Mapping the Knowledge Domain of Text Inferencing: A Bibliometric Analysis

Mapping the Knowledge Domain of Text Inferencing: A Bibliometric Analysis

Zilong Zhong
DOI: 10.4018/IJTIAL.330017
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Abstract

Text inferencing is a critical factor that would affect discourse comprehension. Growing attention has been paid to the research on inferential processing during text reading, with numerous papers on this topic published in recent decades. To gain a bibliographic landscape of inferential processing during discourse reading, co-citation analysis, cluster interpretations, and citation bursts analysis were conducted via CiteSpace based on the data from the Web of Science (WoS) Core Collection of Thomson Reuters from 2001 to 2021. The results reveal that (1) reading comprehension and working memory are fairly popular topics in recent decades; (2) research exploring predictive inferences, bridging inferences, and causal inferences have been paid much attention; and (3) predictive inference, eye movement, and listening comprehension may be attractive in future studies.
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Methods

Data Collection

A bibliometric analysis is a systematic approach that employs computer-assisted techniques to identify the core research or authors, and their relationships by scrutinizing publications pertaining to a particular topic or field (De Bellis, 2009). The two primary databases utilized for bibliometric analysis are Web of Science (WOS) and Scopus (Singh et al., 2021). Although both databases are widely used, WOS is known for its more stringent standards and has a 99.11% overlap with Scopus in terms of indexed journals (Singh et al., 2021). Consequently, the published papers on inference processing in discourse comprehension during 2001-2021 were collected from the WoS Core Collection, consisting of Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Arts and Humanities Citation Index (A and HCI), Conference Proceedings Citation Index-Science (CPCI-S), Conference Proceedings Citation Index Social Science and Humanities (CPCI-SSH) as well as Emerging Sources Citation Index (ESCI). All collected bibliographic records were written in English. The search strategy and the inclusion criteria were detailed in Figure 1. The selection of search terms for this study is informed by the bibliometric analysis of lexical inferencing conducted by Yang et al. (2023). A total of 3,131 records were obtained from 1,306 journals distributed in 200 WoS categories. The current research attempted to focus on inference processing during text reading from the perspectives of linguistics, psychology, and neuroscience. As a result, 1,373 articles were extracted, and the categories involved are shown in Figure 2. Among the 16 categories, Linguistics, Psychology Experimental, Psychology Educational, and Language Linguistics involve the most articles, each accounting for more than 20 percent.

Figure 1.

The flowchart of the search strategy and selection process in this study

IJTIAL.330017.f01
Figure 2.

The categories involved in this study

IJTIAL.330017.f02

Instrument

The CiteSpace software program is a free Java application that analyzes and visualizes the literature of a specified scientific or knowledge domain, providing a visual gateway to the literature of scholarly publications. The program generates interactive visualizations from bibliographic information, particularly citation data from the WoS, which allows users to navigate and explore patterns and trends uncovered in scientific publications (Chen, 2006).

In this study, the knowledge domain associated with inference processing during text reading in the framework of linguistics, psychology, and neuroscience was explored to reveal critical references, identify research patterns and hotspots to predict emerging trends in the literature.

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