A Review of Different Word Embeddings for Sentiment Classification using Deep Learning

July 05, 2018 · The Cartographer · 🏛 arXiv.org

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"Title-pattern auto-detect: A Review of Different Word Embeddings for Sentiment Classification using Deep Learning"

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Authors Debadri Dutta arXiv ID 1807.02471 Category cs.IR: Information Retrieval Cross-listed cs.CL, cs.LG, stat.ML Citations 3 Venue arXiv.org Last Checked 4 days ago

Abstract

The web is loaded with textual content, and Natural Language Processing is a standout amongst the most vital fields in Machine Learning. But when data is huge simple Machine Learning algorithms are not able to handle it and that is when Deep Learning comes into play which based on Neural Networks. However since neural networks cannot process raw text, we have to change over them through some diverse strategies of word embedding. This paper demonstrates those distinctive word embedding strategies implemented on an Amazon Review Dataset, which has two sentiments to be classified: Happy and Unhappy based on numerous customer reviews. Moreover we demonstrate the distinction in accuracy with a discourse about which word embedding to apply when.