C ases perTerm (O ct.through S ept.) 0 20 40 60 80 100 120 140 160 180 200 1944 1946 1948 1950 1952 1954 1956 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 Term N um berofC ases A verage Topics perC ase perTerm (O ct.through S ept.) 0 0.5 1 1.5 2 2.5 3 3.5 1944 1946 1948 1950 1952 1954 1956 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 Term A verage N um berofTopics perC ase Entire Dataset – No Thresholding Total Nodes -- 289 (with Co- Occurrence) Range (Degree of Connectivity) – 1 to 250 Mean (Degree of Connectivity) -- 26 Median (Degree of Connectivity) -- 14 Mode (Degree of Connectivity) -- 13 Total Connections between Nodes - 3717 : Nodes are highly inter- Fisheye View of the Center of the Graph 0 50 100 150 200 250 300 0 2 4 6 8 10 12 14 16 18 N um berofNodes D egree ofC onnectivity This is an enlargement of the area around the Criminal Law node. Interestingly, the node closely clusters with a number of procedural topics (in green). While grouped in different West categories (blue = Crimes, green = Remedies), it appears that Criminal Law more closely relates to some Remedies topics than Crimes topics. This is investigated further below. Crimes Category Extracted from Network Remedies Category Extracted from Network Crimes plus Remedies Extracted from Network The graph on the left represents all Crimes and Remedies nodes with connections greater than an edge weight of three. It reveals how interconnected the node Criminal Law is with numerous procedural topics grouped in the Remedies category. In fact, there is a law school class called Criminal Procedure that covers this very intersection of topics from the two different West categories. While the West Outline of the Law with its seven categories and numerous sub- categories may be one conceptualization of the law, the co-occurrence of topics reveals that there may be better conceptualizations. A partial domain map like the graph on the left should help students reinforce their conceptual schemas of subjects like Criminal Procedure in an otherwise visually poor learning environment. Crimes Plus Remedies Edge Weight > 3 Acknowledgements: Professor Katy Börner Ketan Mane Weimao Ke Rongke Gao References: 1. Batagelj, V., & Mrvar, A. Pajek: Program Package for Large Network Analysis, University of Ljubljana, Slovenia. 1997. 2. Shneiderman, B. Tree visualization with treemaps: a 2-d space-filling approach, ACM Transactions on Graphics, vol. 11, 1 (Jan. 1992) 92-99. 3. Hochheiser, H., Shneiderman, B. Visual Specification of Queries for Finding Patterns in Time-Series Data Proceedings Discovery Science 2001, University of Maryland, Computer Science Dept. Technical Report #CS-TR-4326. UMIACS-TR-2001-25. Available at: http://www.cs.umd.edu/hcil/timesearcher/. A verage N um ber ofO pinions Issued per M onth per C ourt 0 10 20 30 40 50 January February M arch April M ay June July August Septem ber O ctober N ovem ber D ecem ber All S tone C ourt V inson C ourt W arren C ourt B urgerC ourt R ehnquistC ourt The Explosion of Civil Rights Litigation West Category by Court (Normalized by Percentage of Overall Topics Issued by that Court) Topic Frequency Over Entire Dataset Warren Court Distribution of Topics TimeSearcher revealed a spike in the topic Constitutional Law in 1982. This may be due to the new Reagan White House and a markedly more conservative Justice Department. TimeSearcher Reveals a Spike Rehnquist Court Distribution of Topics Peter A. Hook Indiana University, School of Library and Information Science 1320 E. 10th St. Bloomington, IN 74405 USA [email protected] ABOUT THE DATASET The dataset contains information about all United States Supreme Court cases that have been issued West topics from the 1944 term through the end of the 2003 term. Of the 405 topics in the West taxonomy, 290 appear in opinions issued by the court for this time period. All but one (Reference), co-occur with other topics. The data was harvested by hand from the Westlaw database--a proprietary database licensed to the students and faculty of the Indiana University School of Law for non-commercial use. The dataset was extensively cleaned and manipulated by hand. The dataset contains information about 7,868 unique cases which contain a combined total of 19,600 topics. Data Elements: • Case Name • Date of Issue • Chief Justice at Date of Issuance • Topics Assigned by West Publishing • Categories of topics (from West) • Sub-Categories of Topics (from West) Visualization Software Tools: • Pajek, Treemap, TimeSearcher The United States Supreme Court: Visualizations and Metrics (60 Years of Data) 1. To map the work of the Supreme Court based on the co-occurrence of West, top- level topics in Supreme Court cases. 2. To evaluate whether the categories and sub-categories of West’s Outline of the Law suggest the manner in which topics co- occur in cases. 3. To understand trends in the workload of the Court. 4. To compare the topics addressed by each Court. Analysis Objectives: TotalC ases N um berof M onths C ases P er M onth TotalC ases N um berof C ases P er M onth TotalC ases N um berof C ases P er M onth TotalC ases N um berof M onths C ases P er M onth TotalC ases N um berof M onths C ases P er M onth TotalC ases N um berof M onths C ases P er M onth JA N . 812 60 14 55 2 28 89 7 13 202 16 13 270 17 16 196 18 11 FEB. 695 60 12 46 2 23 91 7 13 152 16 10 238 17 14 168 18 9 MAR. 980 60 16 34 2 17 111 7 16 263 16 16 329 17 19 243 18 14 APR. 833 60 14 39 2 20 94 7 13 237 16 15 269 17 16 194 18 11 MAY 1008 60 17 25 2 13 102 7 15 289 16 18 322 17 19 270 18 15 JU N . 2162 60 36 52 2 26 162 7 23 446 16 28 846 17 50 656 18 36 JUL. 173 60 3 0 1 0 0 8 0 12 15 1 151 18 8 10 18 1 AUG. 68 60 1 0 1 0 2 8 0 15 15 1 43 18 2 8 18 0 SEP. 55 59 1 0 1 0 1 8 0 17 15 1 34 18 2 3 17 0 OCT. 125 59 2 1 1 1 4 7 1 47 16 3 45 17 3 28 18 2 NOV. 404 60 7 22 2 11 73 7 10 124 16 8 114 17 7 71 18 4 DEC. 553 60 9 27 2 14 79 7 11 180 16 11 165 17 10 102 18 6 7868 718 11 301 20 15 808 87 9 1984 189 10 2826 207 14 1949 215 9 C ases W ith W estTopics PerM onth PerC ourt BURG ER CO URT REHNQ U IS T C O URT Nov.1944 to A ug.2004 July 1941 to June 1946 July 1946 to Sept.1953 O ct.1953 to June 1969 July 1969 to Sept.1986 O ct.1986 to A ug.2004 STO NE CO URT ALL YEARS VINSO N CO URT W ARREN CO URT 1 3 2 Color Code: 1. Persons 2. Property 3. Contracts 4. Torts 5. Crimes 6. Remedies 7. Government Node Size ~ Number of times topic appears in the dataset Node Color ~ West Category Criminal Law is a catchall topic dealing with elements of crimes in general. Very few crimes co- occur together. For the ones that do (Larceny/Robbery, Robbery/Receiving Stolen Goods) it may be correctly assumed that these crimes are similar. Bigamy is one of the six Crimes topics that does not co-occur with any other Crimes topics. In the context of Supreme Court cases, Bigamy is more likely to co-occur with the non-Crimes topics of Husband and Wife and Divorce. Color Code: Crimes Remedies Node Color ~ West Category Node Size ~ Number of times topic appears in the dataset Number ~ Edge Weight (reflecting the frequency of the co- occurrence of topics)
Entire Dataset – No Thresholding Total Nodes -- 289 (with Co-Occurrence) Range (Degree of Connectivity) – 1 to 250 Mean (Degree of Connectivity) -- 26.
Jan 20, 2016
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Cases per Term (Oct. through Sept.)
0
20
40
60
80
100
120
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19
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20
00
20
02
Term
Num
ber
of C
ases
Average Topics per Case per Term (Oct. through Sept.)
0
0.5
1
1.5
2
2.5
3
3.5
19
44
19
46
19
48
19
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19
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19
54
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56
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62
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66
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68
19
70
19
72
19
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19
76
19
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80
19
82
19
84
19
86
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19
90
19
92
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98
20
00
20
02
Term
Ave
rag
e N
um
be
r o
f To
pic
s p
er
Ca
se
Entire Dataset – No Thresholding
Total Nodes -- 289 (with Co-Occurrence)Range (Degree of Connectivity) – 1 to 250 Mean (Degree of Connectivity) -- 26Median (Degree of Connectivity) -- 14Mode (Degree of Connectivity) -- 13 Total Connections between Nodes - 3717Conclusion: Nodes are highly inter-connected, pulling them to the center.
Fisheye View of the Center of the Graph
0
50
100
150
200
250
300
0 2 4 6 8 10 12 14 16 18
Number of Nodes
De
gre
e o
f C
on
ne
cti
vit
y
This is an enlargement of the area around the Criminal Law node. Interestingly, the node closely clusters with a number of procedural topics (in green). While grouped in different West categories (blue = Crimes, green = Remedies), it appears that Criminal Law more closely relates to some Remedies topics than Crimes topics. This is investigated further below.
Crimes Category Extracted from Network
Remedies Category Extracted from Network
Crimes plus Remedies Extracted from Network
The graph on the left represents all Crimes and Remedies nodes with connections greater than an edge weight of three. It reveals how interconnected the node Criminal Law is with numerous procedural topics grouped in the Remedies category. In fact, there is a law school class called Criminal Procedure that covers this very intersection of topics from the two different West categories. While the West Outline of the Law with its seven categories and numerous sub-categories may be one conceptualization of the law, the co-occurrence of topics reveals that there may be better conceptualizations. A partial domain map like the graph on the left should help students reinforce their conceptual schemas of subjects like Criminal Procedure in an otherwise visually poor learning environment.
Crimes Plus Remedies Edge Weight > 3
Acknowledgements:
Professor Katy BörnerKetan ManeWeimao KeRongke Gao
References:
1. Batagelj, V., & Mrvar, A. Pajek: Program Package for Large Network Analysis, University of Ljubljana, Slovenia. 1997.2. Shneiderman, B. Tree visualization with treemaps: a 2-d space-filling approach, ACM Transactions on Graphics, vol. 11, 1 (Jan. 1992) 92-99. 3. Hochheiser, H., Shneiderman, B. Visual Specification of Queries for Finding Patterns in Time-Series Data Proceedings Discovery Science 2001, University of Maryland, ComputerScience Dept. Technical Report #CS-TR-4326. UMIACS-TR-2001-25. Available at: http://www.cs.umd.edu/hcil/timesearcher/.
Average Number of Opinions Issued per Month per Court
0
10
20
30
40
50
January
February
March
April
May
June
July
August
September
October
November
December
All
Stone Court
Vinson Court
Warren Court
Burger Court
Rehnquist Court
The Explosion of Civil Rights Litigation
West Category by Court (Normalized by Percentage of Overall Topics Issued by that Court)
Topic Frequency Over Entire Dataset Warren Court Distribution of Topics
TimeSearcher revealed a spike in the topic Constitutional Law in 1982. This may be due to the new Reagan White House and a markedly more conservative Justice Department.
TimeSearcher Reveals a Spike
Rehnquist Court Distribution of Topics
Peter A. Hook
Indiana University, School of Library and Information Science1320 E. 10th St.Bloomington, IN 74405 [email protected]
ABOUT THE DATASETThe dataset contains information about all United States Supreme Court cases that have been issued West topics from the 1944 term through the end of the 2003 term. Of the 405 topics in the West taxonomy, 290 appear in opinions issued by the court for this time period. All but one (Reference), co-occur with other topics. The data was harvested by hand from the Westlaw database--a proprietary database licensed to the students and faculty of the Indiana University School of Law for non-commercial use. The dataset was extensively cleaned and manipulated by hand. The dataset contains information about 7,868 unique cases which contain a combined total of 19,600 topics. Data Elements:
• Case Name• Date of Issue• Chief Justice at Date of Issuance• Topics Assigned by West Publishing• Categories of topics (from West)• Sub-Categories of Topics (from West)
Visualization Software Tools:
• Pajek, Treemap, TimeSearcher
The United States Supreme Court: Visualizations and Metrics (60 Years of Data)
1. To map the work of the Supreme Court based on the co-occurrence of West, top-level topics in Supreme Court cases.
2. To evaluate whether the categories and sub-categories of West’s Outline of the Law suggest the manner in which topics co-occur in cases.
3. To understand trends in the workload of the Court.4. To compare the topics addressed by each Court.
Analysis Objectives:
Tot
al C
ases
Num
ber
of
Mon
ths
Cas
es P
er
Mo
nth
Tot
al C
ases
Num
ber
of
Cas
es P
er
Mo
nth
Tot
al C
ases
Num
ber
of
Cas
es P
er
Mo
nth
Tot
al C
ases
Num
ber
of
Mon
ths
Cas
es P
er
Mo
nth
Tot
al C
ases
Num
ber
of
Mon
ths
Cas
es P
er
Mo
nth
Tot
al C
ases
Num
ber
of
Mon
ths
Cas
es P
er
Mo
nth
JAN. 812 60 14 55 2 28 89 7 13 202 16 13 270 17 16 196 18 11FEB. 695 60 12 46 2 23 91 7 13 152 16 10 238 17 14 168 18 9MAR. 980 60 16 34 2 17 111 7 16 263 16 16 329 17 19 243 18 14APR. 833 60 14 39 2 20 94 7 13 237 16 15 269 17 16 194 18 11MAY 1008 60 17 25 2 13 102 7 15 289 16 18 322 17 19 270 18 15JUN. 2162 60 36 52 2 26 162 7 23 446 16 28 846 17 50 656 18 36JUL. 173 60 3 0 1 0 0 8 0 12 15 1 151 18 8 10 18 1AUG. 68 60 1 0 1 0 2 8 0 15 15 1 43 18 2 8 18 0SEP. 55 59 1 0 1 0 1 8 0 17 15 1 34 18 2 3 17 0OCT. 125 59 2 1 1 1 4 7 1 47 16 3 45 17 3 28 18 2NOV. 404 60 7 22 2 11 73 7 10 124 16 8 114 17 7 71 18 4DEC. 553 60 9 27 2 14 79 7 11 180 16 11 165 17 10 102 18 6
7868 718 11 301 20 15 808 87 9 1984 189 10 2826 207 14 1949 215 9
Cases With West Topics Per Month Per Court
BURGER COURT REHNQUIST COURTNov. 1944 to Aug. 2004 July 1941 to June 1946 July 1946 to Sept. 1953 Oct. 1953 to June 1969 July 1969 to Sept. 1986 Oct. 1986 to Aug. 2004
STONE COURTALL YEARS VINSON COURT WARREN COURT
1 32
Color Code:1. Persons2. Property3. Contracts4. Torts5. Crimes6. Remedies7. Government
Node Size ~ Number of times topic appears in the dataset
Node Color ~ West Category
Criminal Law is a catchall topic dealing with elements of crimes in general. Very few crimes co-occur together. For the ones that do (Larceny/Robbery, Robbery/Receiving Stolen Goods) it may be correctly assumed that these crimes are similar. Bigamy is one of the six Crimes topics that does not co-occur with any other Crimes topics. In the context of Supreme Court cases, Bigamy is more likely to co-occur with the non-Crimes topics of Husband and Wife and Divorce.
Color Code:
Crimes
Remedies
Node Color ~ West Category
Node Size ~ Number of times topic appears in the dataset
Number ~ Edge Weight (reflecting the frequency of the co-occurrence of topics)
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