  Research is a continuous phenomenon. It is recursive in nature. Every
research is based on some earlier research outcome. A general approach in
reviewing the literature for a problem is to categorize earlier work for the
same problem as positive and negative citations. In this paper, we propose a
novel automated technique, which classifies whether an earlier work is cited as
sentiment positive or sentiment negative. Our approach first extracted the
portion of the cited text from citing paper. Using a sentiment lexicon we
classify the citation as positive or negative by picking a window of at most
five (5) sentences around the cited place (corpus). We have used Na\"ive-Bayes
Classifier for sentiment analysis. The algorithm is evaluated on a manually
annotated and class labelled collection of 150 research papers from the domain
of computer science. Our preliminary results show an accuracy of 80%. We assert
that our approach can be generalized to classification of scientific research
papers in different disciplines.

Information Retrieval;Digital Libraries