Papers
Lsislif: Feature Extraction and Label Weighting for Sentiment Analysis in Twitter
Hussam Hamdan, Patrice Bellot, Frederic Bechet
ECNU: Multi-level Sentiment Analysis on Twitter Using Traditional Linguistic Features and Word Embedding Features
Zhihua Zhang, Guoshun Wu, Man Lan
UDLAP: Sentiment Analysis Using a Graph-Based Representation
Esteban Castillo, Ofelia Cervantes, Darnes Vilariño et al.
RoseMerry: A Baseline Message-level Sentiment Classification System
Huizhi Liang, Richard Fothergill, Timothy Baldwin
IOA: Improving SVM Based Sentiment Classification Through Post Processing
Peijia Li, Weiqun Xu, Chenglong Ma et al.
Gradiant-Analytics: Training Polarity Shifters with CRFs for Message Level Polarity Detection
Héctor Cerezo-Costas, Diego Celix-Salgado
GTI: An Unsupervised Approach for Sentiment Analysis in Twitter
Milagros Fernández-Gavilanes, Tamara Álvarez-López, Jonathan Juncal-Martínez et al.
CIS-positive: A Combination of Convolutional Neural Networks and Support Vector Machines for Sentiment Analysis in Twitter
Sebastian Ebert, Ngoc Thang Vu, Hinrich Schütze
IIIT-H at SemEval 2015: Twitter Sentiment Analysis – The Good, the Bad and the Neutral!
Ayushi Dalmia, Manish Gupta, Vasudeva Varma
Splusplus: A Feature-Rich Two-stage Classifier for Sentiment Analysis of Tweets
Li Dong, Furu Wei, Yichun Yin et al.
DIEGOLab: An Approach for Message-level Sentiment Classification in Twitter
Abeed Sarker, Azadeh Nikfarjam, Davy Weissenbacher et al.
SemEval-2015 Task 12: Aspect Based Sentiment Analysis
Maria Pontiki, Dimitris Galanis, Haris Papageorgiou et al.
CLaC-SentiPipe: SemEval2015 Subtasks 10 B,E, and Task 11
Canberk Özdemir, Sabine Bergler
SemEval-2015 Task 11: Sentiment Analysis of Figurative Language in Twitter
Aniruddha Ghosh, Guofu Li, Tony Veale et al.
UNITN: Training Deep Convolutional Neural Network for Twitter Sentiment Classification
Aliaksei Severyn, Alessandro Moschitti
SemEval-2015 Task 10: Sentiment Analysis in Twitter
Sara Rosenthal, Preslav Nakov, Svetlana Kiritchenko et al.
SemEval-2015 Task 9: CLIPEval Implicit Polarity of Events
Irene Russo, Tommaso Caselli, Carlo Strapparava
CMILLS: Adapting Semantic Role Labeling Features to Dependency Parsing
Chad Mills, Gina-Anne Levow
LIST-LUX: Disorder Identification from Clinical Texts
Asma Ben Abacha, Aikaterini Karanasiou, Yassine Mrabet et al.
BioinformaticsUA: Machine Learning and Rule-Based Recognition of Disorders and Clinical Attributes from Patient Notes
Sérgio Matos, José Sequeira, José Luís Oliveira
CUAB: Supervised Learning of Disorders and their Attributes using Relations
James Gung, John David Osborne, Steven Bethard
ezDI: A Supervised NLP System for Clinical Narrative Analysis
Parth Pathak, Pinal Patel, Vishal Panchal et al.