Global, International, and Cross Cultural Research in Info Systems (SIG CCRIS)

Paper Type

ERF

Paper Number

1509

Description

Significant research has been conducted to address the problem of identification and elimination of malicious content. The credibility of such information is always in question, especially in the E-commerce domain. This research proposes a classification model that automatically classifies customer reviews as credible or non-credible. This model encompasses a Long Short-Term Memory (LSTM) as a classification technique. The preliminary results have shown the potential of our model to classify customer reviews as credible / non-credible based on textual features.

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Aug 9th, 12:00 AM

An LSTM Based Approach for the Classification of Customer Reviews: An Exploratory Study

Significant research has been conducted to address the problem of identification and elimination of malicious content. The credibility of such information is always in question, especially in the E-commerce domain. This research proposes a classification model that automatically classifies customer reviews as credible or non-credible. This model encompasses a Long Short-Term Memory (LSTM) as a classification technique. The preliminary results have shown the potential of our model to classify customer reviews as credible / non-credible based on textual features.

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