Sentiment analysis is an active area of research in natural language processing field. Prior research indicates numerous techniques have been used to perform the sentiment classification tasks which include the machine learning approaches. Deep learning is a specific type of machine learning that has been successfully applied in various field such as computer vision and various NLP tasks including sentiment analysis. This paper attempts to provide a bibliometric analysis of academic literature related to the sentiment analysis with deep learning methods which were retrieved from Scopus until the third quarter of 2020. We focus on the analysis of the research productivity in this field, the distribution of subject categories, the sources and types of the publications, their geographic distributions, the most prolific and impactful authors and institutions, the most cited papers and the trends of keywords. This study can help researchers and practitioners in keeping abreast with the global research trends in the area of sentiment analysis using deep learning approaches.