By Mingdan Luo, Dorothy DeWitt, and Norlidah Alias
Purpose: Technical communication (TC) is an emerging topic which has received attention in both the field of language studies and among the technical profession in the last few decades. In this article, a scientometric review of academic publications to explore the intellectual landscape and evolutionary characteristics of TC research worldwide between 2001 and 2020 is conducted.
Methods: Visualization software was employed to analyze co-citation and co-word networks from 2,183 articles published in Web of Science and Scopus databases from 2001 to 2020.
Results: The findings indicate that TC research has increased in recent years and has been done in the English language departments and technology departments in recent years. Then, five clusters form the intellectual structure of TC research: translation training, methodologies in TC, composition studies, rhetorical action, and the industry’s needs. Finally, the findings indicated there were paradigm shifts in the field of TC. Further, the evolution analysis has shown that the current trends of TC research is now focused on TC pedagogy, a global TC, human-computer interaction, and language learning and training.
Conclusion: This review provides reliable information for academics and practitioners to identify the knowledge base, the evolutionary process, and the emerging trends in the TC field from visualized maps. This review can serve as a prelude for future TC research and can provide a guide for the TC skills required among professionals in the future.
KEYWORDS: Alluvial diagram, CiteSpace software, co-citation analysis, co-word analysis, evolution characteristics, technical communication
- This article presents the dynamic development, paradigm shifts, and research frontier of the TC field in an innovative and visualized manner, which can benefit a wide range of readers in various areas of TC.
- Practitioners would be more perceptive and productive in their practice and teaching once they recognize the changing roles and competencies in TC trends related to language, technological tools, and human-computer interaction.
- Curriculum designers need to consider the delivery of language skills through online courses as well as using technological tools in blended learning for the future.
In the last decade, scholars have investigated definitions of technical communication (TC) and their related terms (Carradini, 2020) as well as the main issues in this area (Rude, 2009). Some of this research has also reviewed the research methods used in TC (Boettger & Lam, 2013; McNely, Spinuzzi, & Teston, 2015).
Other studies have focused on careers which require TC. For instance, Lanier (2009) found that employers required technical communicators with technical or domain-specific knowledge, while Brumberger and Lauer (2015) analyzed core competencies required for TC in the job market. Hence, the continued interest and research in TC has provided a critical need to review and update the current research base for references of academics and practitioners.
Although the preceding works of literature in TC are valuable and can provide a solid foundation for future research, there are limitations due to the limited breadth and scope of previous review (Chen, 2017). In addition, reviewing a large body of literature to identify viewpoints, connections, distinct features, or make conclusions, is both time and energy-consuming and is limited by one’s cognitive ability (Aryadoust & Ang, 2019). To address this limitation and bridge this gap, a scientometric review can be conducted to provide a significant body of knowledge on topics that are important in the field. In this way, the review is not limited to the partial contributions of specific articles but will focus on the overall development of TC research. Moreover, providing a visualization of the data helps readers better comprehend the data.
A scientometric review is a method of quantitative analysis of literature used to understand the emerging themes and knowledge base in the field of research (Chen et al., 2012). There have been at least three scientometric review articles on TC. Smith’s (2000) review of articles from 1988 to 1997 showed that there was increased interest and research in TC journals for a variety of disciplines. This important article also distinguished this method from other reviews by investigating the vast size of the datasets. In another study, Lowry et al. (2007) investigated the perceived quality of TC-related journal articles. The results showed that although high-impact articles were generally published in high-ranked journals, high-impact research was still published in lower-ranked journals (Lowry et al., 2007). Hence, researchers need to continuously explore topics by retrieving data from various reputable databases rather than being limited to specific journals. In the quantitative content analysis of academic publications from 1996 to 2017, several characteristics were identified, such as the content and resources for TC tended to be process-driven instead of product-driven, and topics related to communication strategy and collaboration might foster future academic-industry connection (Friess & Boettger, 2021). Hence, based on these findings, this review intends to examine TC-related articles in the last two decades (from 2001 to 2020) to determine trends.
Chen, Ibekwe-SanJuan, and Hou (2010) expanded the traditional co-citation analysis methodology with other visualization tools to include new functions, which facilitated analytical tasks and interpretation through automatic cluster labeling and summarization using the scientometric tool, CiteSpace. There has been an upward trend in the use of CiteSpace in various fields (Pan et al., 2018). It has been used to explore emerging trends in regenerative medicine (Chen et al., 2012); it has been used to obtain visualization in the agent-based computing research domain (Niazi & Hussain, 2011) and to identify the current state and trends in the field of public-private partnerships (PPP) research (Song, Zhang, & Dong, 2016); Morar and Agachi (2010) used CiteSpace to present a comprehensive review on the development of heat integration techniques; Fang, Yin, and Wu (2018) used it to map the evolution and emerging trends of climate change and tourism research through the co-citation network; and Jiang, Ritchie, and Benckendorff (2019) used CiteSpace to analyze the intellectual structure of the tourism crisis and disaster management.
Despite the popularity of CiteSpace, as of this writing, no attempt has been made to apply it to analyze the literature reviewed on TC. This article can provide reliable information for both academics and practitioners to quickly identify the knowledge base, the evolutionary process, and the emerging trends in the TC field to be shown as a visual map, which may serve as a prelude to future TC research and could contribute to the future of technical communication as a profession.
CiteSpace is used to code bibliographic records by citing articles and generating networks of co-cited references. The co-citation analysis of the document functions to identify the intellectual structures based on the accumulated co-citation trails in these references (Chen et al., 2012).
As mentioned, several structural and temporal metrics of co-citation networks were applied for clustering (Chen, 2017). Specifically, structural metrics consist of betweenness centrality, modularity, and silhouette, while temporal metrics include citation bursts. The betweenness centrality metric, which measures the importance of the position of the node in the network (the higher the value is, the more significant the reference is), is defined for each node in a network. Citation burst is to detect abrupt changes, such as exceptionally sharp increases among articles that share the same topic (Kleinberg, 2003). The sigma score of a node is a combined metric of both betweenness centrality and citation burst (Chen, 2017). Modular Q measures the degree to which the network can be divided into independent blocks. A high modularity suggests a well-structured network (Chen et al., 2010). In other words, the closer its value is to 1.00, the clearer the boundaries with other clusters are. The silhouette value is used to measure the homogeneity of each cluster. A silhouette value which is very close to the highest value of 1.00 means that the cluster can be regarded as an identified specialty with high validity in the field (Chen, 2017).
In addition, the clustering function of CiteSpace adopts the theory of spectral clustering (Chen et al., 2010), which has been proven as an efficient and generic clustering method (von Luxburg, 2007). The cluster labels displayed are selected from the terms with the highest weights among the citations of the articles in each cluster.
Time is not easy to display clearly in networks, so we used the alluvial diagram to present these complex networks and their relations. By transforming the static network to a dynamic alluvial diagram, the changing path of emerging and significant topics can be tracked. The alluvial generator was utilized to present the visualized network created by CiteSpace. The alluvial diagram was applied to demonstrate the temporal changes in a network’s composition, for example, changes in the structures of scientific disciplines or changes in the usage of words over time (Yeung, 2018).
This review, using these visualization tools, aims to explore the intellectual landscape and evolutionary characteristics related to TC research worldwide and across different fields. The current study aims to answer the following research questions:
- What constitutes the intellectual structure of TC research from 2001 to 2020?
- What are the evolutionary characteristics of TC research over the past two decades?
Data collection procedure
The Web of Science and Scopus databases are regarded as the most reliable data sources because both these large databases allow researchers to export detailed bibliographic information (comprising of author, title, abstract, keywords, and cited reference). Further, these databases provide an ideal data source and a friendly format for scientometric reviews (Fang, Yin, & Wu, 2018; Jing et al., 2020).
A total of 3,316 English published articles, including review articles, were retrieved from the two databases from 2001 to 2020 on 26 December 2020, when applying a topic search using the terms “technical communication,” “technical writing,” “technical English,” and “technical and professional communication.” After removing duplicates, there were a total of 2,183 qualified records from Web of Science (941) and Scopus (1,242). See Figure 1 for the trend in number of publications from 2001 to 2020.
The data collected was then analyzed using a scientometric review by applying two bibliometric techniques: document co-citation analysis and co-word analysis.
Co-citation analysis, which studies the relationship between two co-cited papers, has been used to analyze the intellectual structure of scientific areas (Liu & Chen, 2012). Compared with citation-only analysis, co-citation analysis provides more reliable and insightful information of knowledge domains (Mustafee, Katsaliaki, & Fishwick, 2014).
CiteSpace has been used to convert and code the data from the title, author, keywords, abstract, institution, country, reference, and other detailed information, which is next analyzed and visualized. Then, with CiteSpace, co-citation networks of these data are formed and presented as clusters. In each cluster, the literature was classified by the structure and time indicators of research influence. The features of a cluster were identified from these aspects and include the prominent authors and the development of their milestone masterpieces, appearing as topics in the citation of articles, which show interconnections between the current intellectual focus and the research frontiers (Chen, 2017). Specifically, the five steps in the process of co-citation analysis are: 1) export the bibliographic record of cited articles from the databases; 2) code the data and construct a matrix of co-cited references using CiteSpace; 3) display the co-citation matrix in a node-and-link diagram; 4) use a variety of algorithms for clustering; and 5) interpret the characteristics of co-citation clusters.
Co-word analysis is a bibliometric technique that tracks the connections between concepts that co-occur in titles, abstracts, or keywords (Bernatović et al., 2021). Among the bibliometric methods, co-word analysis is the only method that uses the actual content of the documents to construct a similarity measure (Zupic & Čater, 2015).
The output of the co-word analysis is a network composed of topics and their relationships, which represent the conceptual space of a domain (Zupic & Čater, 2015). The networks were presented as a diagram that can be better understood as the emerging topics in the TC field. These emerging topics were identified depending on the word profiles derived from citing articles based on the weights of the noun terms used. Highly cited articles have higher frequencies of these noun terms and a greater weight value. The steps for this analysis are as follows: 1) divide data into periods as .net files and generate co-word networks in CiteSpace; 2) import the networks into an alluvial diagram generator; 3) use the filter function to simplify the diagram; and 4) interpret the changes over time.
However, there are several limitations in this study. First, only references from the Web of Science and Scopus databases are compiled. While these are the two most influential bibliographic databases globally, yet the scope of the publications may be limited. Second, the current study only selected the term “technical communication,” “technical writing,” “technical English,” and “technical and professional communication” for the search. These four distinct terms were used for the search criteria to ensure the research scope was broad enough to cover all related studies as well as to ensure reliability of the research. However, there might have been terms or keywords which were not taken into consideration and might have resulted in some references being excluded. On the other hand, the study’s findings mitigate this limitation as the results showed that the similarities among these terms (technical communication, business communication, professional communication, technical and professional communication) are strong enough and share some topical overlap in research articles (Carradini, 2020). Third, the current study only includes articles written in English. Both the Web of Science and Scopus databases include far fewer non-English journals, and this limited sample could be unrepresentative of the non-English studies. Nevertheless, future research could include articles published in other languages.
RESULTS AND DISCUSSION
The Intellectual Landscape of Technical Communication Research
In the analysis for research institutions, the most identified research institutions were American public research universities and included reputable universities, such as Arizona State University, Utah State University, Texas Tech University, University of North Texas, and the University of South Florida (Figure 2). Moreover, it was found that the researchers involved were not only from the English department but included the computer science, chemistry, and engineering departments. References with significant and notable tree-rings in red are high-impact contributions, highly cited, and have strong citation bursts (Chen, 2017). Therefore, it can be concluded from Figure 2 that TC research has been actively done in the English language departments and technical departments in recent years.
The map of the results of the co-citation cluster analysis indicates the intellectual base of the underlying specialty of TC. The five most significant clusters were identified as translation training, methodologies in TC, composition studies, rhetorical action, and industry’s need (Figure 3).
From the outcomes, the silhouette values of the five most significant clusters were over 0.85, which demonstrated their reliability. The quantitative calculation of the significance of the clusters provides a valuable contribution, but qualitative content analysis methods will need to be used to supplement and identify the central themes and intellectual structure. For this purpose, the qualitative content analysis is a summative content analysis which compares and contrasts the keywords or content, followed by the interpretation of the context (Hsieh & Shannon, 2005).
Further, the references with high-frequency co-citations in the five most significant clusters are summarized automatically and exported in Table 1.
The metrics and indicators of the research impact were taken into consideration as the citation counts, the h-index and its numerous extensions, and a rich set of altmetrics on social media were included (Chen, 2017). The following terms emerged as the most significant and influential cluster from these metrics: (a) translation training, (b) social justice, (c) transformative paradigm.
First, for TC translation, the current professional translation industry is concerned with the issues of sundry professional translation-related services and practices (Martín, 2020). To some extent, translation training is a value-added service for both industry and graduates’ employability, and we can infer that those professionals need to be equipped with TC skills for a solid support in their careers.
Second, social justice refers to issues related to social justice and ethics in the TC field. Social justice is the bridge from diversity to inclusion (Jones, Moore, & Walton, 2016). Initially, Williams and Pimentel (2012) addressed the significance of race, ethnicity, and multiculturalism in TC. Since then, scholars in the TC field have been exploring strategies for developing more inclusive methods. These methods significantly contributed to the TC field to collectively advocate for social justice as a central goal for a more inclusive research and pedagogy (Jones et al., 2016). Walton and Jones (2013) predicted that in the following five to ten years, one of the most critical research questions in the field of TC is how to navigate increasingly cross-cultural, cross-disciplinary, and cross-organizational contexts to support social justice through better communication because identity factors that touch upon race, class, gender, and sexuality are not mutually exclusive. Agboka (2014) noted that many research methods applied in the intercultural TC field were limited in responding to emerging social justice challenges, so he suggested decolonializing approaches as an alternative by highlighting how these approaches are used in intercultural research. The study of social justice also includes TC pedagogy, such as in preparing students to advocate for marginalized and under-resourced people in contexts from their local communities to employment organizations (Walton & Jones, 2013). Haas (2012) provided a case study of curriculum development for graduates, which support disciplinary inquiry at the intersection of race, rhetoric, technology, and TC. Some other studies include empirical research, such as a case study of engineering students and literature, culture, and digital media students participating in cross-disciplinary, cross-cultural distributed work teams (Paretti, McNair, & Holloway-Attaway, 2007) and cross-culture technology design for local users (Sun, 2012).
Interestingly, this cluster also includes references concerning the medical setting. Patients are seen as participants (those using technical writing outside professional situations) in co-construction and co-design of health care texts (Bellwoar, 2012). This situated study of local TC practices can be reproduced to expand the breadth of existing research. Thus, we begin to reimagine the broader scope of TC to include an approach to literacies in other fields, to a range of sites, to genres, and to texts that undo the privileging of patriarchal institutional spaces (Bellwoar, 2012).
In cluster 1, the summary report showed that the most active citer in the cluster is Mackerle’s (2001) Error estimates and adaptive finite element methods: A bibliography (1990-2000), we labeled it as methodologies in TC through content analysis. Mackerle (2001) proposed a new method to help professionals in engineering obtain information and communicate the results of research. In addition, Carliner (2012), Baehr (2015), Brumberger and Lauer (2015), and Boettger and Lam (2013) were identified as authors of high-impact publications. The sigma scores of these articles are relatively high because of their high structural centrality and intense citation burst. Carliner (2012) addressed that methods to professionalization were rooted in occupation theories, which mention standard components of infrastructure for occupations, such as professional organizations, bodies of knowledge, education, professional activities, and certification. Carliner (2012) proposed three approaches to professionalize TC: formal branding of the profession, the establishment of certification, and support for professional organizations. Baehr (2015) provided a snapshot of how industry leaders conceptualize technical communicators’ identities and relationships through a modified Delphi method. The findings showed that technical communicators function as agile, adaptable, and multi-specialists in a broad range of organizational functions. Brumberger and Lauer (2015) simultaneously analyzed information products, technologies, professional competencies, and personal characteristics requested by the industry. Boettger and Lam (2013) conducted a quantitative and qualitative analysis of papers published within five leading journals on TC from 1992 to 2011. The results showed that solid correlation variables, such as pedagogy, virtual collaboration, and intercultural communication were found. This review also investigated the original field that the researchers cited in their papers, which are business and TC and the STEM programs, communication studies, human-computer interaction, education, and linguistics and language behavior, writing studies, business and economics, information and knowledge management, gender studies, and medicine. Some scholars reviewed the research methodologies in TC, and they found that many tools, technologies, spaces, and practices of TC today dramatically changed (McNely, Spinuzzi, & Teston, 2015). McNely et al. believed that action research, participatory design, and visual methods have adapted and extended traditional qualitative approaches for nuances of contemporary TC. Therefore, it is necessary to review the relevant research on TC in the past 20 years to explore the evolutionary characteristics and future trends of the TC research field worldwide.
The following terms established composition studies as the third cluster: working professional; multilingual writing processes; building transdisciplinary connection; business communication. Studies in this cluster analyzed the form and content of TC. Some studies investigated the required TC-related competence in the industry. They all mentioned technical writing skills during multilingual writing processes as the basis of technical communicators (Brumberger & Lauer, 2015; Lanier, 2009). Further, more and more research discussed the standardization of TC, and technical communicators are required to meet the defined standards for authoring and managing content. Content management refers to topic-based information design and mainly refers to the technologies and processes that support the creation of highly adaptable and portable structured content (Andersen, 2014). Andersen (2014) also addressed the need for a praxis-based collaborative model for technical communication pedagogy and academic research and proposed that the best practice is rhetorical work from the content management perspective. A recent quantitative content analysis on TC journals found that the themes mainly focused on four categories: rhetoric, genre, pedagogy, and diversity (Boettger & Friess, 2020).
The references in cluster 3 have been active for 13 years (from 1995 to 2007) and less active since 2013. This cluster is dominated by significant terms, such as technical writing and curriculum development. In Figure 4, several outstanding references were displayed with the red outer ring. By reviewing these articles, we found that the research at the end of the last century focused on developing technical writing skills through pedagogical programs. Firstly, according to cultural theory, several studies support this notion, including Longo (1998), who suggested how technical writing was constituted as an object of study. Secondly, Longo (2000) addressed TC as a channel for scientific information and argued that the studies before fell short of considering the broader and more complex contexts. Longo’s (2000) work noted that some in the field of liberal arts have participated in causing disciplinary inequity by empowering scientists and engineers to privilege their form of knowledge over liberal arts expertise.
Moreover, Mirel and Spilka (2002) addressed that many TC practitioners found the current academic studies were irrelevant to their needs: The practices outlined in academic publications did not tally with the practitioners who have 11 years of industry experience. Another challenge was that technical communicators feel a lack of status, often marginalized within departments. One problem is a lack of understanding about the field among university administrators and colleagues. The other is that TC practitioners feel undervalued within their organizations because they face corporate layoffs sooner than product designers and engineers, whose contributions are perceived as a core position in companies. In addition, Allen and Benninghoff (2004) reported results from a survey of TC undergraduate programs concerning core concepts emphasized and most commonly taught procedures, skills, and tools in the United States. Giammona (2004) also concludes that the themes of the TC programs in the future are about innovation, global concerns, managing technical leaders and practitioners, and the impact of new technologies.
Cluster 4 labeled as industry need contained these significant terms: industry needs; connecting usability education; technical communication theory; career perspective; career theory; curriculum design. It has been less active since 2007 (Figure 4). However, some high-impact references were still identified from the timeline view. The contributions consistently focus on two topics in this field, which are highly consistent with the terms. First, some studies focused on the industry needs. For example, Schriver (1997) described creating a document based on the readers’ needs. Bazerman and Lander (2001) emphasized that rhetoric can occupy a “clearing” that is obscured in these other approaches to science studies.
Moreover, Spilka (2009) also discussed digital literacy for TC in the 21st century from the perspective of the TC industry. Redish’s (2007) book elaborated on how to design web content. A more recent study from the perspective of the TC industry focuses on the core competencies of technical communicators by analyzing the wide range of information products, technologies, professional competencies, and personal qualities required by an industry job posting (Brumberger & Lauer, 2015).
Another emerging issue under discussion is on connecting the academic and profession. Dias, Freedman, Medway, and Paré (1999) illustrated how writing functions within the activities of various disciplines, based on a seven-year comparative study of writing in different university courses and matched workplaces. They also elaborated further understanding of the relationships between writing in academic and workplace settings. Davis (2001) addressed the role of both academic programs and professional societies in shaping the profession’s future. Wilson and Ford (2003) investigated seven professionals on their experiences entering the TC field and provided helpful information regarding how academic preparation does not prepare students for workplace realities. Cooke and Mings (2005) investigated the knowledge, skills, and abilities that TC trainers needed to emphasize in teaching usability and how academic research in usability can benefit practitioners. For career theory in this cluster, Hart-Davidson (2001) studied the core competencies of TC and highlighted that theory was needed because the practitioners and scholars in TC should work together to make the core expertise of TC explicit.
Furthermore, the clusters can reflect paradigm shifts. Namely, a new paradigm replaces the existing paradigm and provides an overall framework for the research field (Chen, 2017). Hence, this can explain how the less active clusters were replaced by new emerging clusters. Together, from the timeline view and high-impact references, we found that the research focus shifted from cluster 4 (industry need) to cluster 1 (methodologies in TC), while cluster 3 (rhetorical action) shifted to cluster 0 (translation training) and cluster 2 (composition studies).
Conclusively, based on the above discussions, it is evident that the rapid expansion of TC to various fields is reshaping the TC academic and practical areas. In order to find more evidence of the evolutionary characteristics of TC research, we presented an alluvial diagram of TC research over the past 20 years.
Evolutionary Characteristics of Technical Communication Research from 2001 to 2020
For evolution analysis, as mentioned, the diagram was used to show the changes between time points. An alluvial diagram was generated to identify the evolutionary features of TC research over the past 20 years. An alluvial diagram with clusters ordered by size shows changes in network structures over time (Rosvall & Bergstrom, 2010). Following all streams from one cluster to another makes it possible to study the mergers with other clusters and the focus transitions in detail. In other words, curvilinear flows are suddenly interrupted in some clusters, which do not indicate the topic’s termination but transform into a new research topic. For instance, as seen in Figure 5, the Teaching cluster in first phase (2001–2005) was divided into methodology, engineering communication, and empirical analysis clusters in phase two (2006–2010). Moreover, the height of a stream represents the value of weight of a key word in one cluster (Ruan, Hou, & Hu, 2017). To simplify the figure and make it readable, the thin streams with less significant key words were filtered out. For example, in Figure 5, there are streams connecting the culture cluster in phase two (2006–2010) with succeeding clusters in phase three (2011–2015), but there is no keyword with high value. Hence, these thin streams were filtered when simplifying the diagram.
In the visualization of the alluvial diagram, a cluster is displayed as a block in a specific column. The citation flow of specific research is then determined based on the height of the corresponding block. Streamlines connect modules that contain the same nodes. The two connected nodes represent co-word articles, which means the same noun term co-occur in titles, abstracts, or keywords of two articles. The height of the streamline is proportional to the aggregated flow in the nodes present in the connected modules. For example, the rhetoric cluster in phase one (2001–2005) shares overlapping keywords with the methodology cluster in phase two (2006–2010).
Figure 5 shows various clusters during the four time phases. Analyzing data year by year would be tedious, so we defined the time slice as five years. However, the limitation here is that important details in each year are missed.
In the first phase (2001–2005), some significant clusters can be identified, such as rhetoric, teaching, scientific communication, usability, application software, and writing skills. The cluster is labeled by the keyword within it with the highest value (Ruan, Hou, & Hu, 2017).
As TC research proceeded to the second phase (2006–2010), five influential clusters emerged—methodology, engineering communication, empirical analysis, culture, and creativity. Dating back to 2009, there was some significant breakthrough of connection of industry and academia by conducting interdisciplinary research and empirical research (Lanier, 2009; Rude, 2009). This trend had boosted TC’s growth, including TC pedagogy, technology, and methodology.
In the third phase (2011–2015), some significant clusters emerged, labeled business, content management, engineering research, medical education, and learning system. During 2011–2015, both working situation and pedagogical system are prominent themes. Moreover, IR 4.0 promoted the advancement of many fields. Zhang (2017) even mentioned a significant challenge to adapt to inter-disciplinary and cross-disciplinary work requirements in the IR 4.0 era. To this end, TC is infiltrating applied disciplines, such as engineering and medical education. This finding is consistent with the result of the previous co-citation analysis. Specifically, we identified Bellwoar’s (2012) article in the medical context with high impact, supporting medical education became an important topic during this period.
In the fourth phase (2016–2020), previously identified pedagogy-related clusters had finally merged into the clusters labeled leadership, global TC, human-computer interaction, language processing system, and communication training. So far, regarding the increasing influence of globalization, TC has dramatically transformed the educational system in leadership, language processing system, and communication training. In addition, technology in TC, particularly human-computer interaction, is also the research frontier in this field. Finally, language learning and communication training are continuous emerging research trends in the following years. More interestingly, this finding is also consistent with the previous result of co-citation analysis because we investigated that cluster 0 (translation training) and cluster 2 (composition studies) are relatively active now.
In this study, a scientometric review was conducted, and the visualized bibliometric analysis was used to explore the development of TC research over the past two decades. We have offered reliable information so that technical communicators can quickly understand the intellectual landscape, evolutionary process, and research frontiers in the TC field via visualized maps, which may contribute to their future profession concerns. The results of co-citation analysis have revealed the intellectual landscape of TC research. First, TC research has been mainly active in the English language departments and technical departments in recent years. Second, we identified five main clusters as the intellectual structure of TC research, including translation training, methodologies in TC, composition studies, rhetorical action, and industry’s need. Third, the findings indicated paradigm shifts. From the timeline view and high-impact references, we found that the research focus shifted from cluster 4 (industry need) to cluster 1 (methodologies in TC), while cluster 3 (rhetorical action) shifted to cluster 0 (translation training) and cluster 2 (composition studies). It is evident that the rapid expansion of TC to various fields reshapes TC academic and practical areas. Together, the findings of evolution analysis have shown that the emerging trends of TC research are TC pedagogy, global TC, human-computer interaction, language learning and communication training. Therefore, future research interest will likely focus on language learning, online class, and technological tools.
While verifying the findings of previous qualitative studies, this study has made progress in the breadth and depth of previous reviews involving computer-assisted software to identify the intellectual structure of the TC field and track its evolutionary process. More importantly, the current study presented the dynamic development and paradigm shifts as well as the research frontier of the TC field in an innovative and visualized manner, which could benefit the wide range of readers in various fields related to TC. For example, technical communicators can use this research to supplement their work as the main themes and evolutionary process can be obtained from visualized figures instead of trying to sort through an overwhelming mass of journal articles.
This research project can help TCs recognize both where the field has been and where it is going, where it is relatively stable and where it is changing. In doing so, it can help TCs make more perceptive and productive efforts in their practice and teaching. For example, practitioners would recognize the roles and competencies in the TC trends related to language, technological tools, and human-computer interaction. Meanwhile, for curriculum designers, the delivery of language skills through online courses as well as using technological tools in blended learning could be taken into consideration.
Although the results of this study extend past bibliometric studies of TC, there were some limitations. Hence, in order for a more comprehensive and equitable approach, future research should address the following: 1) include articles from other languages besides English for a more international perspective; 2) collect data from more databases for a more inclusive view; 3) expand the review to include TC-related books, newspapers, and theses which may have significant outputs; and 4) include more relevant terms and keywords, such as business and technical communication so that the future emerging trends in the field are also captured.
Agboka, G. (2014). Decolonial methodologies: Social justice perspectives in intercultural technical communication research. Journal of Technical Writing and Communication, 44(3), 297–327. doi: 10.2190/TW.44.3.e
Allen, N., & Benninghoff, S. T. (2004). TPC program snapshots: Developing curricula and addressing challenges. Technical Communication Quarterly, 13(2), 157–185. doi: 10.1207/s15427625tcq1302_3
Andersen, R. (2014). Rhetorical work in the age of content management: Implications for the field of technical communication. Journal of Business and Technical Communication, 28(2), 115–157. doi: 10.1177/1050651913513904
Aryadoust, V., & Ang, B. H. (2019). Exploring the frontiers of eye tracking research in language studies: A novel co-citation scientometric review. Computer Assisted Language Learning, 1–36.
Baehr, C. (2015). Complexities in hybridization: Professional identities and relationships in technical communication. Technical Communication, 62(2), 104–117.
Bazerman, C., & Lander, D. (2001). The languages of Edison’s light. Canadian Journal of Communication, 26(2/3), 295.
Bellwoar, H. (2012). Everyday matters: Reception and use as productive design of health-related texts. Technical Communication Quarterly, 21(4), 325–345.
Bernatović, I., Slavec Gomezel, A., & Černe, M. (2021). Mapping the knowledge-hiding field and its future prospects: A bibliometric co-citation, co-word, and coupling analysis. Knowledge Management Research & Practice, 1–16. doi: 10.1080/14778238.2021.1945963
Boettger, R. K., & Friess, E. (2020). Content and authorship patterns in technical communication journals (1996-2017): A quantitative content analysis. Technical Communication, 67(3), 5–25.
Boettger, R. K., & Lam, C. (2013). An overview of experimental and quasi-experimental research in technical communication journals (1992–2011). IEEE Transactions on Professional Communication, 56(4), 272–293. doi: 10.1109/tpc.2013.2287570
Brumberger, E., & Lauer, C. (2015). The evolution of technical communication: An analysis of industry job postings. Technical Communication, 62(4), 224–243.
Carliner, S. (2012). The three approaches to professionalization in technical communication. Technical Communication, 59(1), 49–65.
Carradini, S. (2020). A comparison of research topics associated with technical communication, business communication, and professional communication, 1963–2017. IEEE Transactions on Professional Communication, 63(2), 118–138. doi: 10.1109/TPC.2020.2988757
Chen, C. (2017). Science mapping: A systematic review of the literature. Journal of Data and Information Science, 2(2), 1–40.
Chen, C., Ibekwe-SanJuan, F., & Hou, J. (2010). The structure and dynamics of cocitation clusters: A multiple-perspective cocitation analysis. Journal of the American Society for information Science and Technology, 61(7), 1386–1409. doi: https://doi.org/10.1002/asi.21309
Chen, C. M., Hu, Z. G., Liu, S. B., & Tseng, H. (2012). Emerging trends in regenerative medicine: A scientometric analysis in CiteSpace. Expert Opinion on Biological Therapy, 12(5), 593–608. doi: 10.1517/14712598.2012.674507
Cooke, L., & Mings, S. (2005). Connecting usability education and research with industry needs and practices. IEEE Transactions on Professional Communication, 48(3), 296–312. doi: 10.1109/tpc.2005.853938
Davis, M. T. (2001). Shaping the future of our profession. Technical Communication, 48(2), 139–144.
Dias, P., Freedman, A., Medway, P., & Paré, A. (1999). Worlds apart: Acting and writing in academic and workplace contexts. Mahway, NJ: Lawrence Erlbaum.
Fang, Y., Yin, J., & Wu, B. (2018). Climate change and tourism: A scientometric analysis using CiteSpace. Journal of Sustainable Tourism, 26(1), 108–126.
Friess, E., & Boettger, R. K. (2021). Identifying commonalities and divergences between technical communication scholarly and trade publications (1996–2017). Journal of Business and Technical Communication, 35(4), 407–432. doi: 10.1177/10506519211021468
Haas, A. M. (2012). Race, rhetoric, and technology: A case study of decolonial technical communication theory, methodology, and pedagogy. Journal of Business and Technical Communication, 26(3), 277–310. doi: 10.1177/1050651912439539
Hart-Davidson, W. (2001). On writing, technical communication, and information technology: The core competencies of technical communication. Technical Communication, 48(2), 145–155.
Hsieh, H. F., & Shannon, S. E. (2005). Three approaches to qualitative content analysis. Qualitative Health Research, 15(9), 1277–1288. doi: 10.1177/1049732305276687
Jiang, Y. W., Ritchie, B. W., & Benckendorff, P. (2019). Bibliometric visualisation: An application in tourism crisis and disaster management research. Current Issues in Tourism, 22(16), 1925–1957. doi: 10.1080/13683500.2017.1408574
Jing, X., Ghosh, R., Sun, Z., & Liu, Q. (2020). Mapping global research related to international students: A scientometric review. Higher Education, 1–19.
Jones, N. N., Moore, K. R., & Walton, R. (2016). Disrupting the past to disrupt the future: An antenarrative of technical communication. Technical Communication Quarterly, 25(4), 211–229. doi: 10.1080/10572252.2016.1224655
Kleinberg, J. (2003). Bursty and hierarchical structure in streams. Data Mining and Knowledge Discovery, 7(4), 373–397. doi: 10.1023/A:1024940629314
Lanier, C. R. (2009). Analysis of the skills called for by technical communication employers in recruitment postings. Technical Communication, 56(1), 51–61.
Liu, S. B., & Chen, C. M. (2012). The proximity of co-citation. Scientometrics, 91(2), 495–511. doi: 10.1007/s11192-011-0575-7
Longo, B. (1998). An approach for applying cultural study theory to technical writing research. Technical Communication Quarterly, 7(1), 53–73.
Longo, B. (2000). Spurious coin: A history of science, management, and technical writing: SUNY Press.
Lowry, P. B., Humpherys, S. L., Malwitz, J., & Nix, J. (2007). A scientometric study of the perceived quality of business and technical communication journals. IEEE Transactions on Professional Communication, 50(4), 352–378. doi: 10.1109/tpc.2007.908733
Mackerle, J. (2001). Error estimates and adaptive finite element methods: A bibliography (1990-2000). Engineering Computations, 18(5-6), 802–914. doi: 10.1108/eum0000000005788
Martín, M. M. (2020). Transcreation as a way to promote employability in translation training: adding value to translation training. Journal of Language and Communication in Business, 60, 125–139.
McNely, B., Spinuzzi, C., & Teston, C. (2015). Contemporary research methodologies in technical communication. Technical Communication Quarterly, 24(1), 1–13. doi: 10.1080/10572252.2015.975958
Mirel, B., & Spilka, R. (2002). Reshaping technical communication: New directions and challenges for the 21st century: Routledge.
Morar, M., & Agachi, P. S. (2010). Review: Important contributions in development and improvement of the heat integration techniques. Computers & Chemical Engineering, 34(8), 1171–1179. doi: 10.1016/j.compchemeng.2010.02.038
Mustafee, N., Katsaliaki, K., & Fishwick, P. (2014). Exploring the modelling and simulation knowledge base through journal co-citation analysis. Scientometrics, 98(3), 2145–2159. doi: 10.1007/s11192-013-1136-z
Niazi, M., & Hussain, A. (2011). Agent-based computing from multi-agent systems to agent-based models: A visual survey. Scientometrics, 89(2), 479–499. doi: 10.1007/s11192-011-0468-9
Pan, X. L., Yan, E. J., Cui, M., & Hua, W. N. (2018). Examining the usage, citation, and diffusion patterns of bibliometric mapping software: A comparative study of three tools. Journal of Informetrics, 12(2), 481–493. doi: 10.1016/j.joi.2018.03.005
Paretti, M. C., McNair, L. D., & Holloway-Attaway, L. (2007). Teaching technical communication in an era of distributed work: A case study of collaboration between US and Swedish students. Technical Communication Quarterly, 16(3), 327–352.
Redish, J. G. (2007). Letting go of the words: Writing web content that works. Morgan Kaufmann.
Rosvall, M., & Bergstrom, C. T. (2010). Mapping change in large networks. Plos One, 5(1). doi: 10.1371/journal.pone.0008694
Ruan, W., Hou, H., & Hu, Z. (2017). Detecting dynamics of hot topics with alluvial diagrams: A timeline visualization. Journal of Data and Information Science, 2(3), 37.
Rude, C. D. (2009). Mapping the research questions in technical communication. Journal of Business and Technical Communication, 23(2), 174–215. doi: 10.1177/1050651908329562
Schriver, K. A. (1997). Dynamics in document design: Creating text for readers. John Wiley & Sons, Inc.
Smith, E. O. (2000). Strength in the technical communication journals and diversity in the serials cited. Journal of Business and Technical Communication, 14(2), 131–184. doi: 10.1177/105065190001400201
Song, J. B., Zhang, H. L., & Dong, W. L. (2016). A review of emerging trends in global PPP research: analysis and visualization. Scientometrics, 107(3), 1111–1147. doi: 10.1007/s11192-016-1918-1
Spilka, R. (2009). Digital literacy for technical communication: 21st century theory and practice. Routledge.
Sun, H. (2012). Cross-cultural technology design: Creating culture-sensitive technology for local users: OUP USA.
von Luxburg, U. (2007). A tutorial on spectral clustering. Statistics and Computing, 17(4), 395–416. doi: 10.1007/s11222-007-9033-z
Walton, R., & Jones, N. N. (2013). Navigating increasingly cross-cultural, cross-disciplinary, and cross-organizational contexts to support social justice. Communication Design Quarterly Review, 1(4), 31–35.
Williams, M. F., & Pimentel, O. (2012). Introduction: Race, ethnicity, and technical communication. Journal of Business and Technical Communication, 26(3), 271–276. doi: 10.1177/1050651912439535
Wilson, G., & Ford, J. D. (2003). The big chill: Seven technical communicators talk ten years after their master’s program. Technical Communication, 50(2), 145–159.
Yeung, A. W. K. (2018). Data visualization by alluvial diagrams for bibliometric reports, systematic reviews and meta-analyses. Current Science, 115(10), 1942–1947. doi: 10.18520/cs/v115/i10/1942-1947
Zhang, H.-L. (2017). 工业4.0时代技能人才职业能力结构需求变化与职业教育调适策略[Research on the change of professional ability demand structure and the adjustment strategy of vocational education in the industrial 4.0 age]. Modern Education Management, (10), 108–112.
Zupic, I., & Čater, T. (2015). Bibliometric methods in management and organization. Organizational Research Methods, 18(3), 429–472. doi: 10.1177/1094428114562629
ABOUT THE AUTHORS
Luo Mingdan is a PhD student in the Faculty of Education, University of Malaya, Kuala Lumpur, Malaysia. Her research interests in technical communication, technical communication pedagogy, and curriculum design. She can be reached at UMedu.email@example.com
Dorothy DeWitt is an associate professor in the Curriculum and Instructional Technology Department, University Malaya, and a recipient of the Endeavour Executive Fellowship from the government of Australia. She has been doing research in instructional design, new pedagogies and technologies for knowledge management, collaborative mobile learning and problem solving. She can be reached at firstname.lastname@example.org
Norlidah Alias is an associate professor in the Curriculum and Instructional Technology Department, University Malaya. Her research focuses on developing digital pedagogies and designing futuristic curriculum focusing on technical and vocational education and training as well as environmental education. She can be reached at email@example.com.