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Exploratory Data Analysis Applied in Mapping Multi-element Soil Geochemical Anomalies for Drill Target Definition:A Case Study from the Unpha Layered Non-magmatic Hydrothermal Pb-Zn Deposit,DPR Korea
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作者 JANG Gwang-Hyok WON Hyon-Chol +1 位作者 HWANG Bo-Hyon CHOI Chol-Man 《Acta Geologica Sinica(English Edition)》 SCIE CAS CSCD 2021年第4期1357-1365,共9页
A factor analysis was applied to soil geochemical data to define anomalies related to buried Pb-Zn mineralization.A favorable main factor with a strong association of the elements Zn,Cu and Pb,related to mineralizatio... A factor analysis was applied to soil geochemical data to define anomalies related to buried Pb-Zn mineralization.A favorable main factor with a strong association of the elements Zn,Cu and Pb,related to mineralization,was selected for interpretation.The median+2 MAD(median absolute deviation)method of exploratory data analysis(EDA)and C-A(concentration-area)fractal modeling were then applied to the Mahalanobis distance,as defined by Zn,Cu and Pb from the factor analysis to set the thresholds for defining multi-element anomalies.As a result,the median+2 MAD method more successfully identified the Pb-Zn mineralization than the C-A fractal model.The soil anomaly identified by the median+2 MAD method on the Mahalanobis distances defined by three principal elements(Zn,Cu and Pb)rather than thirteen elements(Co,Zn,Cu,V,Mo,Ni,Cr,Mn,Pb,Ba,Sr,Zr and Ti)was the more favorable reflection of the ore body.The identified soil geochemical anomalies were compared with the in situ economic Pb-Zn ore bodies for validation.The results showed that the median+2 MAD approach is capable of mapping both strong and weak geochemical anomalies related to buried Pb-Zn mineralization,which is therefore useful at the reconnaissance drilling stage. 展开更多
关键词 factor analysis exploratory data analysis Mahalanobis distance multi-element Unpha
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Predicting the Subcellular Localization of Human Proteins Using Machine Learning and Exploratory Data Analysis 被引量:1
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作者 George K. Acquaah-Mensah Sonia M. Leach Chittibabu Guda 《Genomics, Proteomics & Bioinformatics》 SCIE CAS CSCD 2006年第2期120-133,共14页
Identifying the subcellular localization of proteins is particularly helpful in the functional annotation of gene products. In this study, we use Machine Learning and Exploratory Data Analysis (EDA) techniques to ex... Identifying the subcellular localization of proteins is particularly helpful in the functional annotation of gene products. In this study, we use Machine Learning and Exploratory Data Analysis (EDA) techniques to examine and characterize amino acid sequences of human proteins localized in nine cellular compartments. A dataset of 3,749 protein sequences representing human proteins was extracted from the SWISS-PROT database. Feature vectors were created to capture specific amino acid sequence characteristics. Relative to a Support Vector Machine, a Multi-layer Perceptron, and a Naive Bayes classifier, the C4.5 Decision Tree algorithm was the most consistent performer across all nine compartments in reliably predicting the subcellular localization of proteins based on their amino acid sequences (average Precision=0.88; average Sensitivity=0.86). Furthermore, EDA graphics characterized essential features of proteins in each compartment. As examples, proteins localized to the plasma membrane had higher proportions of hydrophobic amino acids; cytoplasmic proteins had higher proportions of neutral amino acids; and mitochondrial proteins had higher proportions of neutral amino acids and lower proportions of polar amino acids. These data showed that the C4.5 classifier and EDA tools can be effective for characterizing and predicting the subcellular localization of human proteins based on their amino acid sequences. 展开更多
关键词 subcellular localization Machine Learning Exploratory Data Analysis Decision Tree
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Spatiotemporal evolution and influencing factors of urban resilience in the Yellow River Basin,China
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作者 JI Xiaomei NIE Zhilei +2 位作者 WANG Kaiyong XU Mingxian FANG Yuhao 《Regional Sustainability》 2024年第3期54-68,共15页
The Yellow River Basin of China is a key region that contains myriad interactions between human activities and natural environment.Industrialization and urbanization promote social-economic development,but they also h... The Yellow River Basin of China is a key region that contains myriad interactions between human activities and natural environment.Industrialization and urbanization promote social-economic development,but they also have generated a series of environmental and ecological issues in this basin.Previous researches have evaluated urban resilience at the national,regional,urban agglomeration,city,and prefecture levels,but not at the watershed level.To address this research gap and elevate the Yellow River Basin’s urban resilience level,we constructed an urban resilience evaluation index system from five dimensions:industrial resilience,social resilience,environmental resilience,technological resilience,and organizational resilience.The entropy weight method was used to comprehensively evaluate urban resilience in the Yellow River Basin.The exploratory spatial data analysis method was employed to study the spatiotemporal differences in urban resilience in the Yellow River Basin in 2010,2015,and 2020.Furthermore,the grey correlation analysis method was utilized to explore the influencing factors of these differences.The results of this study are as follows:(1)the overall level of urban resilience in the Yellow River Basin was relatively low but showed an increasing trend during 2010–2015,and significant spatial distribution differences were observed,with a higher resilience level in the eastern region and a low-medium resilience level in the western region;(2)the differences in urban resilience were noticeable,with industrial resilience and social resilience being relatively highly developed,whereas organizational resilience and environmental resilience were relatively weak;and(3)the correlation ranking of resilience influencing factors was as follows:science and technology level>administrative power>openness>market forces.This research can provide a basis for improving the resilience level of cities in the Yellow River Basin and contribute to the high-quality development of the region. 展开更多
关键词 Urban resilience Spatiotemporal evolution Entropy weight method Exploratory spatial data analysis method Grey correlation analysis method Yellow River Basin
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Spatio-temporal evolution and factor explanatory power analysis of urban resilience in the Yangtze River Economic Belt 被引量:2
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作者 Changsheng Ye Mengshan Hu +2 位作者 Lei Lu Qian Dong Moli Gu 《Geography and Sustainability》 2022年第4期299-311,共13页
Urban resilience assesses a city’s ability to withstand unknown risks.Scholars are not comprehensive in assessing urban resilience,and they lack consideration of population resilience.This study investigated 110 pref... Urban resilience assesses a city’s ability to withstand unknown risks.Scholars are not comprehensive in assessing urban resilience,and they lack consideration of population resilience.This study investigated 110 prefecturelevel cities in the Yangtze River Economic Belt(YREB)as study areas.We calculated the YREB’s level of urban resilience based on the aspects of“economy-society-population-ecology-infrastructure”,which ensured that the comprehensive evaluation of urban resilience is complete and sufficient.The spatio-temporal evolution of urban resilience was analyzed using exploratory spatial data.Geodetectors were used to investigate the impact of several indicators,focusing on economic,social,population,ecological,and infrastructure factors,on urban resilience.The results showed that the urban resilience of the YREB has maintained a slow upward trend from 2005 to 2018,and the average urban resilience of the YREB has risen from 0.2442 to 0.2560.The resilience gap between cities in the study region increased initially and then decreased.The dominant factor in the spatial differentiation of urban resilience was the economic factors,followed by the population factors.Urban resilience has been clarified and an evaluation index system is constructed,which can provide an effective reference for the evaluation of urban resilience among countries around the world.Based on this,factors that optimize urban resilience are configured,and the regional and national sustainable development can be promoted. 展开更多
关键词 Urban resilience Spatial-temporal differentiation Geographical detector Exploratory spatial data analysis The Yangtze River Economic Belt
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A comprehensive review of tools for exploratory analysis of tabular industrial datasets
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作者 Aindrila Ghosh Mona Nashaat +2 位作者 James Miller Shaikh Quader Chad Marston 《Visual Informatics》 EI 2018年第4期235-253,共19页
Exploratory data analysis plays a major role in obtaining insights from data.Over the last two decades,researchers have proposed several visual data exploration tools that can assist with each step of the analysis pro... Exploratory data analysis plays a major role in obtaining insights from data.Over the last two decades,researchers have proposed several visual data exploration tools that can assist with each step of the analysis process.Nevertheless,in recent years,data analysis requirements have changed significantly.With constantly increasing size and types of data to be analyzed,scalability and analysis duration are now among the primary concerns of researchers.Moreover,in order to minimize the analysis cost,businesses are in need of data analysis tools that can be used with limited analytical knowledge.To address these challenges,traditional data exploration tools have evolved within the last few years.In this paper,with an in-depth analysis of an industrial tabular dataset,we identify a set of additional exploratory requirements for large datasets.Later,we present a comprehensive survey of the recent advancements in the emerging field of exploratory data analysis.We investigate 50 academic and non-academic visual data exploration tools with respect to their utility in the six fundamental steps of the exploratory data analysis process.We also examine the extent to which these modern data exploration tools fulfill the additional requirements for analyzing large datasets.Finally,we identify and present a set of research opportunities in the field of visual exploratory data analysis. 展开更多
关键词 Exploratory data analysis Industrial tabular data Interactive visualization Systematic literature review Research opportunities
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A comprehensive framework for exploratory spatial data analysis:Moran location and variance scatterplots 被引量:2
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作者 J.G.Negreiros M.T.Painho +1 位作者 F.J.Aguilar M.A.Aguilar 《International Journal of Digital Earth》 SCIE 2010年第2期157-186,共30页
A significant Geographic Information Science(GIS)issue is closely related to spatial autocorrelation,a burning question in the phase of information extraction from the statistical analysis of georeferenced data.At pre... A significant Geographic Information Science(GIS)issue is closely related to spatial autocorrelation,a burning question in the phase of information extraction from the statistical analysis of georeferenced data.At present,spatial autocorrelation presents two types of measures:continuous and discrete.Is it possible to use Moran’s I and the Moran scatterplot with continuous data?Is it possible to use the same methodology with discrete data?A particular and cumbersome problem is the choice of the spatial-neighborhood matrix(W)for points data.This paper addresses these issues by introducing the concept of covariogram contiguity,where each weight is based on the variogram model for that particular dataset:(1)the variogram,whose range equals the distance with the highest Moran I value,defines the weights for points separated by less than the estimated range and(2)weights equal zero for points widely separated from the variogram range considered.After the W matrix is computed,the Moran location scatterplot is created in an iterative process.In accordance with various lag distances,Moran’s I is presented as a good search factor for the optimal neighborhood area.Uncertainty/transition regions are also emphasized.At the same time,a new Exploratory Spatial Data Analysis(ESDA)tool is developed,the Moran variance scatterplot,since the conventional Moran scatterplot is not sensitive to neighbor variance.This computer-mapping framework allows the study of spatial patterns,outliers,changeover areas,and trends in an ESDA process.All these tools were implemented in a free web e-Learning program for quantitative geographers called SAKWeb#(or,in the near future,myGeooffice.org). 展开更多
关键词 GEOCOMPUTATION exploratory spatial data analysis spatial autocorrelation Moran scatterplot Moran’s I variography
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Churn Prediction Task in MOOC
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作者 Lisitsyna Liubov Oreshin SA 《Journal of Computer Science Research》 2019年第1期29-35,共7页
Churn prediction is a common task for machine learning applications in business.In this paper,this task is adapted for solving problem of low efficiency of massive open online courses(only 5%of all the students finish... Churn prediction is a common task for machine learning applications in business.In this paper,this task is adapted for solving problem of low efficiency of massive open online courses(only 5%of all the students finish their course).The approach is presented on course“Methods and algorithms of the graph theory”held on national platform of online education in Russia.This paper includes all the steps to build an intelligent system to predict students who are active during the course,but not likely to finish it.The first part consists of constructing the right sample for prediction,EDA and choosing the most appropriate week of the course to make predictions on.The second part is about choosing the right metric and building models.Also,approach with using ensembles like stacking is proposed to increase the accuracy of predictions.As a result,a general approach to build a churn prediction model for online course is reviewed.This approach can be used for making the process of online education adaptive and intelligent for a separate student. 展开更多
关键词 Machine learning Data science Exploratory data analysis Logistic regression Gradient boosting on trees STACKING CLASSIFICATION RANKING
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Changing Rural Development Inequality in Jilin Province, Northeast China 被引量:9
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作者 CHENG Yeqing WANG Yanfei +1 位作者 WANG Zheye LUO Xiaolong 《Chinese Geographical Science》 SCIE CSCD 2013年第5期620-633,共14页
Rural development inequality is an important practical issue during the course of full establishment of a ′moderately well-off society′ in modern China,and the objective understanding and evaluation of the status an... Rural development inequality is an important practical issue during the course of full establishment of a ′moderately well-off society′ in modern China,and the objective understanding and evaluation of the status and regional inequality of rural development can provide scientific basis for ′building a new countryside′ and coordination development of rural-urban regions.Based on the county-level data of 2000,2005 and 2009,this paper examines the rural development inequality of Jilin Province in Northeast China by establishing a rural development index.The spatio-temporal dynamic patterns and domain factors are discussed by using the method of exploratory spatial data analysis and multi-regression model.The results are shown as follows.Firstly,most of the counties were in lower development level,which accounted for 58.3%,62.5% and 66.7% of the total counties in 2000,2005 and 2009,respectively.The characteristics of spatial inequality were very obvious at county level.For example,rural development level of Changchun Proper and the proper of seven prefecture-level cities were much higher than that of the surrounding regions.The counties in the eastern and northern Jilin Province were the lowest regions of rural development level,while the middle counties were the rapid growth areas in rural economy.Secondly,Moran′s I of rural development index(RDI) was 0.01,–0.16 and –0.06 in 2000,2005 and 2009,respectively,which indicated that spatial agglomeration of RDI was not obvious in Jilin Province,and took on the characteristic of random distribution.The counties of both the units and its adjacent units have higher development level(HH) were transferred from the western areas to the eastern areas,while the countries of both the units and its adjacent units have lower development level(LL) were diffused from the eastern to middle and western Jilin Province.Finally,the result of multi-regression analysis showed that the improvement of agricultural production condition,development of agricultural economics and the adjustment of industrial structure were the domain factors affecting rural development inequality of Jilin Province in the later ten years. 展开更多
关键词 rural development index exploratory spatial data analysis multi-regression model Jilin Province
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Spatial Pattern and Regional Types of Rural Settlements in Xuzhou City,Jiangsu Province,China 被引量:7
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作者 MA Xiaodong QIU Fangdao +2 位作者 LI Quanlin SHAN Yongbin CAO Yong 《Chinese Geographical Science》 SCIE CSCD 2013年第4期482-491,共10页
This paper principally focuses on the morphological differences,spatial pattern and regional types of rural settlements in Xuzhou City of Jiangsu Province in China.Using satellite images of Xuzhou City taken in 2007 a... This paper principally focuses on the morphological differences,spatial pattern and regional types of rural settlements in Xuzhou City of Jiangsu Province in China.Using satellite images of Xuzhou City taken in 2007 and 2008 and models of exploratory spatial data analysis(ESDA) and spatial metrics,the paper conducts a quantitative analysis of the morphological pattern of rural settlements,and finds significant characteristics.First,rural settlements in Xuzhou City are significantly agglomerated in terms of their spatial distribution;meanwhile,there is significant variation in the geographical density distribution.Second,the scale of rural settlements in Xuzhou City is larger than the average in Jiangsu Province,and the histogram of the scale data is more even and more like a gamma distribution.There are a significant high-value cluster in the scale distribution,and local negative correlation between the scale and density distribution of rural settlements in Xuzhou City.Third,the morphology of rural settlements in Xuzhou City shows relative regularity with good connection and integrity,but the spatial variation of the morphology is anisotropic.Finally,according to the characteristics of density,scale,and form of rural settlements,the rural settlements of Xuzhou City are divided into three types:A high-density and point-scattered type,a low-density and cluster-like type and a mass-like and sparse type.The research findings could be used as the scientific foundation for rural planning and community rebuilding,particularly in less-developed areas. 展开更多
关键词 rural settlements spatial pattern regional types exploratory spatial data analysis(ESDA) Xuzhou City
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Detection of spatial hot spots and variation for the neon flying squid Ommastrephes bartramii resources in the northwest Pacific Ocean 被引量:6
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作者 冯永玖 陈新军 刘艳 《Chinese Journal of Oceanology and Limnology》 SCIE CAS CSCD 2017年第4期921-935,共15页
With the increasing effects of global climate change and fishing activities,the spatial distribution of the neon flying squid(Ommastrephes bartramii) is changing in the traditional fishing ground of 150°-160°... With the increasing effects of global climate change and fishing activities,the spatial distribution of the neon flying squid(Ommastrephes bartramii) is changing in the traditional fishing ground of 150°-160°E and 38°-45°N in the northwest Pacific Ocean.This research aims to identify the spatial hot and cold spots(i.e.spatial clusters) of O.bartramii to reveal its spatial structure using commercial fishery data from2007 to 2010 collected by Chinese mainland squid-j igging fleets.A relatively strongly-clustered distribution for O.bartramii was observed using an exploratory spatial data analysis(ESDA) method.The results show two hot spots and one cold spot in 2007 while only one hot and one cold spots were identified each year from2008 to 2010.The hot and cold spots in 2007 occupied 8.2%and 5.6%of the study area,respectively;these percentages for hot and cold spot areas were 5.8%and 3.1%in 2008,10.2%and 2.9%in 2009,and 16.4%and 11.9%in 2010,respectively.Nearly half(>45%) of the squid from 2007 to 2009 reported by Chinese fleets were caught in hot spot areas while this percentage reached its peak at 68.8%in 2010,indicating that the hot spot areas are central fishing grounds.A further change analysis shows the area centered at156°E/43.5°N was persistent as a hot spot over the whole period from 2007 to 2010.Furthermore,the hot spots were mainly identified in areas with sea surface temperature(SST) in the range of 15-20℃ around warm Kuroshio Currents as well as with the chlorophyll-a(chl-a) concentration above 0.3 mg/m^3.The outcome of this research improves our understanding of spatiotemporal hotspots and its variation for O.bartramii and is useful for sustainable exploitation,assessment,and management of this squid. 展开更多
关键词 Ommastrephes bartramii exploratory spatial data analysis (ESDA) spatial hot spot spatialautocorrelation variation assessment northwest Pacific Ocean
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Spatio-temporal Dynamic of Quality of Life of Residents, Northeast China 被引量:1
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作者 CHENG Yeqing WANG Ying +3 位作者 WANG Zheye DU Na SUN Yu ZHAO Zhizhong 《Chinese Geographical Science》 SCIE CSCD 2016年第5期623-637,共15页
Quality of life(QOL) is a hotspot issue that has attracted increasing attention from the Chinese Government and scholars, it is also a vital issue that should be addressed during the cause of ′establishing overall we... Quality of life(QOL) is a hotspot issue that has attracted increasing attention from the Chinese Government and scholars, it is also a vital issue that should be addressed during the cause of ′establishing overall well-off society′. Northeast China is one of the most import old industrial bases in China, however, the industrial structure of heavy chemical industry and the development mode of ′production first, living last′ have leaded to series of social problems, which have also become a serious bottleneck to social stability and economic sustainable development. Through applying the methods of BP neural network, exploratory spatial data analysis(ESDA) and spatial regression model, this paper examines the space-time dynamics of QOL of the residents in Northeast China. We first investigate the indexes of QOL of the residents and then use ESDA methods to visualize its space-time relationship. We have found a spatial agglomeration of QOL of the residents in middle-southern Liaoning Province, central Jilin Province and Harbin-Qiqihar-Daqing area of Heilongjiang Province. Two third of the counties are low-low spatial correlation, and the correlative type of about 60% of the prefecture level areas keeps stable, indicating QOL of the residents in Northeast China shows a certain character of path dependence or spatial locked. We have also found that economic strength and development levels of service industry have positive and obvious effect on QOL of the residents, while the effect of such indexes as the social service level and the proportion of the tertiary industries are less. 展开更多
关键词 quality of life (QOL) BP neural network exploratory spatial data analysis (ESDA) spatial regression model Northeast China
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Improving symbolic data visualization for pattern recognition and knowledge discovery 被引量:1
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作者 Kadri Umbleja Manabu Ichino Hiroyuki Yaguchi 《Visual Informatics》 EI 2020年第1期23-31,共9页
This paper examines the visualization of symbolic data and considers the challenges rising from its complex structure.Symbolic data is usually aggregated from large data sets and used to hide entry specific details an... This paper examines the visualization of symbolic data and considers the challenges rising from its complex structure.Symbolic data is usually aggregated from large data sets and used to hide entry specific details and to transform huge amounts of data(like big data)into analyzable quantities.It is also used to offer an overview in places where general trends are more important than individual details.Symbolic data comes in many forms like intervals,histograms,categories and modal multi-valued objects.Symbolic data can also be considered as a distribution.Currently,the de facto visualization approach for symbolic data is zoomstars which has many limitations.The biggest limitation is that the default distributions(histograms)are not supported in 2D as additional dimension is required.This paper proposes several new improvements for zoomstars which would enable it to visualize histograms in 2D by using a quantile or an equivalent interval approach.In addition,several improvements for categorical and modal variables are proposed for a clearer indication of presented categories.Recommendations for different approaches to zoomstars are offered depending on the data type and the desired goal.Furthermore,an alternative approach that allows visualizing the whole data set in comprehensive table-like graph,called shape encoding,is proposed.These visualizations and their usefulness are verified with three symbolic data sets in exploratory data mining phase to identify trends,similar objects and important features,detecting outliers and discrepancies in the data. 展开更多
关键词 Data visualization Symbolic data Zoomstar Shape encoding Exploratory data analysis
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Comparison of Principal Components Analysis,Independent Components Analysis and Common Components Analysis
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作者 Douglas N.Rutledge 《Journal of Analysis and Testing》 EI 2018年第3期235-248,共14页
The aim of this work is to describe and compare three exploratory chemometrical tools,principal components analysis,independent components analysis and common components analysis,the last one being a modification of t... The aim of this work is to describe and compare three exploratory chemometrical tools,principal components analysis,independent components analysis and common components analysis,the last one being a modification of the multi-block statistical method known as common components and specific weights analysis.The three methods were applied to a set of data to show the differences and similarities of the results obtained,highlighting their complementarity. 展开更多
关键词 Exploratory data analysis CHEMOMETRICS Principal components analysis Independent components analysis Common components analysis Common components and specific weights analysis
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Spatial-temporal characteristics and decoupling effects of China’s carbon footprint based on multi-source data 被引量:9
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作者 ZHANG Yongnian PAN Jinghu +1 位作者 ZHANG Yongjiao XU Jing 《Journal of Geographical Sciences》 SCIE CSCD 2021年第3期327-349,共23页
In 2007,China surpassed the USA to become the largest carbon emitter in the world.China has promised a 60%–65%reduction in carbon emissions per unit GDP by 2030,compared to the baseline of 2005.Therefore,it is import... In 2007,China surpassed the USA to become the largest carbon emitter in the world.China has promised a 60%–65%reduction in carbon emissions per unit GDP by 2030,compared to the baseline of 2005.Therefore,it is important to obtain accurate dynamic information on the spatial and temporal patterns of carbon emissions and carbon footprints to support formulating effective national carbon emission reduction policies.This study attempts to build a carbon emission panel data model that simulates carbon emissions in China from 2000–2013 using nighttime lighting data and carbon emission statistics data.By applying the Exploratory Spatial-Temporal Data Analysis(ESTDA)framework,this study conducted an analysis on the spatial patterns and dynamic spatial-temporal interactions of carbon footprints from 2001–2013.The improved Tapio decoupling model was adopted to investigate the levels of coupling or decoupling between the carbon emission load and economic growth in 336 prefecture-level units.The results show that,firstly,high accuracy was achieved by the model in simulating carbon emissions.Secondly,the total carbon footprints and carbon deficits across China increased with average annual growth rates of 4.82%and 5.72%,respectively.The overall carbon footprints and carbon deficits were larger in the North than that in the South.There were extremely significant spatial autocorrelation features in the carbon footprints of prefecture-level units.Thirdly,the relative lengths of the Local Indicators of Spatial Association(LISA)time paths were longer in the North than that in the South,and they increased from the coastal to the central and western regions.Lastly,the overall decoupling index was mainly a weak decoupling type,but the number of cities with this weak decoupling continued to decrease.The unsustainable development trend of China’s economic growth and carbon emission load will continue for some time. 展开更多
关键词 nighttime lighting data carbon footprint carbon deficit exploratory spatial-temporal data analysis spatial-temporal interaction characteristics decoupling effect
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Uncovering the Online Social Structure Surrounding COVID-19 被引量:3
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作者 Philip D.Waggoner Robert Y.Shapiro +1 位作者 Samuel Frederick Ming Gong 《Journal of Social Computing》 2021年第2期157-165,共9页
How do people talk about COVID-19 online?To address this question,we offer an unsupervised framework that allows us to examine Twitter framings of the pandemic.Our approach employs a network-based exploration of socia... How do people talk about COVID-19 online?To address this question,we offer an unsupervised framework that allows us to examine Twitter framings of the pandemic.Our approach employs a network-based exploration of social media data to identify,categorize,and understand communication patterns about the novel coronavirus on Twitter.The simplest structure that emerges from our analysis is the distinction between the internal/personal,external/global,and generic threat framings of the pandemic.This structure replicates in different Twitter samples and is validated using the variation of information measure,reflecting the significance and stability of our findings.Such an exploratory study is useful for understanding the contours of the natural,non-random structure in this online space.We contend that this understanding of structure is necessary to address a host of causal,supervised,and related questions downstream. 展开更多
关键词 COVID-19 NETWORKS community detection TWITTER exploratory data analysis
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The measure and characteristics of spatial-temporal evolution of China's science and technology resource allocation efficiency 被引量:14
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作者 FAN Fei DU Debin WANG Xinzhu 《Journal of Geographical Sciences》 SCIE CSCD 2014年第3期492-508,共17页
According to the connotation and structure of science and technology resources and some relevant data of more than 286 cities at prefecture level and above during 2001-2010, using modified method--Data Envelopment Ana... According to the connotation and structure of science and technology resources and some relevant data of more than 286 cities at prefecture level and above during 2001-2010, using modified method--Data Envelopment Analysis (DEA), science and tech- nology (S&T) resource allocation efficiency of different cities in different periods has been figured out, which, uncovers the distributional difference and change law of S&T resource allocation efficiency from the time-space dimension. Based on that, this paper has analyzed and discussed the spatial distribution pattern and evolution trend of S&T resource allocation efficiency in different cities by virtue of the Exploratory Spatial Data Analysis (ESDA). It turned out that: (1) the average of S&T resource allocation efficiency in cities at prefecture level and above has always stayed at low levels, moreover, with repeated fluctuations between high and low, which shows a decreasing trend year by year. Besides, the gap between the East and the West is widening. (2) The asymmetrical distribution of S&T resource allocation effi- ciency presents a spatial pattern of successively decreasing from Eastern China, Central China to Western China. The cities whose S&T resource allocation efficiency are at higher level and high level take on a cluster distribution, which fits well with the 23 forming urban agglomerations in China. (3) The coupling degree between S&T resource allocation efficiency and economic environment assumes a certain positive correlation, but not completely the same. The differentiation of S&T resource allocation efficiency is common in regional devel- opment, whose existence and evolution are directly or indirectly influenced by and regarded as the reflection of many elements, such as geographical location, the natural endowment and environment of S&T resources and so on. (4) In the perspective of the evolution of spatial structure, S&T resource allocation efficiency of the cities at prefecture level and above shows a notable spatial autocorrelation, which in every period presents a positive correlation. The spatial distribution of S&T resource allocation efficiency in neighboring cities seems to be similar in group, which tends to escalate stepwise. Meanwhile, the whole differentiation of geographical space has a diminishing tendency. (5) Viewed from LISA agglomeration map of S&T resource allocation efficiency in different periods, four agglomeration types have changed differently in spatial location and the range of spatial agglomeration. And the conti- nuity of S&T resource allocation efficiency in geographical space is gradually increasing. 展开更多
关键词 science and technology (S&T) resources cities at prefecture level and above modified Data Envelop-ment Analysis (DEA) Exploratory Spatial Data Analysis (ESDA) allocation efficiency
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Analyzing space-time evolution of rural transition in a rapidly urbanizing region:A case study of Suzhou,China 被引量:4
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作者 ZHANG Ruoyan LI Hongbo YUAN Yuan 《Journal of Geographical Sciences》 SCIE CSCD 2022年第7期1343-1356,共14页
Influenced by globalization,rural transition in developed Western countries has experienced processes of productivism,post-productivism,and multifunctional development.By contrast,rural transition in most developing c... Influenced by globalization,rural transition in developed Western countries has experienced processes of productivism,post-productivism,and multifunctional development.By contrast,rural transition in most developing countries has been accompanied by rapid urbanization,which has become a core topic in geography research.As the world’s largest developing country,China has undergone profound development since the reform and opening-up.Moreover,rural spaces in some eastern coastal areas have entered the stage of reconstruction after decades of industrialization and urbanization.This paper takes Suzhou as the case area and measures the process of rural transition from 1990 to 2015 by constructing an index system.It then analyzes the characteristics of space-time evolution using exploratory spatial data analysis(ESDA)methods to reveal the influence of economic and social development on rural transition.The results show that rural transition,which generally entails the weakening of rurality and enhancing of urbanity on a macro scale,tends to be heterogeneous across different regions on a micro scale.This paper argues that multifunctionality will be the main future trend of rural transition in rapidly urbanizing areas.The experience in Suzhou could provide an example for establishing policies on sustainable development in rural spaces and achieving urban-rural co-governance. 展开更多
关键词 rural transition multifunctionality rural revitalization SUZHOU space-time evolution exploratory spatial data analysis(ESDA)
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Dynamic evolution trend of comprehensive transportation green efficiency in China:From a spatio-temporal interaction perspective 被引量:2
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作者 MA Qifei JIA Peng +1 位作者 SUN Caizhi KUANG Haibo 《Journal of Geographical Sciences》 SCIE CSCD 2022年第3期477-498,共22页
It is urgent and important to explore the dynamic evolution in comprehensive transportation green efficiency(CTGE)in the context of green development.We constructed a social development index that reflects the social ... It is urgent and important to explore the dynamic evolution in comprehensive transportation green efficiency(CTGE)in the context of green development.We constructed a social development index that reflects the social benefits of transportation services,and incorporated it into the comprehensive transportation efficiency evaluation framework as an expected output.Based on the panel data of 30 regions in China from 2003-2018,the CTGE in China was measured using the slacks-based measure-data envelopment analysis(SBM-DEA)model.Further,the dynamic evolution trends of CTGE were determined using the spatial Markov model and exploratory spatio-temporal data analysis(ESTDA)technique from a spatio-temporal perspective.The results showed that the CTGE shows a U-shaped change trend but with an overall low level and significant regional differences.The state transition of CTGE has a strong spatial dependence,and there exists the phenomenon of“club convergence”.Neighbourhood background has a significant impact on the CTGE transition types,and the spatial spillover effect is pronounced.The CTGE has an obvious positive correlation and spatial agglomeration characteristics.The geometric characteristics of the LISA time path show that the evolution process of local spatial structure and local spatial dependence of China’s CTGE is stable,but the integration of spatial evolution is weak.The spatio-temporal transition results of LISA indicate that the CTGE has obvious transfer inertness and has certain path-dependence and spatial locking characteristics,which will become the major difficulty in improving the CTGE. 展开更多
关键词 comprehensive transportation green efficiency spatio-temporal interaction dynamic evolution trend spatial markov model exploratory spatio-temporal data analysis
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ndustrial eco-efficiency and its spatial-temporal differentiation in China 被引量:2
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作者 Wei YANG Fengjun JIN +1 位作者 Chengjin WANG Chen LV 《Frontiers of Environmental Science & Engineering》 SCIE EI CAS CSCD 2012年第4期559-568,共10页
The aim of this paper is to study the spatialtemporal differentiation of industrial eco-efficiency in China. Using methods based on the data envelopment analysis (DEA) model and exploratory spatial data analysis (E... The aim of this paper is to study the spatialtemporal differentiation of industrial eco-efficiency in China. Using methods based on the data envelopment analysis (DEA) model and exploratory spatial data analysis (ESDA) and data from 1985, 1995, 2005, and 2008 of 30 provinces in China, the spatial-temporal pattern changes in industrial eco-efficiency are discussed. The results show that: first, the patterns of industrial eco-efficiency are dominated by clustering of relatively low efficiency provinces; second, spatial relationships between the industrial eco-efficiencies of different provinces changed slightly throughout the period and the provinces persistently exhibit spatial concentration of relatively low industrial eco-efficiency; finally, there is an obvious trend in the polarization of industrial eco-efficiency, i.e., the higher level spatial units are concentrated in eastern China, and the lower level spatial units are mainly in western and central China. (ESDA) 展开更多
关键词 industrial eco-efficiency data envelopment analysis (DEA) model exploratory spatial data analysis
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