Charting Scholarly Horizons: Scientometrics in Southeast Asia’s Information Research Landscape

Information research has grown exponentially in recent decades due to rapid technological advancements and the proliferation of digital data. As a key region in the global information landscape, Southeast Asia presents unique opportunities and challenges for knowledge production and dissemination. However, the dynamics of scientific communication within Southeast Asia’s diverse cultural and socioeconomic contexts remain underexplored.

This study aims to address this gap by employing scientometric techniques to analyze trends in Southeast Asia’s information research output over the past decade.

Scientometrics, defined as “the quantitative study of science and technology and their related aspects” (Hood & Wilson, 2001, p. 5), provides an objective framework for mapping the development of scientific fields and identifying influential publications, authors, and institutions (Van Eck & Waltman, 2014). Previous scientometric analyses have illuminated research trends in diverse domains such as biomedicine (Aria & Cuccurullo, 2017), sustainability science (Mukherjeeet al., 2017), and information science (Bouabid & Larivière, 2018). However, scientometric studies focusing specifically on Southeast Asia’s information research landscape remain scarce.

The proposed study seeks to address this need by conducting a comprehensive scientometric analysis of publications related to information research produced in Southeast Asia between 2014-2023. By examining metrics such as publication output, citations, collaboration patterns, and keyword trends over time, this study aims to provide a quantitative snapshot of the region’s scholarly horizons in this field. Such insights are significant for several reasons:

This study is grounded in the theoretical framework of scientometrics, which utilizes bibliometric techniques to quantitatively analyze scientific outputs and map the development of research fields (Hood & Wilson, 2001). Bibliometrics refers to “the application of quantitative analysis and statistics to publications such as journal articles and their accompanying citation counts” (Borgman & Furner, 2002, p. 1). Key bibliometric indicators that will be examined in this study include publication counts, citation analysis, co-authorship networks, keyword analysis, and institutional collaboration patterns.

Previous scientometric studies have established theoretical and methodological frameworks that will inform the current analysis. For example, Van Eck and Waltman’s (2014) work on visualizing the structure of science through citation network analysis provides a model for mapping collaboration patterns and research clusters. Aria and Cuccurullo’s (2017) large-scale bibliometric analysis of biomedicine demonstrates techniques for identifying influential publications, authors, and journals. Additionally, Mukherjeeet al.’s (2017) examination of keyword trends in sustainability science offers insights into tracking emerging research areas over time.

By applying established bibliometric techniques within the theoretical framework of scientometrics, this study aims to quantitatively profile Southeast Asia’s information research landscape and identify key trends, opportunities, and gaps. The results will contribute new knowledge about the dynamics of scientific communication within this unique regional context.

By triangulating quantitative bibliometric techniques with qualitative network analysis and thematic coding, this study aims to develop a nuanced understanding of Southeast Asia’s information research landscape over the past decade. The mixed-methods approach strengthens the validity and reliability of results (Johnsonet al., 2007).

This proposed study is significant for several reasons. First, it will address the dearth of scientometric analyses focusing specifically on Southeast Asia’s information research landscape. By mapping trends, networks, and influences over the past decade, the study aims to provide the first comprehensive profile of this scholarly domain within the region.

Second, the results will offer valuable insights for policymakers, research administrators, and funding bodies seeking to better understand and support the region’s knowledge production dynamics. Key indicators such as publication output trends, institutional collaboration patterns, and emerging areas of study can inform strategic decision making and resource allocation.

Third, the study contributes new knowledge that advances scientometric theory and methodology. By applying established bibliometric techniques to analyze Southeast Asia’s diverse scholarly contexts, novel indicators or analytical approaches relevant to the Global South may emerge. This can enrich the theoretical and methodological toolkit of scientometrics.

Finally, the results have implications for capacity building within Southeast Asia’s information research community. By identifying influential publications, authors, and institutions, the study highlights expertise that can be leveraged for networking, mentorship, and collaborative opportunities. Knowledge gaps may also be addressed through targeted training or research initiatives.

In summary, this proposed scientometric analysis of Southeast Asia’s information research landscape over the past decade is significant for addressing current gaps in the literature, informing policy and practice, advancing scientometric theory, and strengthening regional research capacity. By mapping trends, networks and influences through quantitative bibliometric techniques and qualitative network analysis, the study aims to provide novel insights into the dynamics of scientific communication within this context.

A statistical analysis technique called bibliometrics is used to evaluate a subject’s features and key developmental patterns by examining published research articles. It is a tried-and-true technique for gathering and spotting important research in a variety of scientific and medical domains. Scholars can give both objective and subjective results about the most significant works in a field by carefully analysing TC count, since it is believed to be predictive of an article’s overall influence.

On Wednesday 17, 2024 a comprehensive search string was extracted from Web of Science citation database for identification, and downloaded of relevant papers published between January 2014 to December 2023 on Information trend, Information retravel, data science, machine learning in information retrieval research. The keyword related to information trend was used in TS=(“Information retrieval” OR “publication trends” or “data science” OR “machine learning in information retrieval” OR “research impact assessment” or “bibliometrics” OR “citation analysis”) and 2014 or 2015 or 2016 or 2017 or 2018 or 2019 or 2020 or 2021 or 2022 or 2023 (Publication Years) and SINGAPORE or MALAYSIA or THAILAND or VIETNAM or BRUNEI (Countries/Regions). Total 786 publications 17,413 citations, 22.1 Avarage citations per papers and 58 h index identified, which were rearraigned in the decreasing order of citations, The data was used year wise, subject area, source type, organisations, authors, journals, country wise, and keywords. The data was used to manage the extracted data and perform statistical analysis and developed bibliometric analysis. The 1,393 records were extracted as a CSV file and imported by Biblioshiny and VOSViewer software, which provides a network visualization of publications, including bibliographic coupling, co-authorship, Co-occurrence analysis, countries, organisations, authors, Journals and keywords.

The data covers a period of 10 years from 2014 to 2023. There are 419 sources, which could include journals, books, or other document repositories. There are a total of 786 documents in this dataset. The dataset indicates a negative annual growth rate of -19.73%. This suggests a decline in the number of documents over time. The average age of the documents is 3.75 years, indicating that the content is relatively recent. Each document has an average of 21.8 citations, suggesting that the documents are cited frequently. There are 2353 Keywords Plus (ID) and 3058 Author’s Keywords (DE) in the documents. There are 3112 authors in total. There are 22 authors who have single-authored documents. There are 27 single-authored documents, and on average, each document has 4.96 co-authors. This suggests a high level of collaboration. International collaboration is at 71.25%, indicating a significant proportion of collaboration across borders. The document types include articles (545), data paper (1), early access articles (16), proceedings papers (7), corrections (1), editorial materials (13), editorial materials with early access (1), letters (1), meeting abstracts (1), reviews (192), and early access reviews (8).

Tables 1 and 2 illustrate the upward trend in the total number of publications. The total publications seem to be rising steadily over time, suggesting expansion or advancement of some kind. For each year, the percentage of the total 786 is given. The fact that the percentages add up to just over 100% is an intriguing observation. The total publications increased significantly between 2019 and 2020, from 70 to 98, and this growth is also seen in the publications 100% of the total. Although the publications values rise annually, the rate of increase varies. For instance, there is a significant growth in both publications and percentage terms from 2018 to 2019, while the increase in publications terms from 2022 to 2023 is lower, even though the percentage grows.

The distribution of document types in a publication dataset is shown in the Table 4 and Figure 1. With 569 instances, articles are the most common document type in the sample. Original research findings, analyses, or investigations are usually presented in articles. With 200 records, review articles rank as the second most popular document type. Documents with an Early Access TP of 25 are those that are made available prior to the official publishing date. Editorial materials (TP=14) frequently consist of viewpoints from the editorial team, commentary, and opinion pieces. Research presented at conferences is usually presented in procedural papers (TP=7), which are developed from conference proceedings. Errors in previously published works are corrected in correction (TP=1) documents. The description of datasets, techniques, and data gathering procedures is the main focus of the data paper (TP=1).

Figure 1:
Publication types and impact.

According to Web of Science (WoS), the cited publications in publications trend in data science, bibliometrics were selected most productive research area. The research contributions in these subfields varied widely, Computer science 306 (38.931%) publications, followed by Engineering 167 (21.247%) publications, Information Science Library Science 86 (10.941%) publications, Environmental Sciences Ecology published 82 (10.433%) publications, Science Technology Other Topics 81 (10.305%) publications, Telecommunications 56 (7.125%) publications, Business Economics 52 (6.616%) publications, Physics 30 (3.817% publications etc., (Table 3).

The most collaborative countries network shows the performance of research collaboration between each other’s. Table 4 and Figure 3 shows the intensity of the relationship, i.e., Malaysia and Singapore have the highest values in the “TP” column, indicating they may be leading in the metric being measured. Countries like China, USA, Thailand, and Vietnam also have relatively high values, suggesting they are significant in the analysis. Countries like Bangladesh, Indonesia, and Nigeria have lower values, indicating they may have less influence or impact according to the metric. The distribution of values varies widely, indicating a diverse range of performances or contributions among the listed countries. Without knowing what “TP” represents, it’s hard to draw specific conclusions. It would be helpful to understand the context and purpose of this analysis (Table 5).

Figure 3:
Most collaborative institutions.

It appears that you’ve provided a Table 6 related to institutional research output analysis, with columns for “Affiliations,” “TP” (presumably standing for some form of output), and “% of 786.” Here are some observations (Table 6):

Nanyang Technological University, National University of Singapore, and University Malaya are among the top contributors (n=100, 12.723%) each having a significant percentage of the total output. The Table 5 includes a diverse range of institutions from various countries, including Singapore, Malaysia, Thailand, Vietnam, and others. Several institutions have the same output (“TP”) values, indicating that they contribute equally to the research output. The “% of 786” column provides the percentage contribution of each institution to the total research output. It seems to be based on a total count of 786, and the values reflect the proportion of each institution’s output relative to this total. Institutions like the University of California System and the Chinese Academy of Sciences suggest an international collaboration or research presence. The percentages vary widely, ranging from over 12% to around 1.5%, highlighting the diversity in the contributions of different institutions. Further analysis could involve looking for trends over time, comparing the performance of institutions within the same country, or exploring the types of research being conducted.

Table 7 presents the profile of the top 20 highly productive authors and top 20 most impactful authors The most productive authors in data science, bibliometrics publication trends are listed in Table 5 and Figure 4, along with their average citation with publications, the total number of citations, and the total number of publications, Table 5 and Figure 4 shows that the most productive 414 authors participated in 786 Asian countries Data science, machines learning, publications trends, of which 88 authors published 1 article each, 524 authors published 2 papers each, 164 authors published 3 papers each, 34 authors published 4 papers each, 11 authors published 5 papers each, 42 authors published 5 papers each, 6 authors published 6 papers each, 4 authors published 7 papers each. Mosavi, Amir, Obuda University leads the Table 5 and Figure 2 highest i.e., 54 (3.053%) publications, 796 citations, followed by Kumar, Satish, Indian Institute of Management Nagpur, published 23 (2.926%) publications, 2072 citations and 156.87 average citation per papers, Hallinger, Philip, Mahidol University published 16 (2.036%) publications, 2072 citations and 156.87 average citations per papers.

Figure 2:
Top 29 countries collaboration network map.

Figure 4:
Most productive and impactful authors.

Figure 5 shows the most frequent indexing keywords and their frequency of occurrence in Southeast Asia’s Information Research. The keywords that appeared at least 1900 times in 786 publications were listed. 50 keywords 4 clusters, 700 links and 1900 total link strength, i.e., bibliometrics 190 occurrences with 189 total link strength followed by data science 84 occurrences with 190 total link strength, information retrieval 77 occurrences with 44 total link strength bibliometrics analysis 77 occurrences 159 total link strength respectively.

Figure 5:
Countries collaboration.

The scientometric analysis conducted in the study “Charting Scholarly Horizons: Scientometrics in Southeast Asia’s Information Research Landscape” offers valuable insights into the scholarly dynamics of Southeast Asia’s information research landscape. The study utilized bibliometric techniques to quantitatively analyze the research output in the region over the past decade. Scientometrics, as defined by Hood and Wilson (2001), involves the quantitative study of science and technology and their related aspects. By examining metrics such as publication output, citations, collaboration patterns, and keyword trends, the study aimed to provide a comprehensive profile of the scholarly horizons in Southeast Asia’s information research field (Ahmed & Sab, 2024).

The findings of the study revealed a significant volume of publications focusing on various aspects of information research, including trends, retrieval, data science, and machine learning. Despite a negative annual growth rate, the average citations per paper and the calculated h-index indicated substantial engagement and impact within the scholarly community (Ahmed & Sab, 2024). The study also identified prominent researchers and academic institutions contributing to Southeast Asia’s information research, highlighting collaborative networks and expertise clusters. The relatively recent age of the documents emphasized the dynamic nature of scholarly communication in the region (Ahmed & Sab, 2024).

The study’s conclusions underscored the importance of continued research and collaboration to advance knowledge and address the challenges in Southeast Asia’s information landscape. By understanding the trends, challenges, and opportunities highlighted in the analysis, stakeholders can navigate and contribute to the evolving scholarly horizons of Southeast Asia effectively (Ahmed & Sab, 2024).

In conclusion, the scientometric analysis presented in the study sheds light on the scholarly dynamics of Southeast Asia’s information research landscape. The study’s findings provide a foundation for further research and collaboration in the region to foster academic excellence and address societal needs effectively.

The scientometric analysis of Southeast Asia’s information research landscape provides valuable insights into the region’s scholarly dynamics. The study revealed a notable volume of publications focused on various facets of information research, including trends, retrieval, data science, and machine learning. Despite a negative annual growth rate, the average citations per paper and the calculated h-index indicate significant engagement and impact within the scholarly community. Through co-authorship analysis and affiliation data, prominent researchers and academic institutions contributing to Southeast Asia’s information research were identified, highlighting collaborative networks and expertise clusters. The relatively recent age of the documents underscores the dynamic nature of scholarly communication in the region. This study underscores the importance of continued research and collaboration in advancing knowledge and addressing the challenges inherent in Southeast Asia’s information landscape.

By understanding the trends, challenges, and opportunities highlighted in this analysis, stakeholders can better navigate and contribute to the evolving scholarly horizons of Southeast Asia. Further exploration and interdisciplinary approaches are warranted to harness the full potential of information research in addressing societal needs and fostering academic excellence in the region.