A Model for Classifying Social Commerce Texts Using Deep Learning

With the rapid expansion of online commerce, a significant volume of data related to these activities is generated and shared daily on social media platforms. Analyzing and processing these data can have numerous applications in enhancing and strengthening social commerce. One such processing task is the classification of social commerce texts, which has notable effects in areas such as better customer experience management, online advertisement generation, and increasing customer demand. In this paper, we propose a model for classifying social commerce texts using deep learning and relevant pre-trained language models. This model first utilizes a pre-trained language model to extract text feature vectors and then uses them for accurate text classification. The results obtained from applying the proposed model to benchmark datasets show that the introduced classification algorithm performs well in classifying social commerce texts, with an average precision score of ۰.۷۲۵ and an average recall score of ۰.۷۰۸.

Keywords:

Text Classification , social commerce , Deep Learning , Natural Language Processing , Machine Learning