Detecting Dynamics of Hot Topics with Alluvial Diagrams:A Timeline Visualization

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.

A Metric Approach to Hot Topics in Biomedicine via Keyword Co-occurrence

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.

ICS-SVM:A user retweet prediction method for hot topics based on improved SVM

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.

Contrastive analysis in China and abroad on the Evolution of hot topics in the field of digital library based on LDA model

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.

Approach to extracting hot topics based on network traffic content

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.

Hotshots of Spatio-temporal Behavior of Chinese Residents in the Context of Big Data:Visual Analysis Based on CiteSpace

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”.

Design and Implementation of On-Line Hot Topic Discovery Model

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.

How did high temperature extremes in southern Xinjiang,China induce the repaid rise in jujube futures prices in the summer of 2021?

In the summer of 2021,southern Xinjiang,China,experienced a temporary period of high temperature extremes.Because of this weather event,jujube futures prices rose by more than 50%in a short time.To clarify the influence mechanism of these two events,we investigated the current status of jujube farming and collected investors’online comments.We analysed these comments specifically using textual analysis tools,such as co-word networks.Results showed that the concerns of investors about the reduction in jujube production triggered by high temperature extremes were the primary reason for the rapid rise in jujube futures prices.Especially in combination with the cultivation density of jujube and their adaptability to the growing environment,a new understanding can be obtained.That is to say,when a crop is excessively densely cultivated in a region and is highly sensitive to a meteorological variable anomaly at a certain growth stage,a less destructive local extreme weather event could induce severe panic among investors regarding production reduction and thus influence the normal changes in futures price.In response to the impact mechanisms revealed in this study,we proposed policy recommendations,such as strengthening the degree of crop damage disclosure and designing weather futures derivatives,to address similar situations in the future.This study not only fills the gap in the research on the impact paths of high temperature extremes on jujube futures prices but also has a reference value for securing the stability of futures prices of related agricultural products in the future.

A comprehensive bibliometric analysis of Apache Hadoop from 2008 to 2020

Purpose-The purpose of this paper is to make an overview of 6,618 publications of Apache Hadoop from 2008 to 2020 in order to provide a conclusive and comprehensive analysis for researchers in this field,as well as a preliminary knowledge of Apache Hadoop for interested researchers.Design/methodology/approach-This paper employs the bibliometric analysis and visual analysis approaches to systematically study and analyze publications about Apache Hadoop in the Web of Science database.This study aims to investigate the topic of Apache Hadoop by means of bibliometric analysis with the aid of visualization applications.Through the bibliometric analysis of the collected documents,this paper analyzes the main statistical characteristics and cooperation networks.Research themes,research hotspots and future development trends are also investigated through the keyword analysis.Findings-The research on Apache Hadoop is still the top priority in the future,and how to improve the performance of Apache Hadoop in the era of big data is one of the research hotspots.Research limitations/implications-This paper makes a comprehensive analysis of Apache Hadoop with methods of bibliometrics,and it is valuable for researchers can quickly grasp the hot topics in this area.Originality/value-This paper draws the structural characteristics of the publications in this field and summarizes the research hotspots and trends in this field in recent years,aiming to understand the development status and trends in this field and inspire new ideas for researchers.

Global perspectives and future research directions for the phytoremediation of heavy metal-contaminated soil:A knowledge mapping analysis from 2001 to 2020

In total,9,552 documents were extracted from the Web of Science Core Collection and subjected to knowledge mapping and visualization analysis for the field of phytoremediation of HM-contaminated soil(PHMCS)with CiteSpace 5.7 R3 software.The results showed that(1)the number of publications increased linearly over the studied period.The top 10 countries/regions,institutions and authors contributing to this field were exhibited.(2)Keyword co-occurrence cluster analysis revealed a total of 8 clusters,including“Bioremediation,”“Arsenic,”“Biochar,”“Oxidative stress,”“Hyperaccumulation,”“EDTA,”“Arbuscular mycorrhizal fungi,”and“Environmental pollution”clusters(3)In total,334 keyword bursts were obtained,and the 25 strongest,longest duration,and newest keyboard bursts were analyzed in depth.The strongest keyword burst test showed that the hottest keywords could be divided into 7 groups,i.e.,“Plant bioremediation materials,”“HM types,”“Chelating amendments,”“Other improved strategies,”“Bioremediation characteristics,”“Risk assessment,”and“Other.”Almost half of the newest topics had emerged in the past 3 years,including“biochar,”“drought,”“health risk assessment,”“electrokinetic remediation,”“nanoparticle,”and“intercropping.”(4)In total,9 knowledge base clusters were obtained in this study.The studies of Ali et al.(2013),Blaylock et al.(1997),Huang et al.(1997),van der Ent et al.(2013),Salt et al.(1995),and Salt(1998),which had both high frequencies and the strongest burst scores,have had the most profound effects on PHMCS research.Finally,future research directions were proposed.

Flash translation layer:a review and bibliometric analysis

Purpose-The purpose of this paper is to make an overview of 474 publications and 512 patents of FTL from 1987 to 2020 in order to provide a conclusive and comprehensive analysis for researchers in this field,as well as a preliminary knowledge of FTL for interested researchers.Design/methodology/approach-Firstly,the FTL algorithms are classified and its functions are introduced in detail.Secondly,the structures of the publications are analyzed in terms of the fundamental information and the publication of the most productive countries/regions,institutions and authors.After that,co-citation networks of institutions,authors and papers illustrated by VOS Viewer are given to show the relationship among those and the most influential of them is further analyzed.Then,the characteristics of the patent are analyzed based on the basic information and classification of the patent and the most productive inventors.In order to obtain research hotspots and trends in this field,the time-line review and citation burst detection of keywords carried out by Cite Space are made to be visual.Finally,based on the above analysis,it draws some other important conclusions and the development trend of this field.Findings-The research on FTL algorithm is still the top priority in the future,and how to improve the performance of SSD in the era of big data is one of the research hotspots.Research limitations/implications-This paper makes a comprehensive analysis of FTL with the method of bibliometrics,and it is valuable for researchers can quickly grasp the hotspots in this area.Originality/value-This article draws the structural characteristics of the publications in this field and summarizes the research hotspots and trends in this field in recent years,aiming to inspire new ideas for researchers.