stands for Digital Object Identifier
and is the unique identifier for objects on the internet. It can be used to create persistent link and to cite articles.
Using DOI as a persistent link
To create a persistent link, add「http://dx.doi.org/」
before a DOI.
For instance, if the DOI of an article is 10.5297/ser.1201.002 , you can link persistently to the article by entering the following link in your browser: http://dx.doi.org/ 10.5297/ser.1201.002 。
The DOI link will always direct you to the most updated article page no matter how the publisher changes the document's position, avoiding errors when engaging in important research.
Cite a document with DOI
When citing references, you should also cite the DOI if the article has one. If your citation guideline does not include DOIs, you may cite the DOI link.
DOIs allow accurate citations, improve academic contents connections, and allow users to gain better experience across different platforms. Currently, there are more than 70 million DOIs registered for academic contents. If you want to understand more about DOI, please visit airiti DOI Registration （ doi.airiti.com ） 。
- Amjad, A., Jefferson, E., & Dragomir, R. (2013, June). Purpose and Polarity of Citation: Towards Nlp-based Bibliometrics. Paper presented at the Proceedings of the 2013 conference of the North American chapter of the association for computational linguistics: Human language technologies, Atlanta, Georgia.
- Bertin, M., & Atanassova, I. (2014). A Study of Lexical Distribution in Citation Contexts Through the IMRaD Standard. PloS Negl. Trop. Dis, 1(200,920), 83,402.
- Bertin, M., Atanassova, I., Gingras, Y., & Larivière, V. (2016). The Invariant Distribution of References in Scientific Articles. Journal of the Association for Information Science and Technology, 67(1), 164-177.
- Bertin, M., Atanassova, I., Sugimoto, C., & Lariviere, V. (2016). The Linguistic Patterns and Rhetorical Structure of Citation Context: An Approach Using N-grams. Scientometrics, 109(3), 1417-1434.
- Bhagavatula, C., Feldman, S., Power, R., & Ammar, W. (2018, June). Content-Based Citation Recommendation. Paper presented at the Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), New Orleans, Louisiana.
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