DFBICA: A new distributed approach for sentiment analysis of bibliographic citations

Sentiment analysis of citations in scientific papers is a new and interesting research area. In this paper, we focus on the problem of automatic identification of positive and negative sentiment polarity of citations in scientific papers. In this work, we conducted empirical research to investigate the classification of positive and negative citations. It is based on word vectors as a feature space, to which the examined citation context was mapped to. In order to handle with the huge amount of data, we have implemented our proposed approach in a distributed manner according to MapReduce paradigm through the Hadoop framework.