Identifying Citation Sentiment and its Influence while Indexing Scientific Papers

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dc.contributor.authorGhosh, Souvick
dc.contributor.authorShah, Chirag
dc.date.accessioned2020-01-04T07:40:19Z
dc.date.available2020-01-04T07:40:19Z
dc.date.issued2020-01-07
dc.description.abstractSentiment analysis has proven to be a popular research area for analyzing social media texts, newspaper articles, and product reviews. However, sentiment analysis of citation instances is a relatively unexplored area of research. For scientific papers, it is often assumed that the sentiment associated with citation instances is inherently positive. This assumption is due to the hedged nature of sentiment in citations, which is difficult to identify and classify. As a result, most of the existing indexes focus only on the frequency of citation. In this paper, we highlight the importance of considering the sentiment of citation while preparing ranking indexes for scientific literature. We perform automatic sentiment classification of citation instances on the ACL Anthology collection of papers. Next, we use the sentiment score in addition to the frequency of citation to build a ranking index for this collection of scientific papers. By using various baselines, we highlight the impact of our index on the ACL Anthology collection of papers. Our research contributes toward building more sentiment sensitive ranking index which better underlines the influence and usefulness of research papers.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2020.307
dc.identifier.isbn978-0-9981331-3-3
dc.identifier.urihttp://hdl.handle.net/10125/64049
dc.language.isoeng
dc.relation.ispartofProceedings of the 53rd Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectData Analytics, Data Mining and Machine Learning for Social Media
dc.subjectcitation sentiment analysis
dc.subjectdecision analytics
dc.subjectmachine learning
dc.subjectranking and indexing
dc.subjectscientometrics
dc.titleIdentifying Citation Sentiment and its Influence while Indexing Scientific Papers
dc.typeConference Paper
dc.type.dcmiText

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