Three Decades of Research Trends in Rhinology: A Bibliometric Analysis of the Journal of Rhinology

Abstract

Background and Objectives

This study conducted a comprehensive bibliometric analysis of articles published in the Journal of Rhinology (JR), the official journal of the Korean Rhinologic Society, to examine research trends, thematic evolution, and emerging hotspots in rhinology.

Methods

A total of 836 JR articles (1994–2025) were retrieved from PubMed and Research Information Sharing Service (RISS) after duplicate removal. The R bibliometrix package was used to perform keyword trend and thematic evolution analyses. VOSviewer was used to visualize keyword co-occurrence networks and temporal relationships between keywords. Gephi was used to calculate centrality measures, providing insight into the structural characteristics of the research network.

Results

From 1994 to 2025, JR published an average of 26.6 articles per year, with publication activity increasing in recent years. Keyword and thematic analyses demonstrated that the research focus gradually shifted from basic disease- and anatomy-related topics and traditional clinical themes in the 2010s to functional conditions, infectious diseases, and increasingly surgical, procedural, and methodological research after 2020, while “rhinitis” and “sleep apnea syndromes” were consistently addressed. Co-occurrence analysis further identified “endoscopy” as a central keyword, highlighting its continued importance in JR research.

Conclusion

The articles published in JR encompass a broad spectrum of rhinology research, integrating disease pathophysiology, clinical applications, surgical techniques, and evidence-based approaches. These findings highlight evolving research trends and provide guidance for future domestic and international studies in rhinology.

INTRODUCTION

In recent years, bibliometric analysis has gained recognition as an analytical method in medical research [1]. This approach enables the systematic interpretation of bibliographic information to analyze and visualize the development of specific research fields. Through bibliometric analysis, researchers can obtain insights into overall research trends, thematic shifts, emerging hotspots, and potential research gaps [2]. In particular, keyword analysis provides insight into evolving research domains and may help guide future research directions [3].

Within medical research, rhinology has advanced substantially over the past decade through technological progress and interdisciplinary integration, making it a timely subject for bibliometric exploration [4]. Ongoing technological developments have facilitated the rapid elucidation of rhinologic disease mechanisms in recent years [5]. However, these advances have also made it increasingly challenging to remain current with the expanding knowledge base in the field. Bibliometric analysis of prior publications may serve as a valuable tool for tracking and synthesizing this rapidly evolving research landscape [6,7].

The Journal of Rhinology (JR) [8] is the official international journal of the Korean Rhinologic Society and is dedicated to advancing knowledge in the diagnosis and treatment of nasal and paranasal sinus diseases. Established in 1994, it has served as a platform for disseminating scientific advances and promoting academic exchange in this evolving specialty. JR publishes basic, clinical, and translational research articles, providing comprehensive insights into rhinology. JR was a Korea Citation Index (KCI) candidate from 2007 to 2009, has been officially indexed since 2010, and is currently listed in Scopus, reflecting its growing international recognition.

Despite the important role of bibliometric analysis in identifying research trends, no previous study has comprehensively examined the research landscape of rhinology in Korea. Therefore, we conducted a bibliometric analysis of all articles published in JR to provide an overview of the current state of rhinology research and to identify potential areas for future investigation. This will allow for a clearer understanding of research interests, with the ultimate goal of providing a comprehensive bibliometric profile of JR as a whole.

METHODS

Data source

The literature search was conducted on July 14, 2025. PubMed and Research Information Sharing Service (RISS) were searched, and all JR publications were screened for inclusion. Because JR was not indexed in PubMed from 1994 to 2021 [9], 786 articles were retrieved from RISS [10] and exported to EndNote [11]. Additionally, 102 articles published between 2022 and 2025 were retrieved from PubMed using the search strategy “Journal of Rhinology [Journal].” Two authors independently cross-checked the records and manually removed 52 duplicate articles available in both Korean and English. In total, 836 articles published between 1994 and 2025 were included in the analysis (Fig. 1).

Fig. 1.

Flow diagram demonstrating the analysis methodology. RISS, Research Information Sharing Service.

Keywords were standardized prior to analysis to minimize redundancy and ensure conceptual consistency using a stepwise workflow. First, lexical normalization was performed to address superficial differences among keywords, including variations in plurality, spelling, and word form (e.g., “neoplasm” and “neoplasms” were unified under “neoplasm”). Similarly, identical concepts with minor linguistic variations were merged at this stage (e.g., “nasal septal perforation” and “nasal septum perforation” were unified under “nasal septal perforation”). Second, the normalized keywords were grouped according to the Medical Subject Headings (MeSH) database. Conceptually overlapping terms were consolidated under the official MeSH descriptor. This process enabled the unification of terms representing similar concepts, such as “SARS-CoV-2” and “Coronavirus.” The first two steps were conducted independently by two researchers and subsequently cross-checked to ensure consistency and validity. Third, to enhance clinical relevance, the keyword grouping decisions were independently validated by one author (JY Kim), an expert in otorhinolaryngology with more than 20 years of clinical experience and expertise in medical informatics. This reviewer reassessed the retrieved terms and their assigned groupings. For expert validation, a professor of otolaryngology reviewed the MeSH-consolidated keyword list and reclassified keywords with a frequency of five or more to ensure appropriate clinical contextualization. Keywords without an assigned group label were retained in their original form, whereas keywords assigned to a group were standardized using the representative group term. This process reduced the number of unique keywords from 120 original terms to 72 standardized groups (Supplementary Table 1 in the online-only Data Supplement). This expert-guided refinement was applied consistently in subsequent analyses to maintain clinical relevance while preserving less frequent, conceptually distinct terms.

Bibliometric analysis

Publications from 1994 onward (corresponding to Vol. 1 of JR) were used to analyze annual publication volume. Keyword analyses were restricted to publications from 2008 onward because RISS data completeness before 2008 could not be ensured. Korean keywords were translated into English to reduce redundancy, and duplicate keywords were removed.

The R bibliometrix package (version 5.1.0) [12] was used to analyze annual publication trends, keyword trends, and thematic evolution. The minimum keyword occurrence threshold was set at 5. Each keyword was represented by a dot indicating the median year of appearance and was sorted according to this value. Dot size reflected frequency, and lines connecting the first and third quartiles represented the primary period of discussion. For thematic evolution analysis, the top 250 keywords meeting the minimum frequency threshold were clustered using the “walktrap” algorithm, which identifies related keyword clusters based on random walks [13]. The period from 2008 to 2025 was divided into four intervals, and clusters predominating in each interval were identified. Thematic transitions across intervals were illustrated using directional arrows.

Text network analysis

VOSviewer (version 1.6.20) [14] was used to conduct co-occurrence analysis of author-provided keywords. A bibliometric map was generated using the full counting approach, with all keywords as the unit of analysis. The minimum occurrence threshold was five. Two network visualizations were produced: 1) a network visualization illustrating keyword clusters and 2) an overlay visualization depicting temporal relationships based on average publication year. Each keyword was represented as a node, and each edge represented co-occurrence frequency. Link thickness reflected connection strength. The total link strength of a node was defined as the sum of its connection strengths. Clusters were distinguished by color and represented thematic domains. Denser areas indicated well-developed research domains, whereas sparser regions reflected emerging or niche topics. The average publication year was used to identify emerging themes.

The number of links, total link strength, and number of occurrences were obtained using VOSviewer. Closeness centrality and betweenness centrality values for each keyword were calculated through the “network overview” tab and then exported using the “data laboratory” feature in Gephi (version 0.10.1) [15] to assess their network properties. Closeness centrality, betweenness centrality, and the average publication year data were calculated and extracted using Gephi’s native “network diameter” plug-in provided in the “network overview” tab. Together, these metrics provided a comprehensive characterization of the research network (Table 1).

Table 1.

Top 10 author’s keywords ranked by occurrence frequency

No.	Label	Occurrence*	Link	Total link strength	Betweenness centrality	Closeness centrality	Major publication year
1	Paranasal sinus	85	27	92	143.650	0.696	2014
2	Sleep apnea syndromes	74	9	18	31.168	0.475	2017
3	Sinusitis	71	28	82	191.119	0.706	2015
4	Endoscopy	63	32	82	262.342	0.75	2015
5	Rhinitis	43	14	25	78.751	0.539	2011
6	Nasal polyps	35	11	25	86.856	0.552	2014
7	Nasal cavity	34	18	35	66.646	0.608	2015
8	Neoplasms	26	15	27	40.585	0.558	2015
9	Nasal septum	22	17	28	37.688	0.585	2016
10	Fungal ball	17	12	26	15.940	0.558	2014

^*based on “bibliometrix” results, which report keyword frequencies without a minimum threshold.

RESULTS

Publication trends

We analyzed JR’s annual scientific output from 1994 to 2025 (Fig. 2). The annual publication volume averaged 26.6 articles per year through 2024. The highest annual output occurred in 2009 (35 articles), whereas the lowest was recorded in 2001 (13 articles). Over the most recent five-year period, the average increased to 29.4 articles per year, indicating an upward trend in recent publication activity.

Fig. 2.

Annual scientific production.

The frequency of each keyword’s appearance reflects the main research interests of JR. We examined the most frequently used keywords in JR from 1994 to 2025 and identified the top 15 keywords (Fig. 3). The most frequently appearing keyword was “paranasal sinus” (n=85), followed by “sleep apnea syndromes” (n=74), “sinusitis” (n=71), and “endoscopy” (n=63).

Fig. 3.

Most relevant words.

By identifying the periods during which keywords were most actively used, we can infer JR’s research priorities and how these priorities changed over time. We analyzed the first and third quartiles of each keyword’s occurrence period to represent the interval during which the keyword was predominantly cited in JR (Fig. 4). Based on these results, we examined high-frequency terms longitudinally. Around 2015, “sinusitis” and “endoscopy” showed high frequencies and were consistently observed for approximately 10 years (approximately 2011–2021). In addition, “paranasal sinus” appeared frequently around 2016 and was sustained for a relatively long period (2010–2020). Around 2018, “sleep apnea syndromes” became prominent and continued to appear from 2012 to 2022. In contrast, keywords such as “Caldwell–Luc operation” and “epithelial cells,” which were more common in the early 2010s, were not sustained in later years. More recently, after 2020, methodological keywords such as “meta-analysis” and “surveys and questionnaires” newly emerged.

Fig. 4.

Trend topics from 2008 to 2025.

Thematic evolution

From 2008 to 2025, keywords were clustered using the walktrap algorithm, and the most frequently discussed clusters in each period were identified (Fig. 5). “Rhinitis” and “sleep apnea syndromes” appeared across all periods, indicating that these clusters have been consistently addressed in JR. From 2008 to 2012, keywords related to nasal anatomical structures and diseases directly associated with the nose (e.g., “nasal cavity” and “paranasal sinus”) predominated. From 2013 to 2016, this pattern remained similar, although diagnostic technique–related keywords such as “computed tomography” were added. From 2017 to 2021, keywords related to infectious diseases (e.g., “SARS-CoV-2”) and procedural topics (e.g., “rhinoplasty”) emerged. From 2022 to 2025, surgical method–related keywords, including “endoscopy” and “septoplasty,” became prominent. Overall, basic disease-related keywords such as “nasal polyps” and “neoplasms” were dominant in earlier periods, whereas surgical and procedural keywords such as “rhinoplasty” and “septoplasty” became more prominent in recent years.

Fig. 5.

Thematic evolution.

Co-occurrence analysis

A total of 1,019 keywords were identified, of which 49 met the threshold of 5 minimum occurrences (Fig. 6). The network demonstrated seven clusters with 208 links and a total link strength of 395. The first cluster (9 terms), colored red, focused on nasal cavity anatomy and obstruction, including epistaxis, turbinate surgery, and SARS-CoV-2. The second cluster (7 terms), colored green, concentrated on inflammatory and immune responses in rhinitis, asthma, and nasal polyps. The third cluster (7 terms), shown in dark blue, encompassed skull base pathology and reconstruction, including neoplasms and cerebrospinal fluid. The fourth cluster (7 terms), colored yellow, focused on pediatric conditions and sleep apnea syndromes alongside surgical interventions such as tonsillectomy and rhinoplasty. The fifth cluster (6 terms), colored purple, addressed paranasal sinus pathology, particularly sinusitis and fungal infections such as aspergillosis. The sixth cluster (5 terms), visualized in light blue, encompassed endoscopic nasal surgery and associated symptoms, including facial pain and headache. The seventh cluster (5 terms), colored orange, focused on nasal septal structural conditions and septoplasty. The final cluster (3 terms), colored brown, concentrated on surgical treatment outcomes and the use of computed tomography.

Fig. 6.

Co-occurrence network visualization of research topics, organized by cluster.

Among the analyzed keywords, “paranasal sinus” appeared most frequently (n=85), followed by “sleep apnea syndromes” (n=74), “sinusitis” (n=71), and “endoscopy” (n=63). In betweenness centrality, “endoscopy” ranked highest (262.342), and “sinusitis” (191.119) and “paranasal sinus” (143.650) also showed strong bridging roles within the co-occurrence network. For closeness centrality, “endoscopy” ranked highest (0.750), followed by “sinusitis” (0.706), “paranasal sinus” (0.696), and “nasal septum” (0.574), indicating that these terms served as central connectors across research themes. The terms with the highest number of links were “endoscopy” (n=32), “sinusitis” (n=28), “paranasal sinus” (n=27), and “nasal cavity” (n=18), indicating broad relevance across the network. The terms with the highest total link strength were “paranasal sinus” (n=92), “endoscopy” (n=82), “sinusitis” (n=82), “nasal cavity” (n=35), and “nasal septum” (n=28). High total link strength indicates strong connectivity with multiple research clusters, suggesting that these terms were well integrated across thematic domains.

DISCUSSION

This study represents the first effort in the Korean rhinology field to systematically analyze research trends in JR using bibliometrix-based methods. By evaluating high-frequency keywords from the inception to July 14, 2025, we identified “sleep apnea syndromes,” “sinusitis,” and “paranasal sinus” as central topics. In addition, since the onset of the COVID-19 pandemic in 2020, research themes have broadened to include infection- and complication-related keywords such as “SARS-CoV-2” and “cerebrospinal fluid.” From a surgical perspective, “rhinoplasty” and “endoscopy” were prominent. Methodologically, the increasing use of “meta-analysis” suggests a growing emphasis on systematic investigation and evidence-based approaches.

Recent rhinology research has expanded beyond an exclusive focus on the nasal cavity to include functional and systemic conditions that affect overall health. Notably, the emergence of “sleep apnea syndromes” as a distinct research topic suggests that rhinology increasingly addresses broader and more complex clinical problems [16–18]. With advances in endoscopic techniques, imaging tools, and treatment approaches, clinicians and researchers are now better able to evaluate and manage sleep apnea syndromes [19,20]. These patterns suggest that JR has increasingly reflected a clinical perspective extending beyond local disease mechanisms to broader health considerations.

“Paranasal sinus” and “sinusitis” have consistently appeared as core JR research topics over time, indicating sustained scholarly interest in sinonasal disease. These keywords were frequently connected with “endoscopy” in the co-occurrence network, suggesting that endoscopy-based surgical strategies represent an important research axis in JR studies of sinonasal disorders. This pattern is consistent with prior reports indicating that endoscopic techniques have contributed to surgical research by enabling detailed visualization of anatomical structures and improving surgical precision [21,22]. The present findings similarly indicate stable, long-term trends, suggesting steady growth in surgery-related research within JR. In parallel, as research on related themes has accumulated, the importance of systematically synthesizing evidence has increased. The rising prominence of “meta-analysis” further reflects growing attention to structured and objective study designs, consistent with the expansion of evidence-based approaches in rhinology [16,18,23–25].

This study has several limitations. First, bibliographic data collection was not fully consistent across years. For example, keywords from 1994 to 2007 were incompletely retrieved; however, after JR’s inclusion in KCI in 2008, keywords from 2008 to 2020 were more completely captured through RISS. Furthermore, since indexing in PubMed in 2022, more comprehensive records, including standardized bibliographic data and keywords, have been available. Despite these discrepancies, we conducted an analysis spanning JR’s full publication history, from the inaugural issue to the most recent volume. Accordingly, our findings provide insight into the academic trajectory of rhinology research in Korea.

Second, this keyword-based approach inherently assumes that author-assigned keywords adequately represent the broader research landscape. If keywords are selected inconsistently, research topics may be misclassified, potentially biasing trend interpretation. Nevertheless, although some representational error is possible at the individual-article level, the sample size of 836 publications may mitigate the influence of such variability. Therefore, the overall trends identified here are likely to remain informative, while acknowledging the limitations of reliance on author-provided keywords.

Third, because this study focused on a single journal (JR), generalizability to the broader rhinology literature is limited. In addition, the number of publications analyzed was finite, and geographic concentration of authors or institutions could have introduced bias. Nevertheless, JR encompasses approximately 30 years of research, and the dataset includes international authors and institutions, supporting a degree of global relevance. Future studies should incorporate broader domestic and international journal samples and apply more comprehensive data collection and analytic methods to generate findings that can be more broadly generalized across the field of rhinology.

Supplementary Materials

The online-only Data Supplement is available with this article at https://doi.org/10.18787/jr.2025.00061.

Supplementary Table 1.

Keyword standardization of medical terms prior to analysis