README.md

Aicyber SemEval 2016 i-vector

This repository contains the aicyber's system for SemEval 2016 Task 4A.

SemEval 2016 Task 4A

This task is sentiment analysis in tweeets. It focused on classifying tweets into 3 classes: positive,negative or neutral sentiment.

Two systems are included:

1. system based on vector space model

2. system based on i-vector

[Prerequisites] (./System_2/prerequisites.md)

Kindly cite this paper if you use the code:

Steven Du and Xi Zhang. 2016. Aicyber at SemEval-2016 Task 4: i-vector based sentence representation. In Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval 2016), San Diego, US

@InProceedings{SemEval:2016:task4,
  author    = {Steven Du and Zhang Xi},
  title     = {Aicyber at {SemEval}-2016 Task 4: i-vector based sentence representation},  booktitle = {Proceedings of the 10th International Workshop on Semantic Evaluation},
  series    = {SemEval '16},
  month     = {June},
  year      = {2016},
  address   = {San Diego, California},
  publisher = {Association for Computational Linguistics},
}