  Celebrity Endorsement is one of the most significant strategies in brand
communication. Nowadays, more and more companies try to build a vivid
characteristic for themselves. Therefore, their brand identity communications
should accord with some characteristics as humans and regulations. However, the
previous works mostly stop by assumptions, instead of proposing a specific way
to perform matching between brands and celebrities. In this paper, we propose a
brand celebrity matching model (BCM) based on Natural Language Processing (NLP)
techniques. Given a brand and a celebrity, we firstly obtain some descriptive
documents of them from the Internet, then summarize these documents, and
finally calculate a matching degree between the brand and the celebrity to
determine whether they are matched. According to the experimental result, our
proposed model outperforms the best baselines with a 0.362 F1 score and 6.3% of
accuracy, which indicates the effectiveness and application value of our model
in the real-world scene. What's more, to our best knowledge, the proposed BCM
model is the first work on using NLP to solve endorsement issues, so it can
provide some novel research ideas and methodologies for the following works.
