ImpactCite: An XLNet-based Solution Enabling Qualitative Citation Impact Analysis Utilizing Sentiment and Intent

Dominique Mercier, Dominique Mercier, Syed Rizvi, Syed Rizvi, Vikas Rajashekar, Andreas Dengel, Andreas Dengel, Sheraz Ahmed

Abstract

Citations play a vital role in understanding the impact of scientific literature. Generally, citations are analyzed quantitatively whereas qualitative analysis of citations can reveal deeper insights into the impact of a scientific artifact in the community. Therefore, citation impact analysis including sentiment and intent classification enables us to quantify the quality of the citations which can eventually assist us in the estimation of ranking and impact. The contribution of this paper is three-fold. First, we provide ImpactCite, which is an XLNet-based method for citation impact analysis. Second, we propose a clean and reliable dataset for citation sentiment analysis. Third, we benchmark the well-known language models like BERT and ALBERT along with our proposed approach for both tasks of sentiment and intent classification. All evaluations are performed on a set of publicly available citation analysis datasets. Evaluation results reveal that ImpactCite achieves a new state-of-the-art performance for both citation intent and sentiment classification by outperforming the existing approaches by 3.44% and 1.33% in F1-score. Therefore, the evaluation results suggest that ImpactCite is a single solution for both sentiment and intent analysis to better understand the impact of a citation.

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Paper Citation


in Harvard Style

Mercier D., Rizvi S., Rajashekar V., Dengel A. and Ahmed S. (2021). ImpactCite: An XLNet-based Solution Enabling Qualitative Citation Impact Analysis Utilizing Sentiment and Intent.In Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-484-8, pages 159-168. DOI: 10.5220/0010235201590168


in Bibtex Style

@conference{icaart21,
author={Dominique Mercier and Syed Rizvi and Vikas Rajashekar and Andreas Dengel and Sheraz Ahmed},
title={ImpactCite: An XLNet-based Solution Enabling Qualitative Citation Impact Analysis Utilizing Sentiment and Intent},
booktitle={Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2021},
pages={159-168},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010235201590168},
isbn={978-989-758-484-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - ImpactCite: An XLNet-based Solution Enabling Qualitative Citation Impact Analysis Utilizing Sentiment and Intent
SN - 978-989-758-484-8
AU - Mercier D.
AU - Rizvi S.
AU - Rajashekar V.
AU - Dengel A.
AU - Ahmed S.
PY - 2021
SP - 159
EP - 168
DO - 10.5220/0010235201590168