Explorations in sentiment mining for arabic and english tweets

Abstract

Assigning sentiment labels to documents is, at first sight, a standard multi-label classification task. As such, it seems likely that standard machine learning algorithms such as deep neural networks (DNNs) will provide an effective approach. We describe an alternative approach, involving the construction of a weighted lexicon of sentiment terms, which significantly outperforms the use of DNNs. The moral of the story is that DNNs are not a universal panacea, and that paying attention to the nature of the data that you are trying to learn from can be more important than trying out ever more powerful general purpose machine learning algorithms.