Senti17 at SemEval-2017 Task 4: Ten Convolutional Neural Network Voters for Tweet Polarity Classification
Labex Observatoire de la vie littéraire (OBVIL)（文学观察实验室（OBVIL））；Laboratoire d’Informatique de Paris 6 (LIP6)（巴黎第六大学计算机实验室（LIP6））；Pierre and Marie Curie University（皮埃尔和玛丽·居里大学）
英文摘要：
This paper presents Senti17 system which uses ten convolutional neural networks (ConvNet) to assign a sentiment label to a tweet. The network consists of a convolutional layer followed by a fully-connected layer and a Softmax on top. Ten instances of this network are initialized with the same word embeddings as inputs but with different initializations for the network weights. We combine the results of all instances by selecting the sentiment label given by the majority of the ten voters. This system is ranked fourth in SemEval-2017 Task4 over 38 systems with 67.4%
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
