Global, International, and Cross Cultural Research in Info Systems (SIG CCRIS)
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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.
Recommended Citation
Vyas, Piyush; Liu, Jun; and Chauhan, Akhilesh, "An LSTM Based Approach for the Classification of Customer Reviews: An Exploratory Study" (2021). AMCIS 2021 Proceedings. 5.
https://aisel.aisnet.org/amcis2021/global_cross_cultural_is/global_cross_cultural_is/5
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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