrik Schuff**1 work here · 129 citations](https://md.research.elamur.ai/free/en/authors/hendrik-schuff/) · [🧑‍🔬**Roman Klinger**1 work here · 129 citations](https://md.research.elamur.ai/free/en/authors/roman-klinger/) · [🧑‍🔬**Sebastian Padó**1 work here · 129 citations](https://md.research.elamur.ai/free/en/authors/sebastian-pado/) · [🧑‍🔬**Aditya Joshi**1 work here · 2 citations](https://md.research.elamur.ai/free/en/authors/aditya-joshi/)

## Top institutions

Institutions on the bylines of its works here, by the number of works.

[🎓**University of Stuttgart** Stuttgart · Germany 1 work here](https://md.research.elamur.ai/free/en/universities/university-of-stuttgart/) · [🎓**Indian Institute of Technology Bombay** Mumbai · India 1 work here](https://md.research.elamur.ai/free/en/universities/indian-institute-of-technology-bombay/) · [🏛️**National Academies of Sciences, Engineering, and Medicine** Washington · United States 1 work here](https://md.research.elamur.ai/free/en/government/national-academies-of-sciences-engineering-and-medicine/) · [🎓**IITB-Monash Research Academy** Mumbai · India 1 work here](https://md.research.elamur.ai/free/en/universities/iitb-monash-research-academy/) · [🏛️**National Research Council Canada** Ottawa · Canada 1 work here](https://md.research.elamur.ai/free/en/government/national-research-council-canada/) · [🎓**University of Waikato** Hamilton · New Zealand 1 work here](https://md.research.elamur.ai/free/en/universities/university-of-waikato/) · [🎓**Monash University** Melbourne · Australia 1 work here](https://md.research.elamur.ai/free/en/universities/monash-university/)

Place and dates from the event's site or the ACL Anthology; works and citations from OpenAlex and our library.

- [← previous Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis 2016](https://md.research.elamur.ai/free/en/venues/wassa/2016/)
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