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Visualizing Language and Aging From 2013-2022

  • Xueyan Li

    Xueyan Li is an associate professor at the School of Foreign Languages, Dalian University of Technology. Her research focuses on psycholinguistics and cognitive neurolinguistics.

    , Tianyi Chen

    Tianyi Chen is a graduate student at the School of Foreign Languages, Dalian University of Technology. His research focuses on psycholinguistics and cognitive neurolinguistics.

    , Hanning Guo

    Hanning Guo is an associate professor at the School of International Education, Dalian University of Technology. Her research focuses on Scientometrics and Teaching Chinese to the Speakers of Other Languages.

    and Huili Wang

    Huili Wang (corresponding author) is a professor at the School of Foreign Languages, Hangzhou City University and the Chief Expert in the Key Hangzhou Collaborative Innovation Institute of Language Services. Her research focuses on psycholinguistics and cognitive neurolinguistics.

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Published/Copyright: December 7, 2024
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Abstract

Declining cognitive abilities can be a concomitant of advanced age. As language is closely associated with cognitive abilities, changes in language abilities can be an important marker of changes in cognitive abilities. The current study is to review cognitive studies of language and aging by first identifying and exploring the major clusters and pivotal articles and then detecting emerging trends. Data of 3, 266 articles on language and aging from 2013 to 2022 were collected from the Web of Science Core Collection database. Adopting Document Co-citation Analysis, Freeman’s betweenness centrality metric (Freeman, 2002) and Kleinberg’s burst detection algorithm (Kleinberg, 2002), we explored major clusters, pivotal articles and emerging trends in this field. Cognition appears to be the most remarkable cluster. Bilingualism, speech production, listening effort, and reading comprehension are other major active clusters in a certain period. The most recent active cluster concerns the studies of Alzheimer’s disease. Articles serving as pivotal points concentrate on cognitive studies of the Framework for Understanding Effortful Listening (FUEL), the new Ease of Language Understanding model (EUL) and a hierarchical multi-representational generative framework of language comprehension. The progress in statistical methods, the relationship between language and cognitive impairment and the relationship between language abilities and cognition are the emerging trends. These emerging trends will provide some insights into how cognitive abilities influence language abilities in aging.

About the authors

Xueyan Li

Xueyan Li is an associate professor at the School of Foreign Languages, Dalian University of Technology. Her research focuses on psycholinguistics and cognitive neurolinguistics.

Tianyi Chen

Tianyi Chen is a graduate student at the School of Foreign Languages, Dalian University of Technology. His research focuses on psycholinguistics and cognitive neurolinguistics.

Hanning Guo

Hanning Guo is an associate professor at the School of International Education, Dalian University of Technology. Her research focuses on Scientometrics and Teaching Chinese to the Speakers of Other Languages.

Huili Wang

Huili Wang (corresponding author) is a professor at the School of Foreign Languages, Hangzhou City University and the Chief Expert in the Key Hangzhou Collaborative Innovation Institute of Language Services. Her research focuses on psycholinguistics and cognitive neurolinguistics.

Acknowledgments

This work was supported by the National Social Science Foundation of China (Grant No. 21BYY102).

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Published Online: 2024-12-07
Published in Print: 2024-11-26

© 2024 BFSU, FLTRP, Walter de Gruyter, Cultural and Education Section British Embassy

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