SemEval 2016 Task 4
Related Papers
aueb.twitter.sentiment at SemEval-2016 Task 4: A Weighted Ensemble of SVMs for Twitter Sentiment Analysis
This paper describes the system with which we participated in SemEval-2016 Task 4 (Sen- timent Analysis in Twitter) and specifically the Message Polarity Classification subtask. Our system is a weighted …...
NRU-HSE at SemEval-2016 Task 4: Comparative Analysis of Two Iterative Methods Using Quantification Library
In many areas, such as social science, politics or market research, people need to track sentiment and their changes over time. For sentiment analysis in this field it is more …...
QCRI at SemEval-2016 Task 4: Probabilistic Methods for Binary and Ordinal Quantification
We describe the systems we have used for participating in Subtasks D (binary quan- tification) and E (ordinal quantification) of SemEval-2016 Task 4 “Sentiment Analysis in Twitter”. The binary quantification …...
SemEval-2016 Task 4: Sentiment Analysis in Twitter
This paper discusses the fourth year of the ”Sentiment Analysis in Twitter Task”. SemEval-2016 Task 4 comprises five sub- tasks, three of which represent a significant departure from previous editions. …...
SwissCheese at SemEval-2016 Task 4: Sentiment Classification Using an Ensemble of Convolutional Neural Networks with Distant Supervision
In this paper, we propose a classifier for predicting message-level sentiments of En- glish micro-blog messages from Twitter. Our method builds upon the convolutional sen- tence embedding approach proposed by …...
UNIMELB at SemEval-2016 Tasks 4A and 4B: An Ensemble of Neural Networks and a Word2Vec Based Model for Sentiment Classification
This paper describes our sentiment clas- sification system for microblog-sized doc- uments, and documents where a topic is present. The system consists of a soft- voting ensemble of a word2vec …...
VCU-TSA at Semeval-2016 Task 4: Sentiment Analysis in Twitter
The aim of this paper is to produce a method- ology for analyzing sentiments of selected Twitter messages, better known as Tweets. This project elaborates on two experiments carried out …...