Abstract-Scientific papers generally include citations to external sources such as journal articles, books, or Web links to refer to works that are related in an important way to the research. The reason for the citation appears within the sentences surrounding the citation tag in the body text, and represents the relationship between the citation and cited works as supportive, contrastive, corrective, etc. This could be an important clue for researchers seeking relevant previous work or approaches for a certain research purpose. We propose to develop an automated method to identify the citing author's sentiments toward the cited external sources expressed in citation sentences using machinelearning techniques and linguistic cues. As a preliminary study, this paper presents a support vector machine (
In REF , Kim and Thoma developed an automated sentiment detection method using machine learning techniques and linguistic clues.
Automated classification of author's sentiments in citation using machine learning techniques: A preliminary study
2015 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)
2015 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)
Computer Science