# A Decade of In-text Citation Analysis based on Natural Language Processing and Machine Learning Techniques: An overview of empirical studies

arXiv: https://arxiv.org/abs/2008.13020 · HTML: https://mlsanity.com/paper/2008.13020/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Aug 2020.

## Built on by (most cited first, 7 of 7)

- [MultiCite: Modeling realistic citations requires moving beyond the single-sentence single-label setting](https://mlsanity.com/paper/2107.00414/) (2021)
- [From Insights to Actions: The Impact of Interpretability and Analysis Research on NLP](https://mlsanity.com/paper/2406.12618/) (2024)
- [Cracking Double-Blind Review: Authorship Attribution with Deep Learning](https://mlsanity.com/paper/2211.07467/) (2022)
- [When Large Language Models Meet Citation: A Survey](https://mlsanity.com/paper/2309.09727/) (2023)
- [Citations are not opinions: a corpus linguistics approach to understanding how citations are made](https://mlsanity.com/paper/2104.08087/) (2021)
- [CausalCite: A Causal Formulation of Paper Citations](https://mlsanity.com/paper/2311.02790/) (2023)
- [Scaling In, Not Up? Testing Thick Citation Context Analysis with GPT-5 and Fragile Prompts](https://mlsanity.com/paper/2602.22359/) (2026)

## Abstract (arXiv)

Citation analysis is one of the most frequently used methods in research evaluation. We are seeing significant growth in citation analysis through bibliometric metadata, primarily due to the availability of citation databases such as the Web of Science, Scopus, Google Scholar, Microsoft Academic, and Dimensions. Due to better access to full-text publication corpora in recent years, information scientists have gone far beyond traditional bibliometrics by tapping into advancements in full-text data processing techniques to measure the impact of scientific publications in contextual terms. This has led to technical developments in citation context and content analysis, citation classifications, citation sentiment analysis, citation summarisation, and citation-based recommendation. This article aims to narratively review the studies on these developments. Its primary focus is on publications that have used natural language processing and machine learning techniques to analyse citations.