Analysis of Online Marketplace Data on Social Networks Using LSTM

In recent years, the users of the online marketplace on social networks are increased rapidly. The availability of online marketplace data has been created a great research scope for analyzing. The main concern of this paper is to understand and recognize the evolving characteristics of online marketplace real user's behavior on the social network. We used `Facepager' as an effective tool to capture the data from Facebook and applied LSTM Neural Network (NN) to classify positive and negative review and observe better accuracy. Our future work is to conduct an explainable attention-based LSTM to detect anomalous semantic information from social network data.