Senti17 at SemEval-2017 Task 4: Ten Convolutional Neural Network Voters for Tweet Polarity Classification

May 04, 2017 ยท Declared Dead ยท ๐Ÿ› International Workshop on Semantic Evaluation

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Authors Hussam Hamdan arXiv ID 1705.02023 Category cs.CL: Computation & Language Citations 12 Venue International Workshop on Semantic Evaluation Last Checked 5 months ago
Abstract
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%
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