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Citation analysis is one of the most frequently used methods in researchevaluation. We are seeing significant growth in citation analysis throughbibliometric metadata, primarily due to the availability of citation databasessuch as the Web of Science, Scopus, Google Scholar, Microsoft Academic, andDimensions. Due to better access to full-text publication corpora in recentyears, information scientists have gone far beyond traditional bibliometrics bytapping into advancements in full-text data processing techniques to measurethe impact of scientific publications in contextual terms. This has led totechnical developments in citation context and content analysis, citationclassifications, citation sentiment analysis, citation summarisation, andcitation-based recommendation. This article aims to narratively review thestudies on these developments. Its primary focus is on publications that haveused natural language processing and machine learning techniques to analysecitations.

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