Patent citation network analysis: A perspective from descriptive statistics and ERGMs

Top 100 cited articles in the thromboangiitis obliterans: a bibliometric analysis and visualized study

OBJECTIVE

Thromboangiitis obliterans (TAO) is one of the most common types of peripheral arterial disease (PAD). This study aimed to explore the characteristics of the top 100 most cited articles in the TAO.

METHODS

A bibliometric analysis based on the Web of Science (WOS) database was performed. Literature was retrieved and ranked by the citations. Listed below are the top 100 citations, including original articles, reviews, full-length proceeding papers, and case reports that were included for analysis. The type of literature, research areas, and languages were recorded. The trends of citations including the total citations, an analysis of publication and citation numbers were conducted each year. We analyzed citations from highly cited countries, authors, institutions, and journals. Research hotspots were gathered by a visualized analysis of author keywords.

RESULTS

Most of the highly cited literature was original articles. A rising trend was observed in the number of citations per year. The peaks in the number of highly cited articles appeared in the year 1998 and 2006. The majority of the articles focused on the cardiovascular system and surgery. Journal of Vascular Surgery published most of the highly cited articles. The USA and Japan contributed nearly half the number of highly cited articles. Mayo Clinic and Nagoya University were highly cited institutions. Shionoya S and Olin JW were both the author with the largest number of citations and the most highly cited author in the reference. Articles that were highly cited most often addressed the following topics: "vasculitis", "autoimmune disease", and "critical limb ischemia". Keywords that were mostly used in recent years were "stem cell therapy", "progenitor therapy", and "immunoadsorption". The detection of bursts of author keywords showed the following: "permeability", "differentiation", and "critical limb ischemia" are recent keywords that have burst.

CONCLUSIONS

In this study, the highly cited contributors in the field of TAO research were identified. Most cited articles in the top 100 focused on the cardiovascular system and surgery. Treatment and pathophysiology including stem cell therapy, progenitor therapy, genetics, autoimmunity, and inflammation are the hotspots of TAO.

Analysis of international competitive situation of key core technology in strategic emerging industries: New generation of information technology industry as an example

In the context of the current technological revolution and unprecedented major changes, countries are facing the situation of accelerating the development of key core technologies, which is caused by the transformation from the dispute over trade to the dispute over ecology and scientific and technological strength. Competitive situation analysis is an important link of key core technology innovation. The construction of a universal model of international competitive situation analysis of key core technology can provide scientific support for decision makers of science and technology innovation to solve technical difficulties. This study takes the new generation of information technology industry as an example, identifies key core technologies of the industry and evaluates the competitive situation of the major world countries. Studies indicate that in the field of new generation information technology, the US and Japan is in the leading position globally. In addition, China has active innovation activities in all fields, but overall there remains a considerable gap with the world-leading level, and its R&D quality needs to be further improved.

Identification of technology frontiers of artificial intelligence-assisted pathology based on patent citation network

Objectives

This paper aimed to identify the technology frontiers of artificial intelligence-assisted pathology based on patent citation network.

Methods

Patents related to artificial intelligence-assisted pathology were searched and collected from the Derwent Innovation Index (DII), which were imported into Derwent Data Analyzer (DDA, Clarivate Derwent, New York, NY, USA) for authority control, and imported into the freely available computer program Ucinet 6 for drawing the patent citation network. The patent citation network according to the citation relationship could describe the technology development context in the field of artificial intelligence-assisted pathology. The patent citations were extracted from the collected patent data, selected highly cited patents to form a co-occurrence matrix, and built a patent citation network based on the co-occurrence matrix in each period. Text clustering is an unsupervised learning method, an important method in text mining, where similar documents are grouped into clusters. The similarity between documents are determined by calculating the distance between them, and the two documents with the closest distance are combined. The method of text clustering was used to identify the technology frontiers based on the patent citation network, which was according to co-word analysis of the title and abstract of the patents in this field.

Results

1704 patents were obtained in the field of artificial intelligence-assisted pathology, which had been currently undergoing three stages, namely the budding period (1992–2000), the development period (2001–2015), and the rapid growth period (2016–2021). There were two technology frontiers in the budding period (1992–2000), namely systems and methods for image data processing in computerized tomography (CT), and immunohistochemistry (IHC), five technology frontiers in the development period (2001–2015), namely spectral analysis methods of biomacromolecules, pathological information system, diagnostic biomarkers, molecular pathology diagnosis, and pathological diagnosis antibody, and six technology frontiers in the rapid growth period (2016–2021), namely digital pathology (DP), deep learning (DL) algorithms—convolutional neural networks (CNN), disease prediction models, computational pathology, pathological image analysis method, and intelligent pathological system.

Conclusions

Artificial intelligence-assisted pathology was currently in a rapid development period, and computational pathology, DL and other technologies in this period all involved the study of algorithms. Future research hotspots in this field would focus on algorithm improvement and intelligent diagnosis in order to realize the precise diagnosis. The results of this study presented an overview of the characteristics of research status and development trends in the field of artificial intelligence-assisted pathology, which could help readers broaden innovative ideas and discover new technological opportunities, and also served as important indicators for government policymaking.

Research on Evolution Characteristics and Factors of Nordic Green Patent Citation Network

Dealing with the environmental and climate risks caused by global warming has become a global consensus. As a sensitive area with particularly fragile ecological environment, the Nordic countries took the lead in making the commitment of “carbon neutrality” by the middle of this century. The green industry will play an important role during this process. Based on the patent data related to the green industry in Nordic countries, this paper studies the evolution characteristics and dynamic changes of influencing factors of patent citation network from 1980 to 2019 by using the social network analysis method and exponential random graph model. The research results show that: Nordic green technologies have gradually changed from passive development to active innovation from the source, and gradually diversified and subdivided in the development process; the connectivity and transitivity of the patent citation network are good and relatively stable in the evolution process; the connections of Nordic countries with non-Nordic countries are strong and gradually spread to distant regions; the awareness of patent property rights protection has gradually increased, and industry and academia are increasingly integrated, which all promote the formation of patent citation relationship.

Patent Analysis Using Bayesian Data Analysis and Network Modeling

Patent analysis is to analyze patent data to understand target technology. Patent data contains various detailed information about the developed technology. Therefore, many studies concerning patent analysis have been carried out in the technology analysis fields. Most traditional methods for technology analysis were based on qualitative approaches such as Delphi survey. However, the patent analysis methods based on statistics and machine learning have been introduced recently. In this paper, we proposed a statistical method for quantitative patent analysis. Moreover, we selected drone technology as the target technology for patent analysis. To understand drone technology, we analyzed the patents on drone technology. We searched the patent documents related to drone technology and transformed them to structured data using text mining techniques. First, we visualized the patent keywords to identify the technological structure of a drone. Next, using Bayesian additive regression trees, we analyzed the structured patent data to construct technology scenarios for drones. To illustrate the performance and validity of our proposed research, we presented the experimental results of patent analysis using patent documents related to drone technology.

A Scientometric Assessment of Agri-Food Technology for Research Activity and Productivity

In accordance with the UN Sustainable Development Goals (SDGs), several SDGs target global food issues, including zero hunger (food security and sustainable agriculture), responsible consumption and production (food losses), climate action (greenhouse gas emissions from food waste), and partnerships for the goals (research collaboration). As such, it is vital to identify technology and market opportunities to support advanced development by exploring scientific and technological research on such SDGs. The significance of technological innovation and evaluations of activity, productivity, and collaboration aids and guides future research streams. Motivated by the growing severity of the global food waste crisis, this paper focuses on the case study of shelf-life extension technology for food and applies a scientometric analysis of patents based on text mining. VantagePoint was used to analyze 2516 patents issued between 2000 and 2020, with the aim of understanding the conceptual structure of knowledge and the social relationships among key players. The results indicate that the technology is experiencing a period of growth, and it can be clustered into five technology sectors. Across all technology clusters, China outperformed other countries in terms of the number of patents. Almost all of China’s patents applied for technology commercialization domestically, whereas other countries tended to apply for patents overseas to exploit opportunities. The findings have implications for both policymaking and strategic decision-making using a multi-layered network innovation system.

Exploring the topology and dynamic growth properties of co-invention networks and technology fields

This study investigates the topology and dynamics of collaboration networks that exist between inventors and their patent co-authors for patents granted by the USPTO from 2007-2019 (2,241,201 patents and 1,879,037 inventors). We study changes in the configurations of different technology fields via the power-law, small-world, preferential attachment, shrinking diameter, densification law, and gelling point hypotheses. Similar to the existing literature, we obtain mixed results. Based on network statistics, we argue that the sudden rise of large networks in six technology sectors can be understood as a phase transition in which small, isolated networks form one giant component. In two other technology sectors, such a transition occurred much later and much less dramatically. The examination of inventor networks over time reveals the increased complexity of all technology sectors, regardless of the individual characteristics of the network. Therefore, we introduce ideas associated with the technological diversification of inventors to complement our analysis, and we find evidence that inventors tend to diversify into new fields that are less mature. This behavior appears to be correlated with the compliance of some of the expected network rules and has implications for the emerging patterns among the different collaboration networks under consideration here.