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Preliminary Journal and Document Co-Citation Network Visualizations, 1903-2013

1250 Node co-citation network visualization using the latest version of CiteSpace (CiteSpace III), 1903-2013. 250 most cited sources/journals for each of the 25 year slices were chosen to build the network. Labels have been added to show significant clusters of journal categories. Color scale at the top shows relation between time slice and time period. Pink ring around node indicates centrality >= 0.10. Notice that there are no nodes or links for the first 25 years, due to lack of citations in the records.  As a result, I have changed the co-citation analysis years to 1948-2013 in later runs.

1250 Node co-citation network visualization using the latest version of CiteSpace (CiteSpace III), 1903-2013. 250 most cited sources/journals for each of the 25 year slices were chosen to build the network. Labels have been added to show significant clusters of journal categories. Color scale at the top shows relation between time slice and time period. Pink ring around node indicates centrality >= 0.10. Notice that there are no nodes or links for the first 25 years, due to lack of citations in the records. As a result, I have changed the co-citation analysis years to 1948-2013 in later runs.

Have been working on some visualizations using the very large dataset. Here are two of them, a Journal Co-Citation (JCA) Network (above), and a Document Co-citation (DCA) network (below). Enjoy!

624 node Document Co-citation (JCA) network visualization, with clusters as determined by CiteSpace.  This network is split into 12-year slices, with the top 125 most-cited documents from each slice.  Notice the large number of blue-colored clusters isolated from other clusters.  This is the visual expression of the research from 1948-1960 which was largely never follow-up upon by the disaster research community.

624 node Document Co-citation (JCA) network visualization 1948-2013, with clusters as determined by CiteSpace. This network is built upon 12-year slices, with the top 125 most-cited documents from each slice. Notice the large number of blue-colored clusters isolated from other clusters. This is the visual expression of the research from 1948-1960 which was largely never follow-up upon by the disaster research community (click for full-size).

DCA network visualization, without CiteSpace cluster labels.

DCA network visualization, without CiteSpace cluster labels (click for full size).

Preliminary 5,000 Node Term Network Visualization From 1903-2013 Dataset

Network of 5000 most frequently occurring terms in the titles and abstracts of the 1903-2013 dataset source articles.

Network of 5000 most frequently occurring terms in the titles and abstracts of the 1903-2013 dataset source articles.

Density visualization of the same term network, showing a bimodal structure.

Density visualization of the same term network, revealing a bimodal structure.

Here is a first view of a 5000 node network of most frequently occurring terms in the titles and abstracts of the large, 34,000 record dataset.  

The term network provides an aggregate glimpse into how research interests in Disaster Studies and Sciences have been structured across the 110-year period.  As is immediately apparent, a substantial volume of the research space is occupied by work on seismic hazards and earthquakes.  Additionally, a distinction can be seen between the topics more of interest to pure seismology on the far right, transitioning into topics of more interdisciplinary interest as one moves to the left.

As one continues moving towards the left, other areas of hazard study are encountered, including tsunamis, volcanology, landslides/avalanches, floods, and meteorological events.  What is also found is something of a transitional area bridging the more natural science-oriented hazards branch to the social and medical science-orientation of the human dimensions branch: pure and applied sciences and technology, including optics, GIS, remote sensing, and decision-support systems.

It is near this area (near the center left of the network) one may be quite surprised to find homeland security.  However (and this came as a surprise to me as well), there is a substantial research body in both pure and applied sciences to topics with homeland security and/or emergency management applications, such as biosensors, nuclear weapons material detectors, explosive detectors, biological warfare agent detection, robust ad hoc communication networks, and more.

The center of the human dimensions branch is represented by the “disasters” hub.  Around this hub, one can find the research concerns of the geographers, sociologists, city and urban planners, political scientists, physicians, psychiatrists, psychologists,  public health researchers, public administration scholars, and others. Some of these clusters are more well-defined than others, but all broadly focus on disasters as human events.

For those who would like to more closely explore the network visualization, you can download VOS Viewer here: http://www.vosviewer.com/download/.  You will need to download the map file (https://docs.google.com/file/d/0B7GBghcJr6aJaDc2TDF6NUFMaDg/edit?usp=sharing)  and network file (https://docs.google.com/file/d/0B7GBghcJr6aJM002cmtaSU5GcGc/edit?usp=sharing) OR the normalized network file (https://docs.google.com/file/d/0B7GBghcJr6aJRjRtQTRrR0lHTm8/edit?usp=sharing).

These files can then be used in VOS Viewer to generate and explore the network visualization in detail.

First Look: 34,000+ Disaster-Related Bibliometric Records Speak

This shows the distribution of journal titles containing articles in the current dataset of approximately 33,000 records, 1903-2013.

This shows the distribution of journal titles containing articles in the current dataset of approximately 34,000 records, 1903-2013.

This image shows areas where the density of publications is highest, and some of the journals that correspond to those areas.

This image shows areas where the density of publications is highest, and some of the journals that correspond to those areas.

Any reports of my demise have been greatly exaggerated….

The past 6-8 weeks have been both hectic and productive….turned 45 years old…..my family finally placed the ashes of my stepfather in their permanent resting place…..upgraded my internet and satellite tv……bought a new car….I am getting all of my teeth replaced in a few days….and I have built and am currently refining a dataset of over 34,000 un-duplicated, raw,  Web of Science records related to disasters (mostly), 1903- May 2013.

This is not as easy as it may sound.  The dataset combines all of my previous WoS searches with the results of many new results pulled from WoS during August, including contents of the Bulletin of the Seismological Society of America 1950-2013 (6,000 or so articles) .  The entire dataset was fed into both EndNote and CiteSpace to remove any duplicates, and to verify the number of records. The precise total number of records, if you wish to know, is 34, 553.  

This number will likely decrease somewhat in the future, as I have not yet started in earnest weeding out results that are not of at least minimal relevance to the study of disasters and hazards.

There are two dataset versions: 1) a raw dataset that except for some capitalization differences in some records that are the result of my decision early in my thesis work to make those records all uppercase, has not been edited; and 2) a standardized dataset that will, as best as possible, correct variations in author and source spellings that are widespread in WoS records.  

The standardized version is an ongoing, tedious, literally unending process that can only approach, but never reach, perfection.  At the present time I have standardized approximately 800 of the top 1200 Authors of the articles in the dataset.  This small task took approximately two weeks. Unfortunately for some names, particularly the Chinese and Taiwanese authors,  this appears nearly impossible using only surnames and initials.  Many of these authors share names and initials.  It may be necessary in some cases to use full names to distinguish between different authors.  I think I will tackle this issue at a later date.

My plan is to eventually standardize most of the top 3000 authors.  I will then move on to the authors of the cited references, then the sources in those references. This may well take up the remainder of the year.

From the dataset, here is the bibliographic coupling network of the 1200 most frequent authors of the 34,553 articles in the dataset using VOS Viewer…some clear clusters appear to emerge:

Bibliographic Coupling of Authors in the Dataset Using VOS Viewer.

Bibliographic Coupling of Authors in the Dataset Using VOS Viewer.

Density view of the network.

Density view of the network.

Here is the Bibliographic Coupling Network of Journals in the dataset:

BibSources1 Panorama

BibSourceDensity

I am making both datasets publicly available. The raw, unedited dataset and the most recent Standardized dataset are both contained in a folder that can be accessed using this Google Drive link: https://drive.google.com/folderview?id=0B7GBghcJr6aJM3NUOUJwWXFKZGs&usp=sharing .  I also intend to make an EndNote file available in the near future.

I will be posting more network images soon.  Also, please note my primary contact email has now changed to joseph.martin3@att.net.  You can still also reach me at jmartiniii1968@yahoo.com.

The Structure of Science Part II: Gaining Perspective on Disaster Studies Using Overlay Mapping

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The Fishbowl of Science: Loet Leydesdorff et al.’s (2013) journal-level base map of science, using 2011 citing patterns of 10, 675 Web of Science-indexed journals. If you are looking for your favorite disaster-related journal, many of them are in this map…you just have to zoom in a lot more to see them…most are but specks in relation to the entire journal structure of science. Hopefully this fact will not come as too much of a shock to anyone (“I don’t understand….I thought everyone reads Biosecurity and Bioterrorism!!!!”….)
You can play with this in a shared VOS Viewer map yourself:  http://www.vosviewer.com/vosviewer.php?map=http://www.leydesdorff.net/journals11/citing_all.txt.

Here is Leydesdorff et al.'s map of science based on the pattern of being cited. You can also explore this map yourself: http://www.vosviewer.com/vosviewer.php?map=http://www.leydesdorff.net/journals11/cited_all.txt

Here is Leydesdorff et al.’s base map of science this time based on the pattern of journals being cited by other journals in 2011. There is a slight difference between the journals another journal cites, and the journals that cite it.  According to Leydesdorff, the citing pattern shows the most current activity of science.  The cited map shows the established knowledge base of science as contained in the journals.
You can also explore this map yourself:
http://www.vosviewer.com/vosviewer.php?map=http://www.leydesdorff.net/journals11/cited_all.txt

Cited map of science, but this time shown in VOS Viewer as a density map.  This shows which areas of science are most actively cited to.

Cited base map of science, but this time shown in VOS Viewer as a density map. This shows the areas most actively cited by other journals.

If you search for WoS indexed articles with "Disaster" in topic or title, 1980-2011 and then map all of the journals cited in the results (approximately 5000 records), this is what you get...

If you search for WoS indexed articles and conference papers with “disaster” in topic or title fields, 1980-2011, and then overlay all of the journals cited in those articles (approximately 4500 unedited records) over the citing base map, this is what you get.  Even though some of these journals and the source articles they were cited in are likely not related to Disaster Studies and Sciences, it still shows the cross-disciplinary nature of disaster research.

Source journals in WoS-indexed articles on disaster recovery as an overlay on the base citing map.

Source journals in WoS-indexed articles on disaster recovery as an overlay on the base citing map. This shows the journals where disaster recovery articles came from, as well as their position within the overall structure of science. Notice the variety of disciplinary areas involved.

As you may recall in my last post, I have just discovered overlay mapping and its use in mapping knowledge domains.  I am reading and digesting several papers written by several prominent scholars, including Loet Leydesdorff, Ismael Rafols, Chaomei Chen, and Alan Porter. 

To refresh your memory: in overlay mapping, data is superimposed upon an existing base map.  In this case, the base maps are of science, as represented in the journal-to-journal citing and cited by patterns among the journals indexed in Web of Science. The overlay data can consist of the WoS-indexed articles published by specific authors, group of authors, institutions, specialties, fields, disciplines, etc., within a particular time period.  You can also choose to create an overlay based on the source article data, or the cited references within those articles.

The method of overlay mapping, thus allows comparison between the data and the base map, and between different overlay maps (though according to Leydesdorff there are limits to the types of between-map quantitative comparisons that can be made if using VOS Viewer to visualize the data…will not bother you with the exact details but just know that because a journal node in one map is twice as big as the same journal node on a different map (provided the viewing settings are the same for both maps), it does not mean one node is two times more frequent….it only means the node is more frequent).

On this page of his website, Leydesdorff has instructions and programs that will convert WoS data into overlay maps, as well as links to PDF versions of papers on overlay mapping.  The programs are fairly easy to use, and one can create a large number of different maps that can be viewed in VOS Viewer in a relatively short amount of time.  CiteSpace can also be used, according to some of Chen’s most recent documentation on CiteSpace, but I am only beginning to investigate that process.

So let us see a few more examples of the nifty things you can do with the overlays:

Updated thesis data as overlay against citing base map.

Here are the cited journals in my updated thesis data as an overlay on the citing base map…..I believe it would be correct to say many different disciplines are represented.

Density view of the same map, show greatest intensities over what I identify as our field's Hazard Sciences Branch, and our Human Dimensions Branch.

Density view of the same map, show greatest intensities over what I identify as our field’s Hazard Sciences Branch, and our Human Dimensions Branch.

Some of the journals within the Hazard Sciences area.

Some of the journals within the Hazard Sciences area.

View of journals in and near what I believe is the central core of the Human Dimensions area.

View of journals in and near what I believe is the central core of the Human Dimensions area.

JCA750-2

Journal co-citation network of the same data. Notice that the same general organization and relationship of journals cited can be seen that are seen in the overlay maps.

Neat, eh?  Now let’s take a look at using the method to see what is revealed about different journals and different authors in the world of disasters:

Overlay of  journals cited in Journal of Homeland Security and Emergency Management articles, 2006-2011.

Overlay of WoS-indexed journals cited in Journal of Homeland Security and Emergency Management articles, 2006-2011.

Cited journal overlay, but this time using Disaster Prevention and Management, 2009-2011.

Cited journal overlay, but this time using Disaster Prevention and Management, 2009-2011. Very similar to JHSEM, but important distinctions are noticeable.

Overlay of selection of WoS-indexed journals containing articles by Waugh, placed on the cited base map.

Overlay of WoS-indexed journals containing articles by Waugh (author or co-author), placed on the cited base map.

Same map as above, but this time showing WoS-indexed journals that have published articles by Cutter.  Whose work appears to cross more disciplinary lines-Waugh or Cutter? Both the map and a statistical measure of interdisciplinarity (Spirling-Rao) say hands-down it is Cutter.

Same map as above, but this time showing WoS-indexed journals that have published articles by Cutter. Whose work appears to cross more disciplinary lines-Waugh or Cutter? Both maps and measure of interdisciplinarity (Rao-Stirling diversity) say hands-down it is Cutter.

There are limitations to these overlays, of which the main one is that these maps will only show journals that are indexed in WoS.  So for example, articles published in the Australian Journal of EM or the International Journal of EM, or citations to these journals in WoS-indexed articles, do not appear on the base map or overlays. Despite this fact, the technique appears to offer another way to view the field, one that is complimentary to the results produced by co-citation  analysis.

The Structure of Science Part I: A Most Curious Resemblance

A map of science based on the 2011 revised Web of Science categories in Leydesdorff, Carley, and Rafols (2013 in press) paper.....

Map of science based on the 2011 revised Web of Science categories in Leydesdorff, Carley, and Rafols (2013 in press) paper…..

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Here is Leydesdorff,  Rafols, and Chen’s updated 2013 journal-level map of science based on citing patterns among 10,675 journals indexed in Web of Science, as visualized in VOS Viewer.  This map can be accessed at http://www.leydesdorff.net/journals11/. Does the structure of these networks look familiar to anyone?

I was originally planning to write about some interesting work being done by several information science researchers, including Loet Leydesdorff, Ismael Rafols, Chaomei Chen, and Alan Porter. 

Their work improves on earlier work by Vargas-Quesada, De-Moya-Anegón, Chinchilla-Rodríguez, and González-Molina (2006), as well as others, to map the entire intellectual domain of science.   The recent work involves creating overlays that can be combined with base structural maps of science derived from citation patterns within Web of Science-indexed journals.  The overlays allow the output of a particular author, journal, institution, or field, to be visualized within the entire domain of science.   These base maps, one of which is shown above, might help provide secondary confirmation of the structures I have found in my co-citation networks.

So, I was preparing images of the base maps and marking where different disaster-related journals referenced in my networks were located within.  Then I noticed something.  I had seen the structure of the base map before.

With my original background in neuropsychology, I have spent a lot of time looking at images of the human brain (and in one undergraduate course was tested on neuroanatomy using actual human brain sections the instructor kept in a large glass jar of formaldehyde in his office…..).  The structure of science looks remarkably similar to a cerebral hemisphere seen from the side (lateral view).  Even the way the major disciplines cluster along the outside of the network, with the curve creating an interior space, is similar to the curve of the temporal lobe and the relationship between gray and white matter:

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Right cerebral hemisphere of the human brain. See a similarity between this and the network of science?

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Sagittal section through the right cerebral hemisphere showing the brains thin outer neocortex (gray matter) and the immense number of axon bundles below the neocortex (white matter) that connect these neurons to others throughout the brain and nervous system.

The resemblance was so peculiar that I emailed Dr.  Leydesdorff, who is in Amsterdam, to ask if anyone had noticed the similarity before.  He actually replied back rather quickly that he had not noticed it before but that yes, the similarity was striking. Whether there is any significance to the similarity, he could not say one way or another.  I can only speculate that if the structural similarity can not be shown to be coincidental or arbitrary, then it suggests there is something necessary about that structure that makes it desirable to have, for both brains and scientific knowledge domains.  But the idea that the structure of knowledge somehow echoes the structure of our own brain is a very odd idea indeed!

Here are some additional images of neural pathways and networks that have been produced by the Human Connectome Project, which seeks to completely map all of the brain’s neural pathways and connections–a definitive wiring diagram for the human brain.

Perhaps someone else sees the similarity I do between these images and the network of science…..

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Connectome (1)

Looking again at the right cerebral hemisphere. This Human Connectome Project image shows major neural pathways that connect the brainstem and midbrain (long bluish and purplish vertical fibers) to the pontine & cerebellar areas (yellow and orangish fibers that wrap around the base to the lower left), and cerebral cortex and neocortex (multicolored fibers that fan out from both the upper brainstem pathway and from around the red-ringed elliptical space, which marks the location of the thalamus and hypothalamus). Frontal lobe would be to the right, and occipital lobe to the left.

In Part II,  I will return to my original intention of discussing the base maps of science in relation to my own attempts to map the structure of Disaster Studies and Sciences.

Document Co-Citation Analysis 1995-2013: 2004

The 100 most cited references in 2004 have formed into a larger number of structures than the previous year.  The modularity is also too low for CiteSpace to identify individual clusters.

The 100 most cited references in 2004 have formed into a larger number of structures (7) as well as clusters (11) than the previous year. 

2004 Clusters

Here is 2004, but this time visualized differently, with the nodes colored according to cluster membership.

Having thoroughly depressed myself in the last post by pondering one of many possible unpleasant futures awaiting humanity (and that does not even include possibilities such as the “technological singularity” some futurists have hypothesized may be approaching, perhaps as early as mid-century, beyond which future human history becomes impossible to predict) , let us return to the year-by-year document co-citation analysis of my modified thesis dataset.

We now arrive at 2004.  

Compared to the previous year, this year is somewhat more fragmented, with a larger number of individual structures visible, as well as a greater number of clusters.  We do however, see a broad mix of hazard science and the human dimensions of disaster, including a structure that includes a social science and hazard  science cluster linked together (Cluster 7 and Cluster 8).  The two largest clusters this year are the humanitarianism/development cluster (Cluster 9) and the landslide/susceptibility cluster (Cluster 6).  Some of the significant works cited this year include those by Guzzetti, the Sphere Project, Peacock, and McCarthy’s contribution to the IPCC 2001 climate change report.

Cluster Summary:

Cluster Summarization

Network Summary, Organized by Cluster Membership:

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Network Narrative: 

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Citation Burst Information:

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Document Co-Citation Analysis 1995-2013: 2003

2003 DCA

DCA 2003, 100 Most Cited

The 2003 visualization is notable for a couple of reasons.  First, the visualization is dominated by a single,  multi-cluster, multi-disciplinary, structure.  This structure contains 6 of the 9 total clusters, and 87 of the 100 most cited references for 2003.

The left, less dense,  side of the structure contains 5 clusters: Cluster #7 (emergencies; systems; humanitarian) includes four works related to complex emergencies and humanitarianism that have consistently appeared in previous years; Cluster #6 (emergency; preparedness) includes key works by Mileti, Tierney, and Drabek.  Cluster #5 (vulnerability; impact; hazard; flood) includes the IPCC 2001 Summary for Policy Makers, Ian Davis’ 1978 work on disaster shelter, and Etkins’ 1999 article on risk transference; Cluster #4, (which includes the IPCC 2001 scientific report, Pielke and Landsea’s 1998  work on normalized hurricane damage, and Changnon et al.’s 2001 paper on losses from extreme weather events) pertains to the possible meteorological impacts of climate change.  Cluster #2 is the largest, with 44 members.  it is also the most heterogeneous of the clusters, making it difficult to classify with a single label.  Works in this cluster include: Cannon’s vulnerability analysis contribution to 1994’s Disasters, Development, and Environment; White’s 1974 Natural Hazards;  and Kunkel et al.’s 1999 paper on extreme precipitation trends.  The cluster boundaries encompass Granger et al.’s 1999 multi-hazard risk assessment of Cairnes, Australia; Fell’s 1997 book on landslide risk assessment; and extend across the right side of the structure to include several other works on landslide hazards.

The remainder of nodes on the right side of the structure belong to Cluster #3 (maps; susceptibility), the second largest cluster with 28 members.  Works in the cluster pertain to remote sensing/GIS applications and landslide hazards,   including Varnes’ 1984  work on landslide hazard zonation.

Two of the remaining three small clusters (#0 and #1) pertain to seismic hazards.  The final cluster (#8) relates to tsunamis.

What also makes the 2003 network notable is the large number of high centrality nodes (nodes with pink rings). Eleven nodes have centrality values equal to, or greater than 0.10.   This is by far the greatest number of high centrality nodes to appear so far.  These nodes, whether they are cited frequently or infrequently, usually serve as “gateways” between clusters or different parts of the network.   Nodes with both high citation frequency  and high centrality (such as the works by Mileti, Hewitt, Chambers, Granger, Fell, White, Brabb, and Varnes) are, in keeping with Chen’s purpose in developing CiteSpace, candidates as possible turning points in a knowledge domain.  This is especially the case if examination of the merged network (which includes all of the individual time slices) shows the node is a link between different time periods.  In some studies using CiteSpace, such as examining research on dinosaur extinction, Chen would confirm these turning points by sending questions about the importance of particular works to key authors identified in the network.  This works well for scientific research domains within a single discipline, where theories and schools of thought are more clearly delineated, and more linear, than they may be in an evolving, multi-disciplinary knowledge domain.

Cluster Summary:

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Network Summary, Organized by Cluster Membership:

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Network Narrative: 

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Citation Burst Information:

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Document Co-Citation Analysis 1995-2013: 2002

DCA 2002

DCA 2002, 100 Most Cited

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DCA 2002: Timeline View

The 100 most cited documents in the dataset for 2002 form thirteen clusters.   This year sees Mileti’s Disasters by Design occupy the spotlight as the primary landmark node in the network.  Co-citation links are found between it,  At Risk, and Hewitt’s Regions of Risk, among others.  Included in this co-citation cluster (#11-drought) is also a 1991 paper by DE Alexander on use of information  technology for real-time disaster monitoring.  The works in this cluster were cited in a variety of contexts, as evidenced by the cluster summary.  Other possible labels for this cluster include: community resilience; vulnerability; evacuation; impact; health; volcanic hazards; and others.

Additional social science clusters can also be found.  These include clusters related to seed relief/seed security (#2 diversity); and a small humanitarianism cluster (#5- humanitarian).

Another social science article of note is one not linked by co-citation to any other paper in 2002’s 100 most cited.  It is a member of a small cluster (#10-earthquake/community preparedness) that includes DE Alexander’s 2000 paper in Disaster Prevention and Management on use of scenarios for teaching emergency management; and JI Abrams 1993 paper on earthquake prehospital mortality patterns.  The article is Wise’s December 2002 “Organizing for Homeland Security”. This makes it the first post 911-related paper to appear among the 100 (although it was published in Dec 2002, it was cited in articles by Waugh and Kirlin in the same issue of Public Administration Review ).  It also may mark the entry of Public Administration as a significant disciplinary input into the disaster literature.  This is not to say that PA was not involved previously, only that its participation and importance will become more pronounced from this point forward.

Within hazards research, there are two structures of note.  The first is a well-formed structure of four, linked clusters (#6, 7, 8, 9), related to seismic hazards.  This contains works by Papazachos, Kanamori, Cornell, Tselentis, Tinti, and others.  Cluster 6 was cited in relation to  the 1999 Athens earthquake.  Cluster 7 was cited in relation to tsunamis and the Cascadia subduction zone.  Cluster 8 relates to seismic hazard assessment in general.  Cluster 9 pertains to seismic assessment of Lake Nasser and proposed Kalabsha Dam in Egypt.

The second is a well-formed hazard cluster pertaining to avalanches, snow avalanches, and avalanche forecasting (#3- large).

Cluster Summary:

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Network Narrative: 

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Citation Burst Information:

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Document Co-Citation Analysis 1995-2013: 2001

DCA 2001 Panorama

DCA 2001, 100 Most Cited

The 100 most cited documents in the dataset for 2001 are organized into eleven identifiable clusters.   This year, the work of two geographers, Hewitt’s Regions of Risk,  and Alexander’s  Confronting Catastrophe, take center stage.  Both belong  to a multi-disciplinary “vulnerability” cluster (#5) that also includes At Risk, and Hoffman and Oliver-Smith’s The Angry Earth.  This cluster is linked to what should by now be becoming a familiar cluster of documents: the conflict/humanitarian/chronic emergencies cluster (#4-“context”).  There is also a secondary un-linked “emergencies” cluster related to child refugee health and nutrition deficiencies.

Other important cited references standing out in 2001 are Newhall et al.’s 1982 paper introducing the Volcanic Explosivity Index (VEI); Hanks and Kanamori’s 1979 Moment Magnitude Scale paper.  These are part of a three-cluster structure (#2, #7, #8) cited in relation to tsunami hazards, which also includes Bryant et al.’s 1996 paper on tsunamis’ role in coastal evolution.  There is a fairly dense cluster (#6- system) connecting papers on expert systems to assessment of landslide hazards.  Climate change issues are also beginning to enter the top 100 (#8- climate).

Absent from the network are any references connected to the 9-11 terrorist attacks.  This is to be expected.  Due to the nature of academic publication,  there is a lag between actual events and publication of journal articles related to those events.  From previous year’s results, this lag time can be roughly estimated at a minimum of 1-2 years (this is roughly estimated by looking at the difference between papers’ year of publication and the year of first appearance in the network) .  We might expect to see some influence of 9-11 in 2002’s most cited references, but is more likely to be seen in 2003 and beyond.

Cluster summary:

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Network Narrative: 

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Citation Burst Information:

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Document Co-Citation Analysis 1995-2013: 2000

DCA 2000, 100 Most Cited: Wide-Angel View

DCA 2000, 100 Most Cited: Wide-Angel View

DCA-2000-100

DCA 2000: 100 Most Cited (click to enlarge)

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DCA 2000, 100 Most Cited: CiteSpace “Timezone” view that allows view of cited references grouped by year of reference.

In 2000, the 100 most cited divide into 16 clusters of varying sizes.  Works by Sen, Wells, Ambraseys, Putnam, Alexander, and Noji are among the prominent features of the 100 most cited of 2000.  The largest social science structure consists of two linked clusters  covering international development, conflict, aid, and humanitarianism.  At Risk continues again makes an appearance, but in 2000 is part of a small cluster (#10- vulnerability) connecting vulnerability and poverty.   Noji’s 1997 and Alexander’s 1996 articles are linked together in a multi-disciplinary  (sociology, public health, and geography) cluster covering disaster health effects.  Natural hazard research continues strong, with Wells and Coppersmith’s 1994 article on new empirical relationships  to estimate maximum earthquake magnitudes anchoring a large two-cluster structure linking seismic and tsunami hazard papers.

Cluster summary:

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Network Narrative: 

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Citation Burst Information:

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