In this research, we propose a deep learning method for predicting the success of social media influencer collaboration. The main idea is to predict using audience perception whether the collaboration between a pair of social media influencers will be successful. Each social media influencer is referred to as a brand, while the audience comments is considered as consumer perception. This novel framework will aggregate audience comments using the Bidirectional Encoder Representations from Transformers (BERT) model to represent a social media influencer, and then leverage the neural network model to classify a collaboration into success and failure. In this study, we evaluate our proposed technique with a dataset collected from YouTube. Our empirical results demonstrate the effectiveness of our proposed technique, which outperforms all of the benchmark models.
Chen, Yu-Yuan; Lai, Po-Lin; Chen, Shih-Yu; Lo, Liang-Wei; Chen, Chih-Yun; and Wei, Chih-Ping, "Partner Up: A Deep Learning Method for Predicting the Success of Social Media Influencer Collaboration" (2020). PACIS 2020 Proceedings. 39.
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