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Abstract

This paper provides a diachronic and bibliometric overview of register studies in the past decade. A total of 545 articles were selected from the field of linguistics of the database of Web of Science Core Collection for the analysis. For bibliometric analysis, CiteSpace and VOSViewer were used in order to reveal the co-citation analysis, the high-frequency keywords, keyword clusters, and the timeline of the keyword network in register studies. The results are summarized as follows. First, register studies have been gaining considerable academic attention in the examined years. Second, the major theoretical origins of register studies were text linguistics, systemic functional linguistics, and sociolinguistics. Third, corpus analysis and discourse analysis are the main research methods, followed by genre analysis, and conversation analysis. Fourth, important research themes were extracted and classified based on the following dimensions of register studies, namely, linguistic features, register types, register variations and pragmatic function. Furthermore, Teaching and education was an important dimension in register studies. Fifth, the recent research tended to focus on the register variations caused by the audiences, and corpus analysis and discourse analysis were widely used for broad analyses in different register studies. This bibliometric analysis also shows that online registers have become the research hotspot.

Plain Language Summary

A Bibliometric Analysis of Register Studies (2012-2021)

Research purpose: This paper provides a diachronic and bibliometric overview of register studies in the past decade. Methods: bibliometric analysis. Conclusion: First, register studies have been gaining considerable academic attention in the examined years. Second, the major theoretical origins of register studies were text linguistics, systemic functional linguistics, and sociolinguistics. Third, corpus analysis and discourse analysis are the main research methods, followed by genre analysis, and conversation analysis. Fourth, important research themes were extracted and classified based on the following dimensions of register studies, namely, linguistic features, register types, register variations and pragmatic function. Furthermore, Teaching and education was an important dimension in register studies. Fifth, the recent research tended to focus on the register variations caused by the audiences, and corpus analysis and discourse analysis were widely used for broad analyses in different register studies. Implication: The research may be a useful resource for novice researchers and established scholars in the field, and perhaps also critical in assisting journal editors to continue to promote theoretical or methodological advances in the field.

Keywords

Introduction

Register refers to “a variety of language, corresponding to a variety of situation,” with situation interpreted “by means of a conceptual framework using the terms field, tenor and mode” (Halliday, 1989, pp. 29, 38). Register can be distinguished for “their audiences, mediums (e.g., spoken or written mode), interactivity, production circumstances, communicative purposes” (Seoane & Biber, 2021, p. 2).

Register analysis focuses on “the functional relationships between linguistic patterns of use and the situational characteristics of registers” (Biber & Conrad, 2019, p. 7), including three major components, “the situational characteristics, the pervasive linguistic features, and the communicative functions that explain why these linguistic features occur in this situational context” (Biber & Conrad, 2019, p. 31).

Early studies on register analysis provided linguistic accounts of a single register. Later, more attention has been paid to investigate register variation, which “typically compare two or more registers to identify meaningful patterns of variation that are mediated by register, such as differences across speech and writing (e.g., Biber, 1988; Biber et al., 2011)” (Goulart et al., 2020, p. 7.3). Research on register variation thus emphasizes comparing the linguistic characteristics in different texts and exploring the linguistic co-occurrence patterns, usually interpreting the variations relative to the situational characteristics of those registers.

Some previous reviews of register studies have been conducted to provide insights into the field, such as the main research methods of register studies over the past 25 years (Sardinha & Pinto, 2014) and register studies from the perspective of linguistics (Goulart et al., 2020). The previous reviews of the subject field are mostly introspective experience and lack empirical analysis based on authoritative data, and it seems that an integrated review of register studies from the bibliometric perspective is in need. With the use of visual analytic tools CiteSpace and VOSviewer, this study aims to conduct a diachronic and bibliometric overview of articles published in the Web of Science Core Collection database to present a quantitative analysis of the current status and emerging trends in register studies. More specifically, the study seeks to answer the following research questions:

RQ1. What are the general characteristics (publication trend, productive authors, productive institutions, and countries) in the field of register studies?

RQ2. What are the major theoretical frameworks in register studies?

RQ3. What are the important research methods in register studies?

RQ4. What are the main research themes in register studies?

RQ5. What are the emerging trends in register studies?

Data and Methodology

The data analysis procedure consists of CiteSpace and VOSviewer-based bibliometric analysis. As one of the widely-used bibliometric tools, CiteSpace used in the study is “a Java application for analyzing and visualizing co-citation networks” (Chen, 2004, p. 363). It provides different bibliometric analyses, including the overall structure of the keyword network, the author network, and the network clusters, those help researchers identify the current situation and emerging research trends in a specific field (Mou et al., 2019). For instance, Liu and Hu (2021) used CiteSpace to explore the major research themes and historical trends in English-for-specific-purposes (ESP) research with the support of the co-citation analysis.

VOSviewer is a new mapping technique, “which stands for visualization of similarities” (van Eck et al., 2010, p. 2405), with the function of Citation of sources, Co-authorship of authors, Co-occurrence of keywords, and Co-citation of cited authors to identify main publication venues, productive authors, influential scholars and dominant research themes in the area of register studies. In addition, VOSviewer-based bibliometric analysis helps pinpoint the strands of linguistics. For example, Yilmaz et al. (2022) adopted VOSviewer to discuss the studies of foreign language teaching in early childhood education.

As the visual analytic approach of the network, the advantage of CiteSpace and VOSviewer-based bibliometric analysis can be utilized to comprehensively insight into the research structure and grasp the current research focus based on statistical quantitative profiling and reliable databases (Xiao & Li, 2021, p. 485). For instance, Xiao and Li (2021) employed CiteSpace and VOSviewer-based methods to explore critical discourse analysis’s research status and implications. Figure 1 is the research steps of bibliometric analysis of register studies.

Figure 1.

Steps of bibliometric analysis of register studies.

Data Collection

The bibliometric information of the research articles was retrieved in the Web of Science Core Collection on February 08, 2022. Table 1 presented the information of queries presented. To be more specific, the aim of the information retrieval was to search the articles related to register studies in the research area of linguistics that was published in English between 2012 and 2021. The queries identified a total of 785 articles and their bibliometric records, including such information as article titles, journal titles, publishing years, keywords, abstracts, citations, etc., were downloaded for further analyses.

Table 1.

Retrieval Queries.

(From Web of Science Core Collection)

(TS = register OR register analysis) AND LANGUAGE: (English) AND DOCUMENT TYPES: (Article)

Refined by: WEB OF SCIENCE CATEGORIES: (Linguistics OR Language Linguistics)

Timespan: 2012–2021. Indexes: SSCI.

Inclusion and Exclusion Criteria

To diminish the influences caused by researcher bias on the study, the main elements of each article, including the titles, keywords, and abstracts, were manually coded by two researchers to eliminate studies that are not relevant to register studies. First, articles were excluded if they are book reviews, literature reviews, and book chapters. Next, articles concerning topics that are not relevant to register studies, such as pitch register, and “register” used as a verb were excluded. Both authors repeatedly reviewed all the options to ensure that all decisions were reached in agreement. Overall, a total of 545 research articles were retained for the following analysis after excluding those irrelevant ones.

Data Analysis

The following data analysis procedures were adopted. First, to present the general characteristics in the field of register studies, the bibliometric information was detected based on the publication trend, main publication venues, productive authors, productive institutions, and countries. Moreover, the software SPSS was used for linear regression analysis to explore the relationship between publication year and number of articles.

Second, to identify the major theoretical frameworks in the area of register studies, the co-citation analysis (the journal co-citation analysis, author co-citation analysis, document co-citation analysis) generated by both CiteSpace and VOSviewer was utilized and systematically analyzed.

Third, the keyword list of 292 keywords (freq. ≥ 2) was produced using CiteSpace and 93 keywords (freq. ≥ 5) using VOSviewer (Table 2 listing those being at least 0.02 centralities in CiteSpace and at least 30 link strength in VOSviewer) to pinpoint the important research methods of register studies. At first, the same or semantically relevant keywords were combined, for instance, “multi-dimensional analysis” and “multidimensional analysis.” Then, the keyword list was checked based on classifications of research methods in linguistics indexed in Phakiti et al. (2018) and McKinley and Rose (2020), such as corpus analysis, to ascertain the repeatedly used research methods in register studies.

Table 2.

Keyword List (Centrality ≥ 0.02, Link-strength ≥ 30).

CiteSpace				VOSviewer
Rank	Keywords	Count	Centrality	Rank	Keywords	Occurrences	Link-strength
1	Language	80	0.53	1	Language	83	185
2	English	53	0.34	2	Register	69	160
3	Discourse	20	0.10	3	English	57	156
4	Register variation	22	0.09	4	Register variation	29	59
5	Corpus linguistics	20	0.07	5	Discourse	29	59
6	Corpus	21	0.06	6	Corpus	23	53
7	Acquisition	13	0.06	7	Lexical bundle	12	50
8	Multi-dimensional analysis	13	0.05	8	Academic writing	17	42
9	Spoken	12	0.04	9	Academic language	11	42
10	Academic language	10	0.04	10	Corpus linguistics	23	42
11	Student	8	0.04	11	Stance	15	41
12	Classroom	5	0.04	12	Identity	18	42
13	Text	7	0.03	13	Genre	15	38
14	Communication	7	0.03	14	Multi-dimensional analysis	13	38
15	Address	2	0.03	15	Acquisition	13	35
16	Academic writing	15	0.02	16	Spanish	18	35
17	Identity	14	0.02	17	Indexicality	9	32
18	Lexical bundle	10	0.02	18	Sociolinguistics	9	31
19	Discourse marker	7	0.02	19	Translation	12	31
20	Construction	7	0.02	20	Spoken	12	30
21	Academic discourse	5	0.02
22	Literacy	5	0.02
23	Instruction	5	0.02
24	Genre	5	0.02
25	American	4	0.02
26	Chinese	4	0.02
27	Pattern	4	0.02
28	Repair	2	0.02

Note. The keywords generated by CiteSpace were ranked according to the centrality, while VOSviewer’s keywords were ranked by link strength.

Fourth, the high-frequency keyword was further surveyed to confirm the main research themes. Keywords with a frequency of five or more in VOSviewer were retained (93 keywords). Then, the same or semantically relevant keywords that occurred in CiteSpace were searched and retained (69 of 292 keywords). The sharing keywords that occurred in both two tools may best represent important research themes. Next, the following types of keywords were excluded: (1) keywords that were too general to be considered as research themes, such as “language”; (2) keywords that were related to the research targets of this study, such as “register analysis”; (3) keywords that were related to other research questions, such as “corpus analysis.” Finally, 87 keywords (48 keywords from CiteSpace and 39 keywords from VOSviewer) were left for further analyses based on Biber and Conrad’s (2019) analytical framework on register analysis (See Section 3.4).

Fifth and lastly, the keyword clusters generated by CiteSpace were explored to reveal the emerging trends of register studies. To offer a diachronic perspective on the developments of register studies, the timeline visualization of the keyword network generated by CiteSpace was also displayed and analyzed.

Results and Discussion

General Characteristics

In this section, the publication trend, productive authors, productive institutions, and countries in register studies are discussed.

Publication Trend

Table 3 presents the number of academic journal publications by year between 2012 and 2021. A linear regression model was used to “examine the trend of a group of values on a time series” (Lin & Lei, 2020, p. 4) and was fit to show the publication trend. The results of a linear regression model show a steady increase in the number of articles published in the examined years (F = 47.541, p = .000, R-squared = .856, Adjusted R-squared = .838). As shown in Figure 2, the publication trend shows that register studies have been gaining considerable academic attention in the examined years.

Table 3.

Number of Publications Published Per Year.

Year	Number of publications
2012	36
2013	35
2014	37
2015	50
2016	48
2017	48
2018	70
2019	58
2020	83
2021	80
Total	545

Figure 2.

Publication trend (2012–2021).

Table 4 and Figure 3 present the journals which publications are at least 10 relevant articles. Most journals are dominant ones in the field of linguistics, such as Journal of English for Academic Purposes and Journal of Pragmatics. The most popular journals can be broadly categorized into three research areas as journal titles suggest. Register studies are conducted based on language teaching and education (i.e., Journal of English for Academic Purposes, English for Specific Purposes, Linguistics and Education and Iberica), corpus linguistics (i.e., International Journal of Corpus Linguistics, Corpus Linguistics and Linguistic Theory) and pragmatics (i.e., Journal of Pragmatics). Moreover, some conduct interdisciplinary research in linguistics, anthropology and communication, such as Journal of Linguistic Anthropology, Language and Communication. Along with the general-linguistics journals such as Lingua, some journals reflect the target language in register studies, such as English language studies (i.e., Journal of English Linguistics, English Language and Linguistics), and Spanish language studies (i.e., Revista signos, Iberica).

Table 4.

Publication Venues (Number of publications ≥ 10).

Rank	Journals	Number of publications	Rank	Journals	Number of publications
1	Journal of English for Academic Purposes	23	7	Journal of Linguistic Anthropology	12
2	International Journal of Corpus Linguistics	23	8	Revista signos	12
3	Journal of Pragmatics	20	9	Journal of English Linguistics	11
4	Linguistics and Education	16	10	Language and Communication	11
5	Corpus Linguistics and Linguistic Theory	13	11	English Language and Linguistics	10
6	English for Specific Purposes	12	12	Iberica	10
-	-	-	13	Lingua	10

Figure 3.

Publication venues trend (2012–2021).

Productive Authors, Institutions, and Countries

Table 5 presents the most productive authors in register studies. The most productive authors are Douglas Biber (12 articles), Haidee Kruger (nine articles), and Jesse Egbert (eight articles). And the following authors are Bertus Van Roody (seven articles), Shelly Staples (six articles), and Yao Xinyue (six articles).

Table 5.

Productive Authors (number of publications > 5).

Rank	Authors	Number of publications	Rank	Authors	Number of publications
1	Biber, Douglas	12	4	Van Rooy, Bertus	7
2	Kruger, Haidee	9	5	Staples, Shelly	6
3	Egbert, Jesse	8	6	Yao, Xinyue	6

As shown in Figure 4, significant contributions have been made by several universities, such as Macquarie University (17 articles), Northern Arizona University (13 articles), the Hongkong Polytechnic University (11 articles), and North-West University (10 articles). Figure 5 illustrates the most productive countries in register studies in the examined years. The United States yielded 120 articles, followed by Spain (55 articles), and China (51 articles). The top five productive countries contributed more than 50% of publications in register studies.

Figure 4.

Major research institution.

Figure 5.

Major countries.

Major Theoretical Frameworks

Co-citation analysis is grounded on a hypothesis that “the more frequently the pair are co-cited, the more likely they address the same subject matter and/or use similar methodology” (Liu & Hu, 2021, p. 100), which has been widely used to demonstrate the relationships and structure of a scholarly field in terms of authors, articles, journals, or keywords (Hu et al., 2011, p. 658).

Thus, the main theoretical frameworks of register studies are presented based on co-citation analysis, including journal co-citation (hereinafter abbreviated as JCA), author co-citation (ACA), and document co-citation (DCA) to explore the major theories and key concepts in register studies.

JCA can help define the structure of a research field in which academic journals are an important means of communication (Hu et al., 2011, p. 658). The journal co-citation frequency list and journal co-citation network were generated by CiteSpace and VOSviewer as shown in Table 6 and Figure 6.

Table 6.

Journal Co-citation Frequency List (Freq. ≥ 50).

Rank	Journal	Count	Rank	Journal	Count
1	Journal of Pragmatics	134	10	Modern Linguistics	67
2	Applied Linguistics	133	11	Linguistics	66
3	Language	116	12	Journal of Sociolinguistics	64
4	Language in Society	96	13	Language Learning	59
5	International Journal of Corpus Linguistics	89	14	Discourse Studies	55
6	Journal of English for Academic Purposes	80	15	Corpus Linguistics and Linguistic Theory	53
7	TESOL Quarterly	77	16	Lingua	51
8	Language and Communication	76	17	World Englishes	50
9	English for Specific Purposes	67

Figure 6.

Journals co-citation network.

As can be seen from Figure 6, except for the journal Thesis which cannot involve the field of linguistic studies, the other highly co-cited journals (see Table 6) can generally be divided into four strands, namely pragmatics, sociolinguistics, corpus linguistics, and language teaching and education. This classification can be confirmed not only by the titles of the journals, such pragmatics-oriented journal as Journal of Pragmatics and sociolinguistics-oriented journals as Language in Society, Journal of Sociolinguistics, but also by the keyword list shown in Table 2, such as “identity” and “stance,” which are repeatedly discussed topics in pragmatics and sociolinguistics.

ACA is a common approach to mapping knowledge domains and describing scientific knowledge structures (Bu et al., 2020). Table 7 and Figure 7 present the list of the highly cited authors (freq. ≥ 50) and author co-citation network. Douglas Biber is the most co-cited author in the field, followed by Michel Halliday, Asif Agha, Ken Hyland, Susan Conrad, and William Labov, indicating that their papers played an important role in register studies. A more in-depth analysis of the highly cited authors’ publications reveals the main theoretical foundations of register studies, such as text linguistics (i.e., Biber, Conrad), systemic functional linguistics (SFL, i.e., Halliday), anthrolinguistics (i.e., Agha), and sociolinguistics (i.e., Labov).

Table 7.

Author Co-citation Frequency List (Freq. ≥ 50).

Rank	Authors	Count	Rank	Authors	Count
1	Biber, D.	295	4	Hyland, K.	61
2	Halliday, M.	201	5	Conrad, S.	61
3	Agha, A.	81	6	Labov, W.	56

Figure 7.

Author co-citation network.

DCA is believed that constantly and frequently cited research sets the knowledge foundation of a given field (Huan & Guan, 2020, p. 10). Table 8 and Figure 8 display the most highly cited references in register studies, Moreover, the centrality score indicates that they were the most influential ones among the landmark publications in register studies. Similar to the findings of author co-citation analysis, Biber was the most influential author in register studies, who contributed six of the most-cited references (Biber, 2014; Biber et al., 2011, 2016; Biber & Conrad, 2019; Biber & Egbert, 2016; Biber & Gray, 2013).

Table 8.

Co-citation Frequency List of References (Rank 10).

Rank	Cited reference	Central	Count
1	Biber (1993). Grammatical Complexity in Academic English: Linguistic Change in Writing.	0.08	9
2	Biber (2014). Using multi-dimensional analysis to explore cross-linguistic universals of register variation.	0.05	7
3	Biber (2010). Should we use characteristics of conversation to measure grammatical complexity in L2 writing development?	0.05	6
4	R Core Team (2016). R: A Language and Environment for Statistical Computing.	0.04	8
5	Parkinson and Musgrave (2014). Development of noun phrase complexity in the writing of English for Academic Purposes students.	0.04	6
6	Staples et al. (2016). Academic Writing Development at the University Level: Phrasal and Clausal Complexity Across Level of Study, Discipline, and Genre.	0.03	4
7	Biber and Gray (2013). Being Specific about Historical Change: The Influence of Sub-Register.	0.03	6
8	Biber (1993). Predicting Patterns of Grammatical Complexity Across Language Exam Task Types and Proficiency Levels.	0.02	6
9	Biber (2019). Register, Genre, Style.	0.02	3
10	Larsson and Kaatari (2020). Syntactic complexity across registers: Investigating (in)formality in second-language writing.	0.02	3

Figure 8.

Document co-citation network.

Among them, the most-cited reference in register studies is the one by Biber and Egbert (2016). Biber and Egbert’s (2016) research used multi-dimensional analysis (hence after abbreviated MDA) to explore grammatical complexity in academic English. MDA was also adopted in Biber’s (2014) research.

Moreover, Biber and Gray (2013) analyzed two case studies from the perspectives of historical linguistic change of register differences, which provided a methodology to compare registers in corpus-based historical research. Biber’s studies adopted the register perspective of systemic functional linguistics (Biber & Conrad, 2019, p. 22) and proposed an analytical framework, intending to explore “functional relationships between linguistic patterns of use and the situational characteristics of registers” (Goulart et al., 2020, p. 7.2).

A more in-depth analysis based on the journal, document, and author co-citation analysis revealed that the main theoretical frameworks in register studies are text linguistics, systemic functional linguistics, and sociolinguistics.

Text linguistics refers to a significant approach in terms of theory and methodology in register variation studies which conduct quantitative methods to describe the linguistic features of texts, as “the basis for comparing the patterns of register variation across texts” (Biber, 2019, p. 43). For instance, Smith et al. (2014) quantified linguistic features of specific and general clinical text through a comparative register analysis.

Systemic functional linguistics studies have mainly investigated registers as “different semiotic dimensions together with other types of linguistic variation” in register analysis (Matthiessen, 2019, p. 31). Lukin (2013), for instance, analyzed a TV news report within the framework of SFL and presented functional varieties in the register of news reports on the context-construing work.

Sociolinguistics has also played a critical role in register studies. For instance, Gal (2019) examined the role of register-making in constructing and evoking authority for political discourses and suggested that registers display connections between organizations in different social arenas.

Important Research Methods

Table 9 presents a grouping of keywords of the important research methods used in register studies and their classification grounded on Phakiti et al. (2018) and McKinley and Rose (2020). Among them, the quantitative method mainly includes corpus analysis. Corpus analysis, for instance, was employed by Biber et al. (2021) to investigate the conversation register in the British National Corpus, and findings showed that most conversational talks consisted of sequences of coherent discourse units that can help identify the communicative goals.

Table 9.

Research Methods and Keywords.

	Research methods	Keywords by CiteSpace	Keywords by VOSviewer
Quantitative	Corpus analysis	Corpus (21), multi-dimensional analysis (20), corpus linguistics (20), corpus-based translation study (3), corpus analysis (3), corpora (2), learner corpora (2) backbone corpus (1), comparable corpora (1), corpus-based (1), British national corpus (1), corpus annotation (1)	Multi-dimensional analysis (24), corpus (23), corpus linguistics (23), corpus analysis (6), corpora (6)
Qualitative	Discourse analysis	Discourse (20), discourse marker (7), academic discourse (5), classroom discourse (4), metadiscourse (3), discourse analysis (2), applied linguistics discourse (1), computer mediated discourse (1)	Discourse (29), metadisourse (6), academic discourse (5), discourse markers (5)
	Genre analysis	Genre (5), genre analysis (2), argumentative essay genre (1)	Genre (15)
	Conversation analysis	Conversation (3), conversation analysis (1)	Conversation (6)

As a methodological approach based on corpora, MDA is one “specifically frequently used approach to explore register variation” (Seoane & Biber, 2021, p. 236). MDA was developed to identify “the salient linguistic co-occurrence patterns” in a language from the perspectives of empirical and quantitative and explore register variations defined by the co-occurrence linguistic patterns (Biber & Conrad, 2001, p. 5). The approach can be traced back to Biber (1985, 1986) and then developed further in Biber’s (1988) study, and has been applied for interpreting register features and analyzing register variation based on corpora of Web (Biber & Egbert, 2018).

MDA identifies 67 linguistic features in each observed text (e.g., pronouns, nominal forms, tense and aspect markers, and negation), and reduces the features to six dimensions including “involved versus informational production, narrative versus non-narrative discourse, situation-dependent versus elaborated reference, overt expression of argumentation, abstract versus non-abstract style and online information elaboration” (Biber, 1988, pp. 831, 835) to confirm the register patterns (e.g., science and technology exposition, general narration, interactive persuasion). MDA has been widely used to analyze a range of register studies, such as corporate annual reports (Ren & Lu, 2021), academic writing between Anglophone and non-Anglophone experts (Omidian et al., 2021), contemporary American television (Sardinha & Pinto, 2021) and the extra- and intratextual characteristics of Czech texts (Cvrček et al., 2021).

Register studies are combined with qualitative methods, such as discourse analysis, genre analysis, and conversation analysis. Discourse analysis, for example, was adopted by Baker and Vessey (2022) to compare Islamist extremist texts to reveal similar and distinct discursive themes and linguistic strategies in the same register of different languages. In another example, Corella (2020) adopted discourse analysis to investigate academic spoken register in peer interactions in an elementary classroom.

Genre analysis was used by Gholaminejad (2021) to compare lexical bundles in academic written registers, such as textbooks and research articles, and found different discourse functions between the two registers. Moreover, Sindoni (2021) applied conversation analysis to explore spoken register and findings showed that mode-switching played important role in the management of conversation flow as a self-repair strategy in multi-party interactions.

Main Research Themes

Table 10 presents the grouping results of keywords based on Biber and Conrad’s (2019) analytical framework on register analysis, which reflects important research themes in register studies. To identify the important research themes in register studies, the following dimensions are discussed: linguistic features, register types, register variations, and communicative functions. Furthermore, teaching and education is one important strand in register studies, as discussed in Section 3.2 and thus it is discussed as one of the dimensions of research themes.

Table 10.

Keywords of Research Themes.

Dimensions	Keywords by CiteSpace	Keywords by VOSviewer
Linguistic features	Lexical bundle (10)	Lexical bundle (12)
	Discourse marker (7)	Discourse markers (5)
	Construction (7)	Construction (5), grammaticalization (6)
	Stance (5)	Stance (15)
	Formulaic sequence (2)	Formulaic sequences (5)
Register types	Academic writing (15), academic language (10), literacy (5), academic literacy (4), classroom discourse (4), English for academic purpose (2)	Academic writing (17), academic language (11), English for academic purposes (6), research article (6), academic discourse (5)
	Spoken (12), spoken language (2), conversation (3), song (2), talk (2), speech (2)	Spoken (12), speech (11), conversation (6)
	Written (2)	Written (6)
	Blog (2), web register (2)	Computer-mediated communication (6)
Register variations	Register variation (22), language change (2)	Register variation (29), variation (10)
	Children (6), speaker (4), learner (4), gender (3),	Gender (9), speakers (7), children (5)
	American (4), Australian English (4), American English (3), Spanish English (2), World Englishes (2)	Australian English (5), Cypriot Greek (5),
	Late modern English (2)	Late modern English (5)
Functional dimension	Identity (14)	Identity (18)
Functional dimension	Language ideology (8), ideology (2)	Language ideology (12), ideology (5)
Teaching and Education	Acquisition (13), second language acquisition (4)	Acquisition (13)
	Student (8), L1 (6)	Student (10), learners (7), L1 (6)
	Classroom (5)	Classroom (7)
	Second language (5), second language writing (2)	Second language (5)
	Education (3), high education (1)	Education (5)

Linguistic Features

In the dimension of linguistic features, the frequently explored items are lexical bundles, discourse markers, construction, stance, and formulaic sequences.

Lexical bundles, referred to as multi-word expressions, are the key distinguishing features of particular registers (Hyland & Jiang, 2018). For example, Grabowski (2015) analyzed lexical bundles used in the English pharmaceutical written register and found that there are salient links between different features across different pharmaceutical registers, such as linguistic features and functional features. In another example, Gholaminejad (2021) compared lexical bundles in academic written registers and found that attitudinal/modality lexical bundles are used more in textbooks than research articles.

Another important topic of linguistic features, discourse markers, used as the “linguistic indicators of register” (Brizuela et al., 1999, p. 128), serve an important function in the articulation of the text, such as connecting sentences, clauses, and phrases (Altikriti, 2019). For example, Garcia (2016) identified the usual discourse markers in oral conversations and written speech in Spanish and found the preference of written speech for discourse organizers or the conversation markers tendency to oral interactions.

Constructions involve observations of conventionalized pairings of meaning and form of language features (Goldberg, 2003), which were adopted in the specific constructions in different registers. Schönefeld (2013), for example, examined the English specific construction in four registers (academic prose, newspaper texts, fiction, and conversation) and findings suggested that register leaves a mark on the patterns used in authentic communication. In another example, Bao et al. (2017) examined perfect construction in different registers, including spoken, fiction, magazine, newspaper, and academic registers, to explore the synchronic changes of perfect construction in different registers of American English.

Stance is a cover term for expressing “attitudes, feelings, judgments, or commitment concerning the propositional content of a message” (Biber & Finegan, 1989, p. 93). For example, Poole (2021) compared the variation of stance adverbs between legal writing register and other registers and suggested that there are conflicts between the practical use of stance adverbs and the legal writing style guides.

Formulaic sequences, linking to “a single meaning/pragmatic function” (Conklin & Schmitt, 2008, p. 72), often serve a vital function in discourse. Wang (2018) identified formulaic sequences in academic writing registers and revealed that novice writers used more formulaic sequences with interpersonal functions in academic writing in comparison to expert writers.

Register Types

In the dimension of register types, the repeatedly examined types are spoken, written, academic and online register.

Spoken registers include broadcasts (Zhang et al., 2017), public and non-public conversation (Verhoeven & Lehmann, 2018), and television programs (Sardinha & Pinto, 2021). For example, Sardinha and Pinto (2021) analyzed American television programs and found that all the programs can be categorized into different specific registers, such as “presentation of information, opinion, and discussion,” and so on.

Written registers include business emails (Gimenez-Moreno & Skorczynska, 2013), legal documents (Ingham, 2016; Poole, 2021), novels of Charles Dickens (Egbert & Mahlberg, 2020), news articles (Clarke et al., 2021), and corporate annual reports (Bu et al., 2020; Ren & Lu, 2021). For example, Poole (2021) examined stance adverbs in law written registers and compared the use and function of stance adverbs in different judicial texts.

Next, academic registers include research articles of different disciplines (Hyland & Jiang, 2018), classroom oral interaction (Hong & Basturkmen, 2020), and students’ academic writing (Nasseri, 2021). For example, Hyland and Jiang (2018) examined the diachronic change of the lexical bundles in academic written register, including applied linguistics, sociology, biology, and electronic engineering.

Last, another type emerging in register analysis is online register (indicated by the keyword “computer-mediated communication,” freq. = 6 in VOSviewer, and other relevant keywords, e.g., “blog” and “web”), including both the public-oriented communication registers such as blogs, web pages, and the personal-oriented communication registers such as Emails, Twitter, and Facebook (Sardinha & Pinto, 2014, p. 81).

Most researches tended to describe and identify linguistic features of online language in a broad sense (Goulart et al., 2020, pp. 7.12), for example, by comparing a variety of online registers including websites, Twitter, blogs, and Facebook (e.g., Biber & Egbert, 2018; Sardinha, 2018; Titak & Roberson, 2013).

Furthermore, Twitter and Facebook as the new topics of the personal-oriented communication registers, have been widely taken into consideration, such as the styles of specific individuals’ tweets (Biber & Conrad, 2019), the functional linguistic variation in Twitter trolling (Clarke, 2019), stylistic variation in the celebrity’s tweets (Clarke & Grieve, 2019), companies’ responses to customer complaints on Twitter (Fuoli et al., 2021). For example, Clarke and Grieve (2019) examined Trump’s tweets posted in the past decade and identified four dimensions of stylistic variation, including “conversational, campaigning, engaged, and advisory discourse” (Clarke & Grieve, 2019).

Register Variations

Register variation is meant that two or more registers are compared to identify linguistic patterns of variation which can be interpreted by “the communicative purpose, the context of production, and topic, among other situational factors” (Goulart et al., 2020, p. 7.3), and resonate with the field, tenor and mode of discourse across different registers.

First, the “field” of discourse (what is going on in a given context, indicated by keywords, such as “classroom”) leads to variation in representing motion across different registers (tourist guidebooks, physics textbooks, weather forecasts, among others) (Kashyap & Matthiessen, 2019). For example, Farrugia (2013) examined conversations in a mathematics classroom and illustrated various routes of language choice from informal to formal language in the classroom register.

Second, the “tenor” of discourse (who are taking part in the activity, indicated by keywords, such as “children,”“speaker,” and “gender”) causes variation in employing different patterns of language use across speakers. For example, Bernicot et al. (2012) explored the short message service (SMS) register among French-speaking adolescents and found that the commonly reported distinctions between genders were mitigated in the online register.

Third, the “mode” of discourse (the function of the text in the event, including both the channel taken by the language, indicated by keywords, such as “spoken” and “written”) accounts for variation in using metadiscourse across non-discussion and discussion broadcasts, scripted and unscripted speeches, public and casual conversations (Zhang et al., 2017).

In addition, register variations are accounted for by English varieties, indicated by the keywords “Australian English,”“Spanish English,” and “American English.” For example, Shakir and Deuber (2018) compared the online registers-comments of Pakistani English to U.S. English and identified four dimensions of variation.

Furthermore, other register variations resonated with the diachronic linguistic changes, indicated by the keywords “late modern English.” For example, Hiltunen et al. (2020) explored the patterns of intensification in medical writing by using Late Modern English Medical Texts.

Functional Dimension

In the functional dimension, the commonly examined communicative functions are those of constructing identity and communicative ideology. Identity is commonly produced and reproduced through speakers’ particular language use (Bucholtz & Hall, 2004). For example, Ohashi (2018) analyzed the emails of Japanese men and illuminated that the use of honorifics could index a specific social identity. Revis (2021) explored the naturally-occurring family discourse in a diasporic community and revealed that the participants partially shared socialization trajectories that reflected their immigration identity.

Another communicative function of register is to communicate ideologies. For example, Friedman (2023) analyzed Ukrainian-Russian adolescent bilinguals’ spoken register and showed these young people conducted different language strategies to communicate prevailing purist ideologies.

Teaching and Education

In the dimension of teaching and education, the repeated explored topics are academic register variations in terms of field (indicated by the keyword “classroom”) and tenor (indicated by the keywords “student” and “learners”). As discussed earlier, academic register is an important theme in register studies, and register is fundamentally important for any student’s language learning and one of the main goals of education is “to learn the specialized register of a particular profession” (Biber & Egbert, 2018, pp. 3–4).

Register studies concentrated on linguistic features’ application in language teaching and education, such as discourse markers, and lexical bundles in different language teaching. For example, Garcia (2016) identified of the usual discourse markers in oral conversations and written speech of Spanish and extend those already taught for the acquisition of discourse competence in Spanish as a Foreign Language. Galloway et al. (2019) argued that student-generated metalanguage in academic registers can be used as a primary instructional resource to help learners build knowledge of academic language.

Moreover, some studies involved the implication and application of registers in teaching and education. Schleppegrell (2020) emphasized the importance and implication of register in English teaching and education, namely, understanding variation in the registers in different classroom tasks and identifying language features used in the different disciplinary discourses. With the advent of online teaching, the application of register in online classrooms has received attention. For example, Ho and Tai (2021) explored how online teachers draw on different registers to teach English vocabulary, which offered some pedagogical implications for developing teaching and learning materials on digital platforms.

Emerging Trends in the Area of Register Studies

The keywords in the articles can indicate the fundamental aspects of the study field (Xiao & Li, 2021). Thus, emerging trends in research can be identified by analyzing the co-occurrence of keywords, and “the profile of a specific field can be examined via keyword cluster analysis” (Xiao & Li, 2021, p. 493). The keywords cluster analysis was adopted to highlight emerging trends in register studies.

Table 11 provides the keywords clusters by employing the log-likelihood ratio (LLR) agglomeration calculation and Figure 9 displayed the timeline view of keywords clusters year by year. As shown, all clusters share and overlap similar characteristics between Table 11 and Figure 9. In the 14 labels of clusters, these were most frequently discussed in the second 5 years (2016–2021), namely, #0 systemic functional linguistics, #1 multi-dimensional analysis, #3 discourse, #8 audience, #10 function, and #12 corpus analysis.

Table 11.

Key Labels as Topics in Register Studies.

ID	Clusters	Size	Mean (year)	Top terms (Loglikelihood)
0	Systemic functional linguistics	32	2016	systemic functional linguistics (9.11, 0.005); Australian English (8.96, 0.005); academic language (8.96, 0.005); classroom interaction (8.96, 0.005); metalanguage (8.96, 0.005)
1	Multi-dimensional analysis	23	2017	multi-dimensional analysis (15.51, 1.04); corpus linguistics (9.35, 0.005); language awareness (4.09, 0.05); subjectivity (4.09, 0.05); telecinematic discourse (4.09, 0.05)
2	English for academic purposes	22	2015	English for academic purposes (11.8, 0.001); lexical bundles (10.05, 0.005); frequency (7.6, 0.01); academic writing (7.1, 0.01); disciplinary discourses (3.91, 0.05)
3	Discourse	19	2016	discourse (10.11, 0.005); English learner (5.04, 0.05); Spanish L2 (5.04, 0.05); gender and age effects (5.04, 0.05); null objects (5.04, 0.05)
4	Linguistic complexity	19	2017	linguistic complexity (8.36, 0.005); discourse markers (6.01, 0.05); translation expertise (6.01, 0.05); reception studies (6.01, 0.05); scientific writing (6.01, 0.05)
5	Register variation	18	2016	register variation (18.46, 1.04); factor analysis (9.96, 0.005); spoken language (9.96, 0.005); multi-dimensional analysis (8.52, 0.005); South Africa (4.96, 0.05)
6	Writing-to-learn	18	2015	writing-to-learn (6.13, 0.05); bilingual family interaction (6.13, 0.05); family language policy (6.13, 0.05); teasing (6.13, 0.05); vocational education (6.13, 0.05)
7	Emergent bilingualism	17	2016	emergent bilingualism (5.89, 0.05); narratives (5.89, 0.05); heritage Arabic speakers (5.89, 0.05); European Portuguese (5.89, 0.05); motherese (5.89, 0.05)
8	Audience	14	2018	audience (6.99, 0.01); academic persuasion (6.99, 0.01); academic blogs (6.99, 0.01); translanguaging (6.99, 0.01); academic discourse (6.99, 0.01)
9	Space	14	2015	space (10.6, 0.005); computer-mediated communication (7.05, 0.01); motion (7.05, 0.01); Cypriot Greek (3.61, 0.1); lexical cohesion (3.52, 0.1)
10	Functions	9	2017	functions (7.68, 0.01); annotation tasks (7.68, 0.01); polysemy (7.68, 0.01); descriptive subjectivity (7.68, 0.01); academic articles (7.68, 0.01)
11	Animacy	8	2014	animacy (9, 0.005); third language (l3) (9, 0.005); grammatical variation (9, 0.005); language processing (9, 0.005); modern English (9, 0.005)
12	Corpus analysis	8	2020	corpus analysis (7.43, 0.01); comparative genre analysis (7.43, 0.01); pragmatic development (7.43, 0.01); attitudinal markers (7.43, 0.01); applied linguistics discourse (7.43, 0.01)
13	Linguistic anthropology	7	2016	linguistic anthropology (6.4, 0.05); German (6.4, 0.05); language pedagogy (6.4, 0.05); dialect (6.4, 0.05); discrimination (6.4, 0.05)

Figure 9.

Timeline view of keywords clusters year by year.

First, the label of Cluster #0 relates to “systemic functional linguistics (SFL),” which indicated the important theoretical basis in register studies, as discussed in Section 3.2 To be more specific, SFL involved the keywords, such as “Australian English, academic language, classroom interaction, and metalanguage.” For example, Forey (2020) analyzed the use of a metalanguage taken from SFL in students’ classroom interactions and writings. SFL was adopted to investigate the system of causation in different languages from a contrastive register-based perspective (Sellami-Baklouti, 2021).

Second, the label of Cluster #1 and #12 are associated with MDA and corpus analysis, which demonstrated the trend of the quantitative research methods in register studies. In the two clusters, the important keywords “pragmatic development” and “applied linguistics discourse” might indicate register studies have gained increasing attention in pragmatics and applied linguistics.

As discussed, represented by MDA, corpus analysis was widely used in register analysis. Corpus was adopted to perform an empirical bottom-up analysis of linguistic features based on the collection of texts, and the development of empirical register research coexists with that of empirical corpus-based research (Seoane & Biber, 2021). MDA, as the corpus-based method, was widely used in different register studies, such as Czech texts (Cvrček et al., 2021) and television programs (Sardinha & Pinto, 2021). Moreover, MDA was also used in some new-burgeoning online registers, such as internet texts (Sardinha, 2018), blogs (Shakir & Deuber, 2018), and Twitter (Bohmann, 2020).

The label of Cluster #3 is related to discourse, which includes the discourse produced by different speakers and audiences, such as different genders, ages, and nationalities. Qin and Uccelli (2020), for instance, studied linguistic complexity and register flexibility across academic writing and spoken registers produced by learners of different ages and language backgrounds. Findings revealed that participants’ language proficiency can lead to textual linguistic complexity, but is not consistent with register flexibility.

The label of Cluster #8 is related to “audience,” which is of considerable importance in all models of registers. Barkaoui (2021) examined the potential relationship between audiences and L2 learners in writing and indicated that the participants tended to adopt different writing strategies and styles when writing to different audiences. With the affordance of technology, academic blogs and other platforms provide opportunities for writers to reach wider audiences.

The label of Cluster # 10 is related to “function,” which indicated that the function of the language receives increasing attention in register studies. Register studies focus on “the functional relationships between linguistic patterns of use and the situational characteristics of registers” (Goulart et al., 2020, p. 7.2), and thus tend to functional variations from the description of linguistic features.

Conclusion

This study attempted to present the current situation of register studies using bibliometric analysis. Several findings illustrated in the study may provide new insights and understanding in register studies.

The first finding presented the key journals, most productive authors, institutions, and countries in the field. A group of productive and core authors in the field are identified by the publications and co-citation analysis which may be useful for future researchers to retrieve influential research literature.

The second finding revealed text linguistics, SFL, and sociolinguistics were the major theoretical origins of register studies. Moreover, mixed methods are not uncommon in register studies with the development of corpus linguistics and computational linguistics. In register studies, quantitative methods were used to describe the general linguistic characteristics of each register, and qualitative approaches can focus on specific communicative purposes.

The third finding is that research themes and trends identified by high-frequency keywords and the timeline of the keyword network show that register studies have emerged as increasingly distinctively pragmatic and sociological. Moreover, some emerging trends for register studies display the tendency of register variations from register descriptions. Register has been conceptualized even more specifically, and online registers, such as Twitter and blogs, have become the research hotspot (Biber & Egbert, 2018). The major research themes and emerging trends are a useful resource for novice researchers and established scholars in the field, and perhaps also critical in assisting journal editors to continue to promote theoretical or methodological advances in the field.

There are also limitations in the study in some aspects. On the one hand, the analyzed data are narrowly limited to those articles published in journals and did not take account of the other types of literature, such as book chapters. On the other hand, the coding schemes and classifications are pre-determined on the previous related studies and subjective evaluations should be involved in the analysis. To this end, the reviewed aspects of research methods, research themes, and emerging trends are worth exploring more comprehensively in future research.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by the Humanities and Social Sciences Project of the Ministry of Education, the People’s Republic of China (Grant Number: 21YJA740035).

ORCID iDs

Ya Sun

Qiong Wang

References

Altikriti

S. F.

(2019). Investigating discourse markers in the annexes of the international civil aviation organization. Southern African Linguistics and Applied Language Studies, 37(1), 77–90.

Baker

Vessey

(2022). A corpus-driven comparison of English and French Islamist extremist texts. International Journal of Corpus Linguistics, 23(3), 255–278.

Bao

Zhang

Feng

(2017). American English perfect construction across registers. Journal of Quantitative Linguistics, 25(4), 1–28.

Barkaoui

(2021). Exploring second language learners’ writing processes and texts when writing to different audiences. The Canadian Modern Language Review, 77(3), 234–268.

Bernicot

Volckaert-Legrier

Goumi

Bert-Erboul

(2012). Forms and functions of SMS messages: A study of variations in a corpus written by adolescents. Journal of Pragmatics, 44(12), 1701–1715.

Biber

(1985). Investigating macroscopic textual variation through multifeature/multidimensional analyses. Linguistics, 23, 337–360.

Biber

(1986). Spoken and written textual dimensions in English: Resolving the contradictory findings. Language, 62, 384.

Biber

(1988). Variation across speech and writing. Cambridge University Press.

Biber

(1993). Representativeness in corpus design. Literary and Linguistic Computing, 8(4), 243–257.

10.

Biber

(2010). What can a corpus tell us about registers and genres? In The Routledge handbook of corpus linguistics. Routledge.

11.

Biber

(2014). Using multi-dimensional analysis to explore cross-linguistic universals of register variation. Languages in Contrast, 14(1), 7–34.

12.

Biber

(2019). Text-linguistic approaches to register variation. Regional Studies, 1(1), 42–75.

13.

Biber

Conrad

(2001). Variation in english: Multi-dimensional studies (1st ed.). Routledge.

14.

Biber

Conrad

(2019). Register, genre and style. Cambridge University Press.

15.

Biber

Egbert

(2016). Register variation on the searchable web: A multi-dimensional analysis. Journal of English Linguistics, 44(2), 95–137.

16.

Biber

Egbert

(Eds.). (2018). Register variation online (1st ed.). Cambridge University Press.

17.

Biber

Egbert

Keller

Wizner

(2021). Towards a taxonomy of conversational discourse types: An empirical corpus-based analysis. Journal of Pragmatics, 171, 20–35.

18.

Biber

Finegan

(1989). Styles of stance in English: Lexical and grammatical marking of evidentiality and affect. Text-Interdisciplinary Journal for the Study of Discourse, 9(1), 93–124.

19.

Biber

Gray

(2013). Being specific about historical change: The influence of sub-register. Journal of English Linguistics, 41(2), 104–134.

20.

Biber

Gray

Poonpon

(2011). Should we use characteristics of conversation to measure grammatical complexity in L2 writing development? TESOL Quarterly, 45(1), 5–35.

21.

Biber

Gray

Staples

(2016). Predicting patterns of grammatical complexity across language exam task types and proficiency levels. Applied Linguistics, 37(5), 639668.

22.

Bohmann

(2020). Situating Twitter discourse in relation to spoken and written texts. Zeitschrift fur Dialektologie und Linguistik, 87(2), 250–284.

23.

Brizuela

Andersen

Stallings

L. M.

(1999). Discourse markers as indicators of register. Hispania, 82, 128–142.

24.

Bucholtz

Hall

(2004). Theorizing identity in language and sexuality research. Language in Society, 33(04), 469–515.

25.

Connor-Linton

Wang

(2020). Linguistic variation in the discourse of corporate annual reports: A multi-dimensional analysis. Discourse Studies, 22(6), 647–677.

26.

Chen

(2004). Searching for intellectual turning points: progressive knowledge domain visualization. Proceedings of the National Academy of Sciences of the United States of America, 101Suppl 1, 5303–5310.

27.

Clarke

(2019). Functional linguistic variation in Twitter trolling. International Journal of Speech Language and the Law, 26(1), 57–84.

28.

Clarke

Grieve

(2019). Stylistic variation on the Donald Trump Twitter account: A linguistic analysis of tweets posted between 2009 and 2018. PLoS One, 14(9), e0222062.

29.

Clarke

McEnery

Brookes

(2021). Multiple correspondence analysis, newspaper discourse and subregister: A case study of discourses of Islam in the British press. Regional Studies, 3(1), 144–171.

30.

Conklin

Schmitt

(2008). Formulaic sequences: Are they processed more quickly than nonformulaic language by native and nonnative speakers? Applied Linguistics, 29(1), 72–89.

31.

Corella

(2020). Talking “smart”: Academic language and indexical competence in peer interactions in an elementary classroom. Linguistics and Education, 55, 100755.

32.

Cvrček

Komrsková

Lukeš

Poukarová

Řehořková

Zasina

A. J.

(2021). From extra- to intratextual characteristics: Charting the space of variation in Czech through MDA. Corpus Linguistics and Linguistic Theory, 17(2), 351–382.

33.

Egbert

Mahlberg

(2020). Fiction – One register or two?: Speech and narration in novels. Regional Studies, 2(1), 72–101.

34.

Farrugia

M. T.

(2013). Moving from informal to formal mathematical language in Maltese classrooms. International Journal of Bilingual Education and Bilingualism, 16(5), 570–588.

35.

Forey

(2020). A whole school approach to SFL metalanguage and the explicit teaching of language for curriculum learning. Journal of English for Academic Purposes, 44, 100822.

36.

Friedman

D. A.

(2023). Language socialization and academic discourse in English as a foreign language contexts: A research agenda. Language Teaching, 56, 261–275.

37.

Fuoli

Clarke

Wiegand

Ziezold

Mahlberg

(2021). Responding effectively to customer feedback on Twitter: A mixed methods study of webcare styles. Applied Linguistics, 42(3), 569–595.

38.

Garcia Salido

. (2016). Error analysis of support verb constructions in written Spanish learner corpora. Modern Language Journal, 100(1), 362376.

39.

Galloway

E. P.

Dobbs

Olivo

Madigan

(2019). ‘You can…’: An examination of language-minoritized learners’ development of metalanguage and agency as users of academic language within a multivocal instructional approach. Linguistics and Education, 50, 13–24.

40.

Gal

(2019). Making registers in politics: Circulation and ideologies of linguistic authority. Journal of Sociolinguistics, 23(5), 450–466.

41.

Gholaminejad

(2021). A comparison of two genres: Lexical bundles in the discourse of applied linguistics. Atlantis-journal of the Spanish Association of Anglo-American Studies, 43(2), 90–109.

42.

Gimenez-Moreno

Skorczynska

(2013). Business communication across three European cultures: A contrastive analysis of British, Spanish and Polish email writing. Iberica, 26, 77–97.

43.

Goldberg

A. E.

(2003). Constructions: A new theoretical approach to language. Trends in Cognitive Sciences, 7(5), 219224.

44.

Goulart

Gray

Staples

Black

Shelton

Biber

Egbert

Wizner

(2020). Linguistic perspectives on register. Annual Review of Linguistics, 6(1), 435–455.

45.

Grabowski

. (2015). Keywords and lexical bundles within English pharmaceutical discourse: A corpus-driven description. English for Specific Purposes, 38, 23–33.

46.

Halliday

M. K.

(1989). Spoken and written language. Oxford University Press.

47.

Hiltunen

Räikkönen

Tyrkkö

(2020). Investigating colloquialization in the British parliamentary record in the late 19th and early 20th century. Language Sciences, 79, 101270.

48.

Hong

Basturkmen

(2020). Incidental attention to academic language during content teaching in two EMI classes in South Korean high schools. Journal of English for Academic Purposes, 48, 100921.

49.

W. Y. J.

Tai

K. W. H.

(2021). Translanguaging in digital learning: The making of translanguaging spaces in online English teaching videos. International Journal of Bilingual Education and Bilingualism, 0(0), 1–22.

50.

Huan

Guan

(2020). Sketching landscapes in discourse analysis (1978–2018): A bibliometric study. Discourse Studies, 22(6), 697–719.

51.

C. P.

J. M.

Gao

Zhang

Y. K.

(2011). A journal cocitation analysis of library and information science in China. Scientometrics, 86(3), 657–670.

52.

Hyland

Jiang

F. (K)

. (2018). Academic lexical bundles how are they changing? International Journal of Corpus Linguistics, 23(4), 383–407.

53.

Ingham

(2016). Investigating language change using Anglo-Norman spoken and written register data. Linguistics, 54(2), 381–410.

54.

Kashyap

A. K.

Matthiessen

C. M. I. M

. (2019). The representation of motion in discourse: Variation across registers. Language Sciences, 72, 71–92.

55.

Larsson

Kaatari

(2020). Syntactic complexity across registers: Investigating (in)formality in second-language writing. Journal of English for Academic Purposes, 45, 100850.

56.

Lin

Lei

(2020). The research trends of multilingualism in Applied Linguistics and Education (2000–2019): A Bibliometric analysis. Sustainability, 12(15), 6058.

57.

Liu

(2021). Mapping the field of English for specific purposes (1980–2018): A co-citation analysis. English for Specific Purposes, 61, 97–116.

58.

Lukin

(2013). What do texts do? The context-construing work of news. Text and Talk, 33(4-5), 523–551.

59.

Matthiessen

C. M.

(2019). Register in systemic functional linguistics. Regional Studies, 1, 10–41.

60.

McKinley

Rose

(2020). The Routledge handbook of research methods in applied linguistics. Routledge.

61.

Mou

Cui

Kurcz

(2019). Bibliometric and visualized analysis of research on major e-commerce journals using CiteSpace. Journal of Electronic Commerce Research, 20(4), 219–237.

62.

Nasseri

(2021). Is postgraduate English academic writing more clausal or phrasal? Syntactic complexification at the crossroads of genre, proficiency, and statistical modelling. Journal of English for Academic Purposes, 49, 100940.

63.

Ohashi

(2018). An emerging role-identity and honorifics: A longitudinal study of email exchanges in a Japanese community. Journal of Pragmatics, 127, 36–55.

64.

Omidian

Siyanova-Chanturia

Biber

(2021). A new multidimensional model of writing for research publication: An analysis of disciplinarity, intra-textual variation, and L1 versus LX expert writing. Journal of English for Academic Purposes, 53, 101020.

65.

Parkinson

Musgrave

(2014). Development of noun phrase complexity in the writing of English for academic purposes students. Journal of English for Academic Purposes, 14, 48–59.

66.

Phakiti

De Costa

Plonsky

Starfield

(2018). The Palgrave handbook of applied linguistics research methodology. Palgrave Macmillan.

67.

Poole

(2021). A corpus-aided study of stance adverbs in judicial opinions and the implications for English for Legal Purposes instruction. English for Specific Purposes, 62, 117–127.

68.

Qin

Uccelli

(2020). Beyond linguistic complexity: Assessing register flexibility in EFL writing across contexts. Assessing Writing, 45, 100465.

69.

Ren

(2021). A multi-dimensional analysis of the management’s discussion and analysis narratives in Chinese and American corporate annual reports. English for Specific Purposes, 62, 84–99.

70.

Revis

(2021). Exploring the “languaging habitus” of a diasporic community: Colombians in New Zealand. Lingua, 263, 102941.

71.

Sardinha

T. B.

(2018). Dimensions of variation across Internet registers. International Journal of Corpus Linguistics, 23(2), 125–157.

72.

Sardinha

T. B.

Pinto

M. V.

(2014). Multi-dimensional analysis, 25 years on. John Benjamins.

73.

Sardinha

T. B.

Pinto

M. V.

(2021). A linguistic typology of American television. International Journal of Corpus Linguistics, 26(1), 127–160.

74.

Schleppegrell

M. J.

(2020). The knowledge base for language teaching: What is the English to be taught as content? Language Teaching Research, 24(1), 17–27.

75.

Schönefeld

(2013). It is … quite common for theoretical predictions to go untested (BNC_CMH). A register-specific analysis of the English go un-V-en construction. Journal of Pragmatics, 52, 17–33.

76.

Sellami-Baklouti

(2021). Transitivity-ergativity perspectives on causation in legal texts: A contrastive study of Arabic and English website terms of service. Lingua, 261, 102782.

77.

Seoane

Biber

(2021). Corpus-based approaches to register variation. John Benjamins.

78.

Shakir

Deuber

(2018). A multidimensional study of interactive registers in Pakistani and US English. World Englishes, 37(4), 607–623.

79.

Sindoni

M. G.

(2021). Mode-switching in video-mediated interaction: Integrating linguistic phenomena into multimodal transcription tasks. Linguistics and Education, 62, 100738.

80.

Smith

Megyesi

Velupillai

Kvist

(2014). Professional language in Swedish clinical text: Linguistic characterization and comparative studies. Nordic Journal of Linguistics, 37(2), 297–323. The R Core Team (Ed.). (2016). R: A language and environment for statistical computing. MSOR Connections, 1. https://api.semanticscholar.org/CorpusID:215755663

81.

Staples

Egbert

Biber

Gray

(2016). Academic writing development at the university level: Phrasal and clausal complexity across level of study, discipline, and genre. Written Communication, 33(2), 149–183.

82.

Titak

Roberson

(2013). Dimensions of web registers: An exploratory multi-dimensional comparison. Corpora, 8(2), 235–260.

83.

van Eck

N. J.

Waltman

Dekker

van Den Berg

. (2010). A comparison of two techniques for bibliometric mapping: Multidimensional scaling and VOS. Journal of the American Society for Information Science and Technology, 61(12), 2405–2416.

84.

Verhoeven

Lehmann

(2018). Self-embedding and complexity in oral registers. Glossa: A Journal of General Linguistics, 3(1), 1–30.

85.

Wang

(2018). As Hill seems to suggest: Variability in formulaic sequences with interpersonal functions in L1 novice and expert academic writing. Journal of English for Academic Purposes, 33, 12–23.

86.

Xiao

(2021). A bibliometric analysis of critical discourse analysis and its implications. Discourse & Society, 32(4), 482–502.

87.

Yilmaz

R. M.

Topu

F. B.

Takkaç Tulgar

(2022). An examination of the studies on foreign language teaching in pre-school education: A bibliometric mapping analysis. Computer Assisted Language Learning, 35(3), 270–293.

88.

Zhang

Sun

Peng

Gan

(2017). A multidimensional analysis of metadiscourse markers across spoken registers. Journal of Pragmatics, 117, 106–118.

Mapping the Field of Register Studies: A Bibliometric Analysis

Abstract

Plain Language Summary

Keywords

Introduction

Data and Methodology

Data Collection

Inclusion and Exclusion Criteria

Data Analysis

Results and Discussion

General Characteristics

Publication Trend

Productive Authors, Institutions, and Countries

Major Theoretical Frameworks

Important Research Methods

Main Research Themes

Linguistic Features

Register Types

Register Variations

Functional Dimension

Teaching and Education

Emerging Trends in the Area of Register Studies

Conclusion

Footnotes

Declaration of Conflicting Interests

Funding

ORCID iDs

References