Is entrepreneurship an emerging area of research? A computational response

Objective: We aim to answer four questions. First, with the increasing number of publications, is there a concentration in specific subjects, or on the contrary, a dispersion, amplifying the span of themes related to entrepreneurship? Second, is there a hierarchy of subjects, in the sense that some of them constitute the “core” of entrepreneurship? Third, are they connected with other established research areas? Finally, it is possible to identify papers that are influential, acting as hubs in the cluster’s formation? Method: We developed an original version of the computational procedure proposed by Shibata et al (2008), which allows us to understand the diversity of the different sub-areas of the topic investigated, reducing the need for specialist supervision. Originality / Relevance: We developed and applied a method to capture the formation and evolution of research areas in entrepreneurship literature, via direct citation networks, allowing us to understand the iteration between the different research sub-areas. Results: The dispersion is a feature of entrepreneurship as field research, with a hierarchy between research areas, indicating an emergent organization in the expansion processes. We concluded that research on entrepreneurship consists of specialization, that is, by application in niches.

Citation Network Study on the Use of New Technologies in Neurorehabilitation

New technologies in neurorehabilitation is a wide concept that intends to find solutions for individual and collective needs through technical systems. Analysis through citation networks is used to search scientific literature related to a specific topic. On the one hand, the main countries, institutions, and authors researching this topic have been identified, as well as their evolution over time. On the other hand, the links between the authors, the countries, and the topics under research have been analyzed. The publications analysis was performed through the Web of Science database using the search terms “new technolog*,” “neurorehabilitation,” “physical therapy*,” and “occupational therapy*.” The selected interval of publication was from 1992 to December 2020. The results were analyzed using CitNetExplorer software. After a Web of Science search, a total of 454 publications and 135 citation networks were found, 1992 being the first year of publication. An exponential increase was detected from the year 2009. The largest number was detected in 2020. The main areas are rehabilitation and neurosciences and neurology. The most cited article was from Perry et al. in 2007, with a citation index of 460. The analysis of the top 20 most cited articles shows that most approach the use of robotic devices and brain–computer interface systems. In conclusion, the main theme was found to be the use of robotic devices to address neuromuscular rehabilitation goals and brain–computer interfaces and their applications in neurorehabilitation.

Bibliometric Analysis of HIV and Exercise Literature Based on Scientific Studies from 1990-2020

Background: Exercise is believed to play an important role in maintaining functionality in patients with HIV and it is thought that researchers are increasingly interested in this field. We aimed to shed light on the historical development of research on HIV and exercise by utilizing visual mapping method. Methods: Overall, 1051 articles retrieved from Web of Science (WoS) core database were analyzed according to the publication year and language, number of issues, citation, country collaborations, co-citation networks and concept–topic trends by using CiteSpace software. Results: The United States played a key role in country collaborations, and had the highest citation burst. The most cited studies were meta-analysis studies. The studies gathered mainly around the clusters named “physical activity” and “metabolic abnormalities” meanwhile, the recent topics of research were heart failure, metabolism, comorbidity, Ethiopia, muscle, cardiovascular event and drug user. Conclusion: The reason why USA was found to be one of the key actors in the network is supposed to be the financial resources it can allocate for the studies conducted. It appears that the majority of the studies in the field dwell upon the impact of exercise on the physical parameters in HIV patients, whereas there are only a limited number of studies focusing on the impact of exercise on HIV-induced psychological and cognitive problems. Recent studies on neurocognitive impairment, on the other hand, are predictive of possible future popularity of such topics among researchers.

Weighted P-Rank Algorithm Based on aHeterogeneous Scholarly Network

The evaluation of scientific article has always been a very challenging task because of the dynamicchange of citation networks. Over the past decades, plenty of studies have been conducted on thistopic. However, most of the current methods do not consider the link weightings between differentnetworks, which might lead to biased article ranking results. To tackle this issue, we develop aweighted P-Rank algorithm based on a heterogeneous scholarly network for article ranking evaluation.In this study, the corresponding link weightings in heterogeneous scholarly network can be updatedby calculating citation relevance, authors’ contribution, and journals’ impact. To further boost theperformance, we also employ the time information of each article as a personalized PageRank vectorto balance the bias to earlier publications in the dynamic citation network. The experiments areconducted on three public datasets (arXiv, Cora, and MAG). The experimental results demonstratedthat weighted P-Rank algorithm significantly outperforms other ranking algorithms on arXiv andMAG datasets, while it achieves competitive performance on Cora dataset. Under different networkconfiguration conditions, it can be found that the best ranking result can be obtained by jointlyutilizing all kinds of weighted information.

AdjMix: simplifying and attending graph convolutional networks

Simple graph convolution (SGC) achieves competitive classification accuracy to graph convolutional networks (GCNs) in various tasks while being computationally more efficient and fitting fewer parameters. However, the width of SGC is narrow due to the over-smoothing of SGC with higher power, which limits the learning ability of graph representations. Here, we propose AdjMix, a simple and attentional graph convolutional model, that is scalable to wider structure and captures more nodes features information, by simultaneously mixing the adjacency matrices of different powers. We point out that the key factor of over-smoothing is the mismatched weights of adjacency matrices, and design AdjMix to address the over-smoothing of SGC and GCNs by adjusting the weights to matching values. Experiments on citation networks including Pubmed, Citeseer, and Cora show that our AdjMix improves over SGC by 2.4%, 2.2%, and 3.2%, respectively, while achieving same performance in terms of parameters and complexity, and obtains better performance in terms of classification accuracy, parameters, and complexity, compared to other baselines.

Scrutinising the Exceptionalism of Young Rural NEETs: A Bibliometric Review

The situation of rural NEETs aged 15 to 24 remains understudied. However, transitions from adolescence to emerging adulthood are very demanding for those in the countryside. Our paper discusses this gap by characterising the scholarship focusing on rural NEETs. We undertook a bibliometric review based on 325 entries on Web of Science (WoS) using the Bibliometrix analysis package. Our approach included descriptive bibliometric analysis, co-citation networks assessment, and thematic analysis. Our findings show that the investigation efforts depicting younger rural NEET are recent and marginal in the larger context of international NEETs scholarship. The field is dominated by economy- and sociology-led networks. Concerns regarding health and employment issues are central in international publishing trends, showing a dominant youth-at-risk approach to this group. Still, themes associated with adolescent NEETs and relevant programs’ assessment are gaining traction. Our findings show a need for funding research initiatives to reduce the invisibility of young rural NEETs.

Exploring Topics in Bibliometric Research Through Citation Networks and Semantic Analysis

This article surveys topic distributions of the academic literature that employs the terms bibliometrics, scientometrics, and informetrics. This exploration allows informing on the adoption of those terms and publication patterns of the authors acknowledging their work to be part of bibliometric research. We retrieved 20,268 articles related to bibliometrics and applied methodologies that exploit various features of the dataset to surface different topic representations. Across them, we observe major trends including discussions on theory, regional publication patterns, databases, and tools. There is a great increase in the application of bibliometrics as science mapping and decision-making tools in management, public health, sustainability, and medical fields. It is also observed that the term bibliometrics has reached an overall generality, while the terms scientometrics and informetrics may be more accurate in representing the core of bibliometric research as understood by the information and library science field. This article contributes by providing multiple snapshots of a field that has grown too quickly beyond the confines of library science.