Subjects: Library Science,Information Science >> Information Processing submitted time 2023-04-14
Abstract: Purpose/Significance Comprehending the development process of scientific knowledge contributes to the scientific research.. For knowledge evaluation and service, it is crucial to trace the structure and progress of knowledge in subdivided fields from a micro perspective. Method/Process This article took the knowledge unit in medical informatics as an example. This paper used the semantic type of triples to define the treatment-related subdivision fields, constructed the knowledge unit citation networks of 125 diseases at different intervals, and identified the knowledge communities with the Leiden algorithm. From the dimensions of knowledge evolution and knowledge competition state, we aim to reveal the evolutionary characteristics of disease individuals. The indexes of Richness, Balance, and Difference are calculated to reveal the diversity characteristics of disease individuals as well as the overall disease population. Result/conclusion The research demonstrates that the knowledge communities can reflect the knowledge structure and evolution state of disease individuals. The overall diversity characteristics of diseases include: the commonality of indicators indicates that the number of all disease knowledge communities is increasing, and the differences in scale and composition between communities are expanding. Different diseases show conventional, early-controversial, and generalized evolutionary patterns, with the earlier diseases being less balanced and more different.
Subjects: Library Science,Information Science >> Library Science submitted time 2023-07-26 Cooperative journals: 《图书情报工作》
Abstract: [Purpose/significance] The extensive development of scientific research cooperation will inevitably lead to the imbalance of regional scientific research output. In order to explore its distribution, the paper analyzed the causes of differences, and studied the spatial distribution of regional scientific research output.[Method/process] Based on the bibliographic data of the computer field from 1997-2016, the geographical location information of the organization is extracted, and the observation point was used to visualize the distribution, and the Gini index and the centrality index are measured to study the distribution concentration. By measuring the global Moran index and local autocorrelation index, the spatial autocorrelation law was studied. By measuring the Pearson correlation coefficient, the correlation between the number of colleges and universities, the gross national product, the research and experimental input, and the population was studied.[Result/conclusion] The output of journals in the computer field showed an uneven geographical distribution, a clear concentration, and spatial autocorrelation. Meanwhile, it had a high correlation with the number of regional universities and regional research and experimental funding.
Subjects: Library Science,Information Science >> Library Science submitted time 2023-07-26 Cooperative journals: 《图书情报工作》
Abstract: [Purpose/significance] The article aims to explore the factors and their mechanisms influencing the generation of co-word network for interdisciplinary field, and to reveal micro-level mechanisms of knowledge connection in interdisciplinary field.[Method/process] Borrowing network embedding theory, the article summarizes the factors into network structure factors (endogenous variables) and keywords' attribute factors (exogenous variables). Exponential random graph model is constructed based on these factors to perform an empirical analysis on the field of Medical Informatics.[Result/conclusion] The results show that the influence of network structure factors on the co-occurrence relationship generation is greater than that of keywords' attributes. Preferential attachment and transitive mechanism have significant positive effect. Keywords tend to be connected with the newer ones. In addition, the keywords of Medical Informatics tend to establish co-occurrence relations with the keywords from basic disciplines, while the keywords from basic disciplines tend to be connected with the keywords in their own disciplines. The conclusions are helpful to understand the formation process of knowledge systems in interdisciplinary fields and the interactions of interdisciplinary knowledge.
Subjects: Library Science,Information Science >> Information Science submitted time 2023-04-01 Cooperative journals: 《图书情报工作》
Abstract: [Purpose/significance] Scientific research communities are important knowledge groups in contemporary science. Studying the evolutionary characteristics of scientific research communities is of great significance for exploring the law of field development and promoting knowledge innovation.[Method/process] This article took the field of Library and Information Science (LIS) as an example. From the perspective of evolutionary event detection, this paper used the Leiden algorithm to detect scientific research communities, and constructed their evolution paths and evolution trees. On this basis, this paper identified the evolution events of scientific research communities, and revealed the evolution modes and evolution characteristics of scientific research communities from three aspects:the overall analysis of the evolution, the evolution paths and the characteristics of the evolution trees, and the statistical characteristics of group evolution events.[Result/conclusion] The research shows that the scale of scientific research communities is developing vigorously, and the evolution trees of scientific research communities present two evolution modes. Most of the evolutionary events of growth type occurred in large communities with a relatively high volume of posts, while both ‘form’ and ‘dissovle’ evolution events occurred in small communities with a relatively high volume of posts. The average community size of evolutionary events such as ‘merge’, ‘partial merge’, ‘split’, and ‘shrink’ is small, and the volume of publications is low. These characteristics further prove that the cooperation and exchanges between scientific research communities tend to be frequent, and the evolution of scientific research communities has become increasingly complex.
Subjects: Library Science,Information Science >> Library Science submitted time 2023-08-26 Cooperative journals: 《图书情报工作》
Abstract: [Purpose/significance] This paper explores the community structure and community membership of the research interest similarity network of core authors in information science.[Method/process] We firstly download all papers of information science retrieved in CSSCI database using the China Library Category number. By recognizing the core-authors in this discipline with Price law, we compute the similarity between each two authors with bag-of-words model and construct the research interest similarity network of core authors. Then we divide it into four research community. Finally, we compute the every author's membership degree to different communities and his/her fuzzy entropy.[Result/conclusion] We discover that the domestic information science discipline has four research field:information organization and retrieval, bibliometrics and scientific evaluation, competitive intelligence and knowledge management, and the information science. Most authors' research isn't limited to one field. Finally, the authors in C2 and C3 merely take each other as secondary membership community, and it implies that the boundary between competitive intelligence and bibliometrics is very obvious.
Subjects: Library Science,Information Science >> Information Science submitted time 2023-04-01 Cooperative journals: 《图书情报工作》
Abstract: [Purpose/significance] The behavior of academic literature downloading is an essential step in the process of academic retrieval. Predicting download behavior of academic literature is conducive to the in-depth understanding of the retrieval behavior of researchers, and provides a basis for optimizing retrieval results of academic resource retrieval platforms and restructuring ranking, to improve the retrieval function and service quality of retrieval system.[Method/process] This paper constructed a multi-dimensional feature system of researchers' academic literature download behavior, and proposed two sub-classifiers based on query relevance and user behavior respectively relying on machine learning algorithms. A weighted strategy was adopted to construct a hybrid model of download behavior prediction of academic literature.[Result/conclusion] The experiment results show that the Random Forest algorithm achieves the best performance in both classifiers. Compared to the model trained with only query relevance features, the accuracy of the hybrid model is increased by 2.3%, and the F1 value is increased by 1.3%. The sub-classifiers based on user behavior have higher weights in the hybrid model. "downloads" "whether professional/advanced search is used"and "published time" make a significant contribution to the academic literature download prediction task.