2015/06/30 by Bilal Hayat Butt, Muhammad Rafi, Butt, Bilal Hayat +9
Computer Science · #Advanced Malware Detection Techniques #Digital Libraries (cs.DL) #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Software Engineering Research #Software Testing and Debugging Techniques #cs.DL #cs.IR
paper · pdf · doi:10.48550/arxiv.1506.08966
arxiv created 2015/06/30 · openalex publication_date 2015/06/30 · arxiv updated 2015/07/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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 Naïve-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.