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Introduction: The distribution pattern and knowledge structure of psychiatric genomics were surveyed based on literature dealing with both psychiatry and genomics/genetics. Coword analysis and bibliographic coupling of the records retrieved from Scopus and PubMed for 2016–2020 revealed the subsurface research aspects. Method: The data were analyzed using coword analysis and clustering methods using Sci2 and VOSviewer. Result: Analysis of ~3800 records showed that psychiatric genomics is, as expectedly, covered largely under biomedical subjects with a visible interest in other disciplines such as humanities and ethics. A coword analysis was done for all the years, followed by a year-wise analysis based on the keywords, and then a bibliographic coupling based on the cited references. This led to the generation of different clusters of prevalent research areas. The centrality values described the position of each component. Discussion: 'Schizophrenia', 'depression', 'pharmacogenomics', and 'immunopathogenesis' were the research topics of overarching interest. 'Gut-brain axis' and 'gene-environment interaction' were the emerging topics, whereas certain topics such as 'child and adolescent psychiatry' remained priorities when compared to earlier studies. The keywords and research focus were diverse. They ranged from genetics to transcriptomics and epigenetics to proteomics of psychiatric disorders. We found a stagnation of science communication in the field with only 0.2% of the articles from the entire corpus relevant to it. The research categories identified in this study reflect the current publication and research trends in psychiatric genomics. [ABSTRACT FROM AUTHOR]

Scientific activity has become increasingly complex in recent years. The need for international research collaboration has thus become a common pattern in science. In this current landscape, countries face the problem of maintaining their competitiveness while cooperating with other countries to achieve relevant research outputs. In this international context, publications from international collaborations tend to achieve greater scientific impact than those from domestic ones. To design policies that improve the competitiveness of countries and organizations, it thus becomes necessary to understand the factors and mechanisms that influence the benefits and impact of international research. In this regard, the aim of this study is to confirm whether the differences in impact between international and domestic collaborations are affected by their topics and structure. To perform this study, we examined the Library and Information Science category of the Web of Science database between 2015 and 2019. A science mapping analysis approach was used to extract the themes and their structure according to collaboration type and in the whole category (2015–2019). We also looked for differences in these thematic aspects in top countries and in communities of collaborating countries. The results showed that the thematic factor influences the impact of international research, as the themes in this type of collaboration lie at the forefront of the Library and Information Science category (e.g., technologies such as artificial intelligence and social media are found in the category), while domestic collaborations have focused on more well-consolidated themes (e.g., academic libraries and bibliometrics). Organizations, countries, and communities of countries must therefore consider this thematic factor when designing strategies to improve their competitiveness and collaborate. [ABSTRACT FROM AUTHOR]

Background: Sjögren's syndrome is an autoimmune disease with a complicated pathophysiology, and treatment strategies are in desperate need of improvement. In this research, we provide the literature topic trends and knowledge structure connected to Sjögren's syndrome from the perspective of bibliometrics for further research. Methods: We acquired 3753 publications from the PubMed database and 3880 catalogs from the Web of Science Core Collection, with a time limit of 2010 to 2021 and the search term as "Sjögren's syndrome." Using the VOSviewer and bibliographic item co-occurrence matrix generator, we conducted cocited analysis, extracted major MeSH terms, generated matrices and performed biclustering analysis, visual matrix, drawn strategy diagram, and social network analysis. Results: Through the clustering of the major MeSH terms, a total of five categories and 10 research topics were identified. Cocitation analysis suggests that diagnosis and clinical manifestations have been the main basis over the past 12 years and also are the mature content in the first quadrant of the strategy map. Ultrasonography, immunosuppressive agents and therapy, mechanism and therapeutic targets, and diagnostic autoantibodies are examples of the third quadrant, which wields great potential to progress. Genetic predisposition and psychology, in the fourth quadrant, need to be developed additionally. The subject keywords near the network's edge, such as "Salivary Glands, Minor/pathology," "Immunosuppressive Agents/therapeutic use," and "Autoantibodies/blood," are all growing research hotspots with much space, according to social network analysis. Conclusion: Through bibliometric analysis of the literature related to Sjögren's syndrome in the past 12 years, we obtained the knowledge basis, undeveloped topics, and emerging hotspots, which can suggest recommendations for future research. Key Points • We disclosed the topic trends and knowledge structure of Sjögren's syndrome literature over the past 12 years. • Clinical manifestations and diagnosis of Sjögren syndrome are included in mature and comprehensive studies, whereas ultrasonography, immunosuppressants and treatments, mechanisms and therapeutic targets, and diagnostic autoantibodies are studies with high potential for advancement. Additional research in genetics and psychology is needed. • We identified potential future research hotspots, including "Salivary Glands, Minor/pathology," "Immunosuppressive Agents/therapeutic use," and "Autoantibodies/blood." [ABSTRACT FROM AUTHOR]

Copyright of Informacao & Sociedade: Estudos is the property of Universidade Federal de Campina Grande, Centro de Humanidades and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Ciência da Informação is the property of Instituto Brasileiro de Informacao em Ciencia e Tecnologia (IBICT) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Today, organizations are facing technological, economic and social challenges that require the intelligent use of data, information and knowledge. To this end, organizations are developing capabilities around intelligence. From the organizational point of view, intelligence in business is a relatively new field study, so it is convenient to know and understand what the main themes are and their evolution in order to facilitate their integration. Taking this into account, the current research conducts a conceptual and structural analysis of the Journal of Intelligence Studies in Business (JISIB). JISIB is one of the few academic journals devoted purely to publishing articles about business intelligence, collective intelligence, competitive intelligence, economic intelligence, market intelligence, marketing intelligence, scientific and technical intelligence, strategic intelligence, and their equivalent terms in other languages. This analysis is carried out by quantifying the main bibliometric performance indicators, identifying the main authors and evaluating the development of the main themes within it using SciMAT as a bibliometric analysis software. To this purpose, the documents published in JISIB from 2011 to 2017 were retrieved from two different sources: the JISIB official web page and the Web of Science. In this way, the bibliometric performance analysis evaluates the impact of the scientific output based on publications and their citations, while science mapping illustrates the intellectual structure of the journal and the evolution of the main research themes. Bearing in mind that JISIB provides an open platform for the publication of original research articles, opinion articles, book reviews and conference proceedings about the intelligence field, this research allows to understand its structure and evolution and all the themes associated with it. It provides a framework to support intelligence researchers and professionals in the development and direction of future research by identifying emerging, transversal, core and declining themes. Finally, this study includes a performance analysis of JISIB. [ABSTRACT FROM AUTHOR]

The conceptual structure of the field of Animal Science (AS) research is examined by means of a longitudinal science mapping analysis. The whole of the AS research field is analysed, revealing its conceptual evolution. To this end, an automatic approach to detecting and visualizing hidden themes or topics and their evolution across a consecutive span of years was applied to AS publications of the JCR category 'Agriculture, Dairy & Animal Science' during the period 1945-2011. This automatic approach was based on a coword analysis and combines performance analysis and science mapping. To observe the conceptual evolution of AS, six consecutive periods were defined: 1945-1969, 1970-1979, 1980-1989, 1990- 1999, 2000-2005 and 2006-2011. Research in AS was identified as having focused on ten main thematic areas: ANIMAL-FEEDING, SMALL-RUMINANTS, ANIMAL-REPRODUCTION, DAIRY-PRODUCTION, MEATQUALITY, SWINE-PRODUCTION, GENETICS-AND-ANIMAL-BREEDING, POULTRY, ANIMAL-WELFARE and GROWTH-FACTORS-AND-FATTYACIDS. The results show how genomic studies gain in weight and integrate with other thematic areas. The whole of AS research has become oriented towards an overall framework in which animal welfare, sustainable management and human health play a major role. All this would affect the future structure and management of livestock farming. [ABSTRACT FROM AUTHOR]

Background: Tyrosine kinase inhibitors (TKIs) have achieved revolutionary results in the treatment of a wide range of tumors, and many studies on this topic continue to be published every year. Some of the published reviews provide great value for us to understand TKIs. However, there is a lack of studies on the knowledge structure, bibliometric analysis, and visualization results in TKIs research., Objective: This paper aims to investigate the knowledge structure, hotspots, and trends of evolution of the TKIs research by co-word analysis and literature visualization and help researchers in this field to gain a comprehensive understanding of the current status and trends., Methods: We retrieved all academic papers about TKIs published between 2016 and 2020 from the Web of Science. By counting keywords from those papers, we generated the co-word networks by extracting the co-occurrence relationships between keywords, and then segmented communities to identify the subdirections of TKIs research by calculating the network metrics of the overall and local networks. We also mapped the association network topology, including the network within and between TKIs subdirections, to reveal the association and structure among varied subdirections. Furthermore, we detected keyword bursts by combining their burst weights and durations to reveal changes in the focus of TKIs research. Finally, evolution venation and strategic diagram were generated to reveal the trends of TKIs research., Results: We obtained 6782 unique words (total frequency 26,175) from 5584 paper titles. Finally, 296 high-frequency words were selected with a threshold of 10 after discussion, the total frequency of which accounted for 65.41% (17,120/26,175). The analysis of burst disciplines revealed a variable number of burst words of TKIs research every year, especially in 2019 and 2020, such as HER2, pyrotinib, next-generation sequencing, immunotherapy, ALK-TKI, ALK rearrangement. By network calculation, the TKIs co-word network was divided into 6 communities: C1 (non-small-cell lung cancer), C2 (targeted therapy), C3 (chronic myeloid leukemia), C4 (HER2), C5 (pharmacokinetics), and C6 (ALK). The venation diagram revealed several clear and continuous evolution trends, such as non-small-cell lung cancer venation, chronic myeloid leukemia venation, renal cell carcinoma venation, chronic lymphocytic leukemia venation. In the strategic diagram, C1 (non-small-cell lung cancer) was the core direction located in the first quadrant, C2 (targeted therapy) was exactly at the junction of the first and fourth quadrants, which meant that C2 was developing; and C3 (chronic myeloid leukemia), C4 (HER2), and C5 (pharmacokinetics) were all immature and located in the third quadrant., Conclusions: Using co-word analysis and literature visualization, we revealed the hotspots, knowledge structure, and trends of evolution of TKIs research between 2016 and 2020. TKIs research mainly focused on targeted therapies against varied tumors, particularly against non-small-cell lung cancer. The attention on chronic myeloid leukemia and pharmacokinetics was gradually decreasing, but the focus on HER2 and ALK was rapidly increasing. TKIs research had shown a clear development path: TKIs research was disease focused and revolved around "gene targets/targeted drugs/resistance mechanisms." Our outcomes will provide sound and effective support to researchers, funders, policymakers, and clinicians., (©Jiming Hu, Kai Xing, Yan Zhang, Miao Liu, Zhiwei Wang. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 08.04.2022.)

The aim of the present work is to define a theoretical framework which facilitates the analysis of the structure of a network at an individual level. To this end, we propose the integration of co-word analysis together with the analysis of social networks. As a result of this study, a series of diagrams called “structural diagrams” has been obtained. Thanks to these diagrams a pattern can be assigned to each node of the network, and a network can be classified into a set of typologies. The information provided by this theoretical framework will allow a deeper understanding of the dynamics of systems, modeled in the form of networks. In this context, structural diagrams technique improves strategies of the visual exploration of the networks as well as to orientate the definition of those procedures which enable the transformation of one typology of network into another. As a specific example of a real application of this theoretical framework, the social network of the Journal of Software Engineering and Databases (JISBD) scientific community has been analyzed, based on its co-authorship networks.

Background: With the rapid development of information and communication technologies, smart homes are being investigated as effective solutions for home health care. The increasing academic attention on smart home health care has primarily been on the development and application of smart home technologies. However, comprehensive studies examining the general landscape of diverse research areas for smart home health care are still lacking.Objective: This study aims to determine the intellectual structure of smart home health care in a time series by conducting a coword analysis and topic analysis. Specifically, it investigates (1) the intellectual basis of smart home health care through overall academic status, (2) the intellectual foci through influential keywords and their evolutions, and (3) intellectual trends through primary topics and their evolutions.Methods: Analyses were conducted in 5 steps: (1) data retrieval from article databases (Web of Science, Scopus, and PubMed) and the initial dataset preparation of 6080 abstracts from the year 2000 to the first half of 2019; (2) data preprocessing and refinement extraction of 25,563 words; (3) a descriptive analysis of the overall academic status and period division (ie, 4 stages of 3-year blocks); (4) coword analysis based on word co-occurrence networks for the intellectual foci; and (5) topic analysis for the intellectual trends based on latent Dirichlet allocation (LDA) topic modeling, word-topic networks, and researcher workshops.Results: First, regarding the intellectual basis of smart home health care, recent academic interest and predominant journals and research domains were verified. Second, to determine the intellectual foci, primary keywords were identified and classified according to the degree of their centrality values. Third, 5 themes pertaining to the topic evolution emerged: (1) the diversification of smart home health care research topics; (2) the shift from technology-oriented research to technological convergence research; (3) the expansion of application areas and system functionality of smart home health care; (4) the increased focus on system usability, such as service design and experiences; and (5) the recent adaptation of the latest technologies in health care. Based on these findings, the pattern of technology diffusion in smart home health care research was determined as the adaptation of technologies, the proliferation of application areas, and an extension into system design and service experiences.Conclusions: The research findings provide academic and practical value in 3 aspects. First, they promote a comprehensive understanding of the smart home health care domain by identifying its multifaceted intellectual structure in a time series. Second, they can help clinicians discern the development and dispersion level of their respective disciplines. Third, the pattern of technology diffusion in smart home health care could help scholars comprehend current and future research trends and identify research opportunities based on upcoming research waves of newly adapted technologies in smart home health care. [ABSTRACT FROM AUTHOR]

Background: Precision medicine (PM) is playing a more and more important role in clinical practice. In recent years, the scale of PM research has been growing rapidly. Many reviews have been published to facilitate a better understanding of the status of PM research. However, there is still a lack of research on the intellectual structure in terms of topics., Objective: This study aimed to identify the intellectual structure and evolutionary trends of PM research through the application of various social network analysis and visualization methods., Methods: The bibliographies of papers published between 2009 and 2018 were extracted from the Web of Science database. Based on the statistics of keywords in the papers, a coword network was generated and used to calculate network indicators of both the entire network and local networks. Communities were then detected to identify subdirections of PM research. Topological maps of networks, including networks between communities and within each community, were drawn to reveal the correlation structure. An evolutionary graph and a strategic graph were finally produced to reveal research venation and trends in discipline communities., Results: The results showed that PM research involves extensive themes and, overall, is not balanced. A minority of themes with a high frequency and network indicators, such as Biomarkers, Genomics, Cancer, Therapy, Genetics, Drug, Target Therapy, Pharmacogenomics, Pharmacogenetics, and Molecular, can be considered the core areas of PM research. However, there were five balanced theme directions with distinguished status and tendencies: Cancer, Biomarkers, Genomics, Drug, and Therapy. These were shown to be the main branches that were both focused and well developed. Therapy, though, was shown to be isolated and undeveloped., Conclusions: The hotspots, structures, evolutions, and development trends of PM research in the past ten years were revealed using social network analysis and visualization. In general, PM research is unbalanced, but its subdirections are balanced. The clear evolutionary and developmental trend indicates that PM research has matured in recent years. The implications of this study involving PM research will provide reasonable and effective support for researchers, funders, policymakers, and clinicians., (©Xiaoguang Lyu, Jiming Hu, Weiguo Dong, Xin Xu. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 04.02.2020.)