Journal of Data and Information Science
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170
(FIVE YEARS 100)

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9
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Published By Walter De Gruyter Gmbh

2543-683x

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Lizhi Xing ◽  
Yu Han

Abstract Purpose With the availability and utilization of Inter-Country Input-Output (ICIO) tables, it is possible to construct quantitative indices to assess its impact on the Global Value Chain (GVC). For the sake of visualization, ICIO networks with tremendous low- weight edges are too dense to show the substantial structure. These redundant edges, inevitably make the network data full of noise and eventually exert negative effects on Social Network Analysis (SNA). In this case, we need a method to filter such edges and obtain a sparser network with only the meaningful connections. Design/methodology/approach In this paper, we propose two parameterless pruning algorithms from the global and local perspectives respectively, then the performance of them is examined using the ICIO table from different databases. Findings The Searching Paths (SP) method extracts the strongest association paths from the global perspective, while Filtering Edges (FE) method captures the key links according to the local weight ratio. The results show that the FE method can basically include the SP method and become the best solution for the ICIO networks. Research limitations There are still two limitations in this research. One is that the computational complexity may increase rapidly while processing the large-scale networks, so the proposed method should be further improved. The other is that much more empirical networks should be introduced to testify the scientificity and practicability of our methodology. Practical implications The network pruning methods we proposed will promote the analysis of the ICIO network, in terms of community detection, link prediction, and spatial econometrics, etc. Also, they can be applied to many other complex networks with similar characteristics. Originality/value This paper improves the existing research from two aspects, namely, considering the heterogeneity of weights and avoiding the interference of parameters. Therefore, it provides a new idea for the research of network backbone extraction.


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Murtuza Shahzad ◽  
Hamed Alhoori

Abstract Purpose Social media users share their ideas, thoughts, and emotions with other users. However, it is not clear how online users would respond to new research outcomes. This study aims to predict the nature of the emotions expressed by Twitter users toward scientific publications. Additionally, we investigate what features of the research articles help in such prediction. Identifying the sentiments of research articles on social media will help scientists gauge a new societal impact of their research articles. Design/methodology/approach Several tools are used for sentiment analysis, so we applied five sentiment analysis tools to check which are suitable for capturing a tweet's sentiment value and decided to use NLTK VADER and TextBlob. We segregated the sentiment value into negative, positive, and neutral. We measure the mean and median of tweets’ sentiment value for research articles with more than one tweet. We next built machine learning models to predict the sentiments of tweets related to scientific publications and investigated the essential features that controlled the prediction models. Findings We found that the most important feature in all the models was the sentiment of the research article title followed by the author count. We observed that the tree-based models performed better than other classification models, with Random Forest achieving 89% accuracy for binary classification and 73% accuracy for three-label classification. Research limitations In this research, we used state-of-the-art sentiment analysis libraries. However, these libraries might vary at times in their sentiment prediction behavior. Tweet sentiment may be influenced by a multitude of circumstances and is not always immediately tied to the paper's details. In the future, we intend to broaden the scope of our research by employing word2vec models. Practical implications Many studies have focused on understanding the impact of science on scientists or how science communicators can improve their outcomes. Research in this area has relied on fewer and more limited measures, such as citations and user studies with small datasets. There is currently a critical need to find novel methods to quantify and evaluate the broader impact of research. This study will help scientists better comprehend the emotional impact of their work. Additionally, the value of understanding the public's interest and reactions helps science communicators identify effective ways to engage with the public and build positive connections between scientific communities and the public. Originality/value This study will extend work on public engagement with science, sociology of science, and computational social science. It will enable researchers to identify areas in which there is a gap between public and expert understanding and provide strategies by which this gap can be bridged.


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Minh-Hoang Nguyen ◽  
Huyen Thanh Thanh Nguyen ◽  
Manh-Toan Ho ◽  
Tam-Tri Le ◽  
Quan-Hoang Vuong

Abstract Purpose The open-access (OA) publishing model can help improve researchers’ outreach, thanks to its accessibility and visibility to the public. Therefore, the presentation of female researchers can benefit from the OA publishing model. Despite that, little is known about how gender affects OA practices. Thus, the current study explores the effects of female involvement and risk aversion on OA publishing patterns among Vietnamese social sciences and humanities. Design/methodology/approach The study employed Bayesian Mindsponge Framework (BMF) on a dataset of 3,122 Vietnamese social sciences and humanities (SS&H) publications during 2008–2019. The Mindsponge mechanism was specifically used to construct theoretical models, while Bayesian inference was utilized for fitting models. Findings The result showed a positive association between female participation and OA publishing probability. However, the positive effect of female involvement on OA publishing probability was negated by the high ratio of female researchers in a publication. OA status was negatively associated with the JIF of the journal in which the publication was published, but the relationship was moderated by the involvement of a female researcher(s). The findings suggested that Vietnamese female researchers might be more likely to publish under the OA model in journals with high JIF for avoiding the risk of public criticism. Research limitations The study could only provide evidence on the association between female involvement and OA publishing probability. However, whether to publish under OA terms is often determined by the first or corresponding authors, but not necessarily gender-based. Practical implications Systematically coordinated actions are suggested to better support women and promote the OA movement in Vietnam. Originality/value The findings show the OA publishing patterns of female researchers in Vietnamese SS&H.


2021 ◽  
Vol 6 (4) ◽  
pp. 111-138
Author(s):  
Jun Guan ◽  
Jingying Xu ◽  
Yu Han ◽  
Dawei Wang ◽  
Lizhi Xing

Abstract Purpose This study aims to provide a new framework for analyzing the path of technology diffusion in the innovation network at the regional level and industrial level respectively, which is conducive to the integration of innovation resources, the coordinated development of innovative subjects, and the improvement of innovation abilities. Design/methodology/approach Based on the Z-Park patent cooperation data, we establish Inter-Enterprise Technology Transfer Network model and apply the concept of Pivotability to describe the key links of technology diffusion and quantify the importance of innovative partnerships. By measuring the topologically structural characteristics in the levels of branch park and the technosphere, this paper demonstrates how technology spreads and promotes overall innovation activities within the innovation network. Findings The results indicate that: (1) Patent cooperation network of the Z-Park displays heterogeneity and the connections between the innovative subjects distribute extremely uneven. (2) Haidian park owns the highest pivotability in the IETTN model, yet the related inter-enterprise patent cooperation is mainly concentrated in its internal, failing to facilitate the technology diffusion across multiple branch parks. (3) Such fields as “electronics and information” and “advanced manufacturing” are prominent in the cross-technosphere cooperation, while fields such as “new energy” and “environmental protection technology” can better promote industrial integration. Research limitations Only the part of the joint patent application is taken into account while establishing the patent cooperation network. The other factors that influence the mechanism of technology diffusion in the innovation network need to be further studied, such as financial capital, market competition, and personnel mobility, etc. Practical implications The findings of this paper will provide useful information and suggestions for the administration and policy-making of high-tech parks. Originality/value The value of this paper is to build a bridge between the massive amount of patent data and the nature of technology diffusion, and to develop a set of tools to analyze the nonlinear relations between innovative subjects.


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Howell Y. Wang ◽  
Shelia X. Wei ◽  
Cong Cao ◽  
Xianwen Wang ◽  
Fred Y. Ye

Abstract Purpose We attempt to find out whether OA or TA really affects the dissemination of scientific discoveries. Design/methodology/approach We design the indicators, hot-degree, and R-index to indicate a topic OA or TA advantages. First, according to the OA classification of the Web of Science (WoS), we collect data from the WoS by downloading OA and TA articles, letters, and reviews published in Nature and Science during 2010–2019. These papers are divided into three broad disciplines, namely biomedicine, physics, and others. Then, taking a discipline in a journal and using the classical Latent Dirichlet Allocation (LDA) to cluster 100 topics of OA and TA papers respectively, we apply the Pearson correlation coefficient to match the topics of OA and TA, and calculate the hot-degree and R-index of every OA-TA topic pair. Finally, characteristics of the discipline can be presented. In qualitative comparison, we choose some high-quality papers which belong to Nature remarkable papers or Science breakthroughs, and analyze the relations between OA/TA and citation numbers. Findings The result shows that OA hot-degree in biomedicine is significantly greater than that of TA, but significantly less than that of TA in physics. Based on the R-index, it is found that OA advantages exist in biomedicine and TA advantages do in physics. Therefore, the dissemination of average scientific discoveries in all fields is not necessarily affected by OA or TA. However, OA promotes the spread of important scientific discoveries in high-quality papers. Research limitations We lost some citations by ignoring other open sources such as arXiv and bioArxiv. Another limitation came from that Nature employs some strong measures for access-promoting subscription-based articles, on which the boundary between OA and TA became fuzzy. Practical implications It is useful to select hot topics in a set of publications by the hot-degree index. The finding comprehensively reflects the differences of OA and TA in different disciplines, which is a useful reference when researchers choose the publishing way as OA or TA. Originality/value We propose a new method, including two indicators, to explore and measure OA or TA advantages.


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Kun Chen ◽  
Xian-tong Ren ◽  
Guo-liang Yang ◽  
Ailifeire Abudouguli

Abstract Purpose This paper studies the relationship between the impact factor (IF) and the number of journal papers in Chinese publishing system. Design/methodology/approach The method proposed by Huang (2016) is used whereas to analysis the data of Chinese journals in this study. Findings Based on the analysis, we find the following. (1) The average impact factor (AIF) of journals in all disciplines maintained a growth trend from 2007 to 2017. Whether before or after removing outlier journals that may garner publication fees, the IF and its growth rate for most social sciences disciplines are larger than those of most natural sciences disciplines, and the number of journal papers on social sciences disciplines decreased while that of natural sciences disciplines increased from 2007 to 2017. (2) The removal of outlier journals has a greater impact on the relationship between the IF and the number of journal papers in some disciplines such as Geosciences because there may be journals that publish many papers to garner publication fees. (3) The success-breeds-success (SBS) principle is applicable in Chinese journals on natural sciences disciplines but not in Chinese journals on social sciences disciplines, and the relationship is the reverse of the SBS principle in Economics and Education & Educational Research. (4) Based on interviews and surveys, the difference in the relationship between the IF and the number of journal papers for Chinese natural sciences disciplines and Chinese social sciences disciplines may be due to the influence of the international publishing system. Chinese natural sciences journals are losing their academic power while Chinese social sciences journals that are less influenced by the international publishing system are in fierce competition. Research limitation More implications could be found if long-term tracking and comparing the international publishing system with Chinese publishing system are taken. Practical implications It is suggested that researchers from different countries study natural science and social sciences journals in their languages and observe the influence of the international publishing system. Originality/value This paper presents an overview of the relationship between IF and the number of journal papers in Chinese publishing system from 2007 to 2017, provides insights into the relationship in different disciplines in Chinese publishing system, and points out the similarities and differences between Chinese publishing system and international publishing system.


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Zheng Xie

Abstract Purpose We proposed a method to represent scientific papers by a complex network, which combines the approaches of neural and complex networks. Design/methodology/approach Its novelty is representing a paper by a word branch, which carries the sequential structure of words in sentences. The branches are generated by the attention mechanism in deep learning models. We connected those branches at the positions of their common words to generate networks, called word-attention networks, and then detect their communities, defined as topics. Findings Those detected topics can carry the sequential structure of words in sentences, represent the intra- and inter-sentential dependencies among words, and reveal the roles of words playing in them by network indexes. Research limitations The parameter setting of our method may depend on practical data. Thus it needs human experience to find proper settings. Practical implications Our method is applied to the papers of the PNAS, where the discipline designations provided by authors are used as the golden labels of papers’ topics. Originality/value This empirical study shows that the proposed method outperforms the Latent Dirichlet Allocation and is more stable.


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Chengzhi Zhang ◽  
Philipp Mayr ◽  
Wei Lu ◽  
Yi Zhang

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Mike Thelwall ◽  
Saheeda Thelwall

Abstract Purpose Methods to tackle Covid-19 have been developed by a wave of biomedical research but the pandemic has also influenced many aspects of society, generating a need for research into its consequences, and potentially changing the way existing topics are investigated. This article investigates the nature of this influence on the wider academic research mission. Design/methodology/approach This article reports an inductive content analysis of 500 randomly selected journal articles mentioning Covid-19, as recorded by the Dimensions scholarly database on 19 March 2021. Covid-19 mentions were coded for the influence of the disease on the research. Findings Whilst two thirds of these articles were about biomedicine (e.g. treatments, vaccines, virology), or health services in response to Covid-19, others covered the pandemic economy, society, safety, or education. In addition, some articles were not about the pandemic but stated that Covid-19 had increased or decreased the value of the reported research or changed the context in which it was conducted. Research limitations The findings relate only to Covid-19 influences declared in published journal articles. Practical implications Research managers and funders should consider whether their current procedures are effective in supporting researchers to address the evolving demands of pandemic societies, particularly in terms of timeliness. Originality/value The results show that although health research dominates the academic response to Covid-19, it is more widely disrupting academic research with new demands and challenges.


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Masashi Shirabe ◽  
Amane Koizumi

Abstract Purpose The adequacy of research performance of universities or research institutes have often been evaluated and understood in two axes: “quantity” (i.e. size or volume) and “quality” (i.e. what we define here as a measure of excellence that is considered theoretically independent of size or volume, such as clarity in diamond grading). The purpose of this article is, however, to introduce a third construct named “substantiality” (“ATSUMI” in Japanese) of research performance and to demonstrate its importance in evaluating/understanding research universities. Design/methodology/approach We take a two-step approach to demonstrate the effectiveness of the proposed construct by showing that (1) some characteristics of research universities are not well captured by the conventional constructs (“quantity” and “quality”)-based indicators, and (2) the “substantiality” indicators can capture them. Furthermore, by suggesting that “substantiality” indicators appear linked to the reputation that appeared in university reputation rankings by simple statistical analysis, we reveal additional benefits of the construct. Findings We propose a new construct named “substantiality” for measuring research performance. We show that indicators based on “substantiality” can capture important characteristics of research institutes. “Substantiality” indicators demonstrate their “predictive powers” on research reputation. Research limitations The concept of “substantiality” originated from IGO game; therefore the ease/difficulty of accepting the concept is culturally dependent. In other words, while it is easily accepted by people from Japan and other East Asian countries and regions, it might be difficult for researchers from other cultural regions to accept it. Practical implications There is no simple solution to the challenge of evaluating research universities’ research performance. It is vital to combine different types of indicators to understand the excellence of research institutes. Substantiality indicators could be part of such a combination of indicators. Originality/value The authors propose a new construct named substantiality for measuring research performance. They show that indicators based on this construct can capture the important characteristics of research institutes.


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