Internet has become a major medium for infomation transmission, how to detect hot topic on web, track the event development and forecast emergency is important to many fields, particularly to some government departmen...Internet has become a major medium for infomation transmission, how to detect hot topic on web, track the event development and forecast emergency is important to many fields, particularly to some government departments. On the basis of the researches in the field of topic detection and tracking, we propose a model for hot topic discovery that will pick out hot topics by automatically detecting, clustering and weighting topics on the websites within a time period. Based on the idea of stock index, we also introduce a topic index approach in following the growth of topics, which is useful to analyze and forecast the development of topics on web.展开更多
Purpose： In this paper, we combined the method of co-word analysis and alluvial diagram to detect hot topics and illustrate their dynamics. Design/methodology/approach： Articles in the field of scientometrics were c...Purpose： In this paper, we combined the method of co-word analysis and alluvial diagram to detect hot topics and illustrate their dynamics. Design/methodology/approach： Articles in the field of scientometrics were chosen as research cases in this study. A time-sliced co-word network was generated and then clustered. Afterwards, we generated an alluvial diagram to show dynamic changes of hot topics, including their merges and splits over time. Findings： After analyzing the dynamic changes in the field of scientometrics from 2011 to 2015, we found that two clusters being merged did not mean that the old topics had disappeared and a totally new one had emerged. The topics were possibly still active the following year, but the newer topics had drawn more attention. The changes of hot topics reflected the shift in researchers＇ interests. subdivided and re-merged. For example, several topics as research progressed. Research topics in scientometrics were constantly a cluster involving ＂industry＂ was divided into Research limitations： When examining longer time periods, we encounter the problem of dealing with bigger data sets. Analyzing data year by year would be tedious, but if we combine, e.g. two years into one time slice, important details would be missed. Practical implications： This method can be applied to any research field to illustrate the dynamics of hot topics. It can indicate the promising directions for researchers and provide guidance to decision makers. Originality/value： The use of alluvial diagrams is a distinctive and meaningful approach to detecting hot topics and especially to illustrating their dynamics.展开更多
In social networks,many complex factors affect the prediction of user forwarding behavior.This paper proposes an improved SVM prediction method for user forwarding behavior of hot topics to improve prediction accuracy...In social networks,many complex factors affect the prediction of user forwarding behavior.This paper proposes an improved SVM prediction method for user forwarding behavior of hot topics to improve prediction accuracy.Firstly,we consider that the improved Cuckoo Search algorithm can select the optimal penalty parameters and kernel function parameters to optimize the SVM and thus predict the user's forwarding behavior.Secondly,this paper considers the factors that affect the user forwarding behavior comprehensively from the user's own factors and external factors.Finally,based on the characteristics of the user's forwarding behavior changing over time,the time-slicing method is used to predict the trend of hot topics.Experiments show that the method can accurately predict the user's forwarding behavior and can sense the trend of hot topics.展开更多
Purpose:To reveal the research hotpots and relationship among three research hot topics in b iomedicine,namely CRISPR,iPS(induced Pluripotent Stem)cell and Synthetic biology.Design/methodology/approach:We set up their...Purpose:To reveal the research hotpots and relationship among three research hot topics in b iomedicine,namely CRISPR,iPS(induced Pluripotent Stem)cell and Synthetic biology.Design/methodology/approach:We set up their keyword co-occurrence networks with using three indicators and information visualization for metric analysis.Findings:The results reveal the main research hotspots in the three topics are different,but the overlapping keywords in the three topics indicate that they are mutually integrated and interacted each other.Research limitations:All analyses use keywords,without any other forms.Practical implications:We try to find the information distribution and structure of these three hot topics for revealing their research status and interactions,and for promoting biomedical developments.Originality/value:We chose the core keywords in three research hot topics in biomedicine by using h-index.展开更多
Revealing and comparing the evolution process of hot topics in the field of Digital Library in China and abroad.[Methods]:Taking data in the field of Digital Library from core journals in CKNI and Web of Science from ...Revealing and comparing the evolution process of hot topics in the field of Digital Library in China and abroad.[Methods]:Taking data in the field of Digital Library from core journals in CKNI and Web of Science from 1990 s to 2020,topics are extracted by LDA model and hot topics are selected based on life cycle theory.Topic evolution paths are generated to contrast evolution of hot topics between home and abroad which are grouped into dimensions of technology and application.It fails to analyze the lagging performance and reasons of research hot topics in the field of Digital Library at home and abroad.In technological dimension of Digital Library,the research content in China lags behind that at abroad.In terms of application dimension,Chinese application tends to focus on social sciences,while application at abroad tends to focus on natural sciences.The evolution of overall research focus is U-shaped,which gradually shifted from technological research to application research,and now turn back to technological dimension.Nowadays,there are also many emerging topics combined with big data technology.展开更多
This article presents the formal definition and description of popular topics on the Internet,analyzes the relationship between popular words and topics,and finally introduces a method that uses statistics and correla...This article presents the formal definition and description of popular topics on the Internet,analyzes the relationship between popular words and topics,and finally introduces a method that uses statistics and correlation of the popular words in traffic content and network flow characteristics as input for extracting popular topics on the Internet.Based on this,this article adapts a clustering algorithm to extract popular topics and gives formalized results.The test results show that this method has an accuracy of 16.7%in extracting popular topics on the Internet.Compared with web mining and topic detection and tracking(TDT),it can provide a more suitable data source for effective recovery of Internet public opinions.展开更多
By using CiteSpace software to create a knowledge map of authors,institutions and keywords,the literature on the spatio-temporal behavior of Chinese residents based on big data in the architectural planning discipline...By using CiteSpace software to create a knowledge map of authors,institutions and keywords,the literature on the spatio-temporal behavior of Chinese residents based on big data in the architectural planning discipline published in the China Academic Network Publishing Database(CNKI)was analyzed and discussed.It is found that there was a lack of communication and cooperation among research institutions and scholars;the research hotspots involved four main areas,including“application in tourism research”,“application in traffic travel research”,“application in work-housing relationship research”,and“application in personal family life research”.展开更多
The smart grid has been such a hot topic recently.In this paper the hot topics in this field,such as the definition and features of smart grid,key technical problems to be addressed such as new system components,new t...The smart grid has been such a hot topic recently.In this paper the hot topics in this field,such as the definition and features of smart grid,key technical problems to be addressed such as new system components,new types of transducers and measurement technologies,advanced interfaces,event-driven fast-simulated decision-making and coordination,and adaptive control,etc.,and diff iculties are analyzed and discussed.展开更多
目的本文旨在通过文献计量学方法分析心脏术后急性肾损伤(CS-AKI)相关论文,探索关于CS-AKI的研究现状、热点和前沿,为科研人员及临床工作者提供参考。方法使用科学网检索2004年1月至2025年1月发表的关于CS-AKI的核心期刊文献,使用软件C...目的本文旨在通过文献计量学方法分析心脏术后急性肾损伤(CS-AKI)相关论文,探索关于CS-AKI的研究现状、热点和前沿,为科研人员及临床工作者提供参考。方法使用科学网检索2004年1月至2025年1月发表的关于CS-AKI的核心期刊文献,使用软件COOC、VOSviewer对数据进行清洗、去重、分析,对文献发表年代、期刊、期刊来源、关键词等进行可视化分析,探索CS-AKI的研究现状、热点及前沿。结果共筛选出2303篇关于CS-AKI的文献。发文量大体呈逐年上升趋势。发文量前三的期刊是Journal of Cardiothoracic and Vascular Anesthesia(心胸血管麻醉杂志)、Journal of Thoracic and Cardiovascular Surgery(胸外科与心血管外科杂志)、Pediatric Nephrology(儿科肾病学),发文量及平均被引次数最多的国家是美国。通过对高频关键词进行聚类分析,得到三个主要研究方向:(1)CS-AKI的诊断、治疗及预后;(2)诊断CS-AKI的新型生物标记物探索;(3)CS-AKI患者的机器学习风险预测模型构建。通过关键词演进分析总结出CS-AKI的研究热点:发病机制、危险因素及肾损伤新型标志物的探索。研究前沿:CS-AKI预后、保护措施及治疗与风险预测模型的构建。结论CS-AKI日益受到研究人员的关注。本研究提供了较全面的关于CS-AKI研究领域的分析总结,未来该领域的研究方向主要是CS-AKI的防治。展开更多
文摘Internet has become a major medium for infomation transmission, how to detect hot topic on web, track the event development and forecast emergency is important to many fields, particularly to some government departments. On the basis of the researches in the field of topic detection and tracking, we propose a model for hot topic discovery that will pick out hot topics by automatically detecting, clustering and weighting topics on the websites within a time period. Based on the idea of stock index, we also introduce a topic index approach in following the growth of topics, which is useful to analyze and forecast the development of topics on web.
基金supported by the National Social Science Foundation of China (Grant No.: 14BTQ030)
文摘Purpose： In this paper, we combined the method of co-word analysis and alluvial diagram to detect hot topics and illustrate their dynamics. Design/methodology/approach： Articles in the field of scientometrics were chosen as research cases in this study. A time-sliced co-word network was generated and then clustered. Afterwards, we generated an alluvial diagram to show dynamic changes of hot topics, including their merges and splits over time. Findings： After analyzing the dynamic changes in the field of scientometrics from 2011 to 2015, we found that two clusters being merged did not mean that the old topics had disappeared and a totally new one had emerged. The topics were possibly still active the following year, but the newer topics had drawn more attention. The changes of hot topics reflected the shift in researchers＇ interests. subdivided and re-merged. For example, several topics as research progressed. Research topics in scientometrics were constantly a cluster involving ＂industry＂ was divided into Research limitations： When examining longer time periods, we encounter the problem of dealing with bigger data sets. Analyzing data year by year would be tedious, but if we combine, e.g. two years into one time slice, important details would be missed. Practical implications： This method can be applied to any research field to illustrate the dynamics of hot topics. It can indicate the promising directions for researchers and provide guidance to decision makers. Originality/value： The use of alluvial diagrams is a distinctive and meaningful approach to detecting hot topics and especially to illustrating their dynamics.
基金This paper is partially supported by the National Natural Science Foundation of China(Grant No.62006032,62072066)Science and Technology Research Program of Chongqing Municipal Education Commission(Grant No.KJZD-K201900603,KJQN201900629)Chongqing Technology Innovation and Application Development Project(Grant No.cstc2020jscx-msxmX0150).
文摘In social networks,many complex factors affect the prediction of user forwarding behavior.This paper proposes an improved SVM prediction method for user forwarding behavior of hot topics to improve prediction accuracy.Firstly,we consider that the improved Cuckoo Search algorithm can select the optimal penalty parameters and kernel function parameters to optimize the SVM and thus predict the user's forwarding behavior.Secondly,this paper considers the factors that affect the user forwarding behavior comprehensively from the user's own factors and external factors.Finally,based on the characteristics of the user's forwarding behavior changing over time,the time-slicing method is used to predict the trend of hot topics.Experiments show that the method can accurately predict the user's forwarding behavior and can sense the trend of hot topics.
基金the National Natural Science Foundation of China Grant 71673131 for financial support
文摘Purpose:To reveal the research hotpots and relationship among three research hot topics in b iomedicine,namely CRISPR,iPS(induced Pluripotent Stem)cell and Synthetic biology.Design/methodology/approach:We set up their keyword co-occurrence networks with using three indicators and information visualization for metric analysis.Findings:The results reveal the main research hotspots in the three topics are different,but the overlapping keywords in the three topics indicate that they are mutually integrated and interacted each other.Research limitations:All analyses use keywords,without any other forms.Practical implications:We try to find the information distribution and structure of these three hot topics for revealing their research status and interactions,and for promoting biomedical developments.Originality/value:We chose the core keywords in three research hot topics in biomedicine by using h-index.
文摘Revealing and comparing the evolution process of hot topics in the field of Digital Library in China and abroad.[Methods]:Taking data in the field of Digital Library from core journals in CKNI and Web of Science from 1990 s to 2020,topics are extracted by LDA model and hot topics are selected based on life cycle theory.Topic evolution paths are generated to contrast evolution of hot topics between home and abroad which are grouped into dimensions of technology and application.It fails to analyze the lagging performance and reasons of research hot topics in the field of Digital Library at home and abroad.In technological dimension of Digital Library,the research content in China lags behind that at abroad.In terms of application dimension,Chinese application tends to focus on social sciences,while application at abroad tends to focus on natural sciences.The evolution of overall research focus is U-shaped,which gradually shifted from technological research to application research,and now turn back to technological dimension.Nowadays,there are also many emerging topics combined with big data technology.
基金was supported by the National Natural Science Foundation of China (Grant No.60574087)the Hi-Tech Research and Development Program of China (2007AA01Z475,2007AA01Z480,2007A-A01Z464)the 111 International Collaboration Program of China.
文摘This article presents the formal definition and description of popular topics on the Internet,analyzes the relationship between popular words and topics,and finally introduces a method that uses statistics and correlation of the popular words in traffic content and network flow characteristics as input for extracting popular topics on the Internet.Based on this,this article adapts a clustering algorithm to extract popular topics and gives formalized results.The test results show that this method has an accuracy of 16.7%in extracting popular topics on the Internet.Compared with web mining and topic detection and tracking(TDT),it can provide a more suitable data source for effective recovery of Internet public opinions.
文摘By using CiteSpace software to create a knowledge map of authors,institutions and keywords,the literature on the spatio-temporal behavior of Chinese residents based on big data in the architectural planning discipline published in the China Academic Network Publishing Database(CNKI)was analyzed and discussed.It is found that there was a lack of communication and cooperation among research institutions and scholars;the research hotspots involved four main areas,including“application in tourism research”,“application in traffic travel research”,“application in work-housing relationship research”,and“application in personal family life research”.
文摘The smart grid has been such a hot topic recently.In this paper the hot topics in this field,such as the definition and features of smart grid,key technical problems to be addressed such as new system components,new types of transducers and measurement technologies,advanced interfaces,event-driven fast-simulated decision-making and coordination,and adaptive control,etc.,and diff iculties are analyzed and discussed.
文摘目的本文旨在通过文献计量学方法分析心脏术后急性肾损伤(CS-AKI)相关论文,探索关于CS-AKI的研究现状、热点和前沿,为科研人员及临床工作者提供参考。方法使用科学网检索2004年1月至2025年1月发表的关于CS-AKI的核心期刊文献,使用软件COOC、VOSviewer对数据进行清洗、去重、分析,对文献发表年代、期刊、期刊来源、关键词等进行可视化分析,探索CS-AKI的研究现状、热点及前沿。结果共筛选出2303篇关于CS-AKI的文献。发文量大体呈逐年上升趋势。发文量前三的期刊是Journal of Cardiothoracic and Vascular Anesthesia(心胸血管麻醉杂志)、Journal of Thoracic and Cardiovascular Surgery(胸外科与心血管外科杂志)、Pediatric Nephrology(儿科肾病学),发文量及平均被引次数最多的国家是美国。通过对高频关键词进行聚类分析,得到三个主要研究方向:(1)CS-AKI的诊断、治疗及预后;(2)诊断CS-AKI的新型生物标记物探索;(3)CS-AKI患者的机器学习风险预测模型构建。通过关键词演进分析总结出CS-AKI的研究热点:发病机制、危险因素及肾损伤新型标志物的探索。研究前沿:CS-AKI预后、保护措施及治疗与风险预测模型的构建。结论CS-AKI日益受到研究人员的关注。本研究提供了较全面的关于CS-AKI研究领域的分析总结,未来该领域的研究方向主要是CS-AKI的防治。
