Papers
Columbia NLP: Sentiment Detection of Subjective Phrases in Social Media
Sara Rosenthal, Kathy McKeown
SU-Sentilab : A Classification System for Sentiment Analysis in Twitter
Gizem Gezici, Rahim Dehkharghani, Berrin Yanikoglu et al.
FBK: Sentiment Analysis in Twitter with Tweetsted
Md. Faisal Mahbub Chowdhury, Marco Guerini, Sara Tonelli et al.
Experiments with DBpedia, WordNet and SentiWordNet as resources for sentiment analysis in micro-blogging
Hussam Hamdan, Frederic Béchet, Patrice Bellot
UMCC_DLSI-(SA): Using a ranking algorithm and informal features to solve Sentiment Analysis in Twitter
Yoan Gutiérrez, Andy González, Roger Pérez et al.
SAIL: A hybrid approach to sentiment analysis
Nikolaos Malandrakis, Abe Kazemzadeh, Alexandros Potamianos et al.
NTNU: Domain Semi-Independent Short Message Sentiment Classification
Øyvind Selmer, Mikael Brevik, Björn Gambäck et al.
SwatCS: Combining simple classifiers with estimated accuracy
Sam Clark, Rich Wicentwoski
[LVIC-LIMSI]: Using Syntactic Features and Multi-polarity Words for Sentiment Analysis in Twitter
Morgane Marchand, Alexandru Ginsca, Romaric Besançon et al.
ECNUCS: A Surface Information Based System Description of Sentiment Analysis in Twitter in the SemEval-2013 (Task 2)
Tiantian Zhu, Fangxi Zhang, Lan Man
SINAI: Machine Learning and Emotion of the Crowd for Sentiment Analysis in Microblogs
Eugenio Martínez-Cámara, Arturo Montejo-Ráez, M. Teresa Martín-Valdivia et al.
KLUE: Simple and robust methods for polarity classification
Thomas Proisl, Paul Greiner, Stefan Evert et al.
USNA: A Dual-Classifier Approach to Contextual Sentiment Analysis
Ganesh Harihara, Eugene Yang, Nathanael Chambers
UT-DB: An Experimental Study on Sentiment Analysis in Twitter
Zhemin Zhu, Djoerd Hiemstra, Peter Apers et al.
uOttawa: System description for SemEval 2013 Task 2 Sentiment Analysis in Twitter
Hamid Poursepanj, Josh Weissbock, Diana Inkpen
TJP: Using Twitter to Analyze the Polarity of Contexts
Tawunrat Chalothorn, Jeremy Ellman
UNITOR: Combining Syntactic and Semantic Kernels for Twitter Sentiment Analysis
Giuseppe Castellucci, Simone Filice, Danilo Croce et al.
AMI&ERIC: How to Learn with Naive Bayes and Prior Knowledge: an Application to Sentiment Analysis
Mohamed Dermouche, Leila Khouas, Julien Velcin et al.
WBI-NER: The impact of domain-specific features on the performance of identifying and classifying mentions of drugs
Tim Rocktäschel, Torsten Huber, Michael Weidlich et al.
FBK-irst : A Multi-Phase Kernel Based Approach for Drug-Drug Interaction Detection and Classification that Exploits Linguistic Information
Md. Faisal Mahbub Chowdhury, Alberto Lavelli
SemEval-2013 Task 9 : Extraction of Drug-Drug Interactions from Biomedical Texts (DDIExtraction 2013)
Isabel Segura-Bedmar, Paloma Martínez, María Herrero-Zazo
AVAYA: Sentiment Analysis on Twitter with Self-Training and Polarity Lexicon Expansion
Lee Becker, George Erhart, David Skiba et al.