presentation

AGE-DECAYING H-INDEX FOR SOCIAL NETWORKS OF CITATIONS

Presentation by:

Apostolos Papadopoulos

D. Katsaros

, A. Sidiropoulos

, Y. Manolopoulos

1

Dept. of Computer & Communication Engineering University of Thessaly, Volos, Greece

2

Dept. of Informatics

Aristotle University, Thessaloniki, Greece

Methods for Ranking Scientists

z Evaluation of scientists by “experts”

–

e.g., surveys

z Citation Analysis

–

Task: Compute a score for the “objects”

z Hybrid method of previous two

Drawbacks of various scientists ranking methods

z Not measure the importance of papers

z Affected by “big hits”

z Not measure productivity

z Need to set administrative parameters

H-index

z Published by J.E. Hirsch in Oct. 2005

z Was known at least two years earlier

z Definition:

A researcher has h-index h if

–

h of his N

articles have received at least h citations each

–

the rest N

-h articles have received no more than

h citations each

H-index

z Calculates the broadness of a researcher

9

Productivity

9

Impact

9

Not affected by “big hits”

9

Not affected by “noise”

Index a

z N

≥h

z Definition:

A researcher has index a if N

=ah

z Second metric-index

H-index drawbacks

z It is a growing function over time

z Does not show scientist’s inactivity or retirement

z Scientists with short scientific life are out of

competition

Contemporary H-index

z

Definition

:

A researcher has contemporary h-index h

if

– h^c

of his N

articles have S

(i)≥h

–

the rest N

-h

articles have S

(i)≤h

– S^c(i)=

γ

–

In our experiments: γ=4 and δ=1

z

An old article gradually loses its “value”

z

Show how “active” a researcher is

Trend H-index

z

Definition

: A researcher has trend h-index h

if

– h^t

of his N

articles have S

(i)≥h

–

the rest N

-h

articles have S

(i)≤h

–

In our experiments: γ=4 and δ=1

z

An old citation gradually loses its “value”

z

Shows how “trend” the work of a researcher is

δ

−

∈

∀

+

−

= ^{γ *} ∑ ^{( Y ( now ) Y ( i ) 1 )}

(i) S

C(i) x t

Age Decaying H-index

z

Definition:

A researcher has Age Decaying h-index h

if

– h^ad

of his N

articles have S

(i)≥h

–

the rest N

-h

articles have S

(i)≤h

–

In our experiments: γ=4 and δ

=δ

=1

z

An old article gradually loses its “value”

2

1

* ( ( ) ( ) 1 )

) 1 )

( )

( (

2

*

∈

∀

−

− +

+

−

= ^{γ Y now Y i} ∑ ^{Y now Y i}

(i) S

C(i) x

ad

The second metric “a” of h-index

z

A factor a is defined as:

– N_c,tot=ah²

z

For h-index generalizations, instead of N

we use the sum of each paper score S

(i):

2 ad ad

P i

ad

(i) a h

S =

∑

∀

H-index generalizations

z Contemporary

z Trend

z Age Decaying

–

Scientists, journals, conferences or any other kind

of semantic grouping of articles

Experiments

z DBLP collection (http://dblp.uni-trier.de/)

–

Data timestamp: March 2006

z DBLP includes data for authors, journals and conferences

z Focuses in the DB area

z “Names Problem” is solved

Experiments – h-index

130 913

2.81 18

8.Umeshwar Dayal

154 994

3.06 18

7.Rakesh Agrawal

93 1024

3.16 18

6.Catriel Beeri

143 1071

2.96 19

5.Won Kim

124 1359

3.39 20

4.Philip A. Bernstein

150 1896

3.91 22

3.David J. DeWitt

227 1783

3.37 23

2.Jeffrey D. Ullman

193 2180

3.78 24

1.Michael Stonebraker

Np

Nc,tot

a h

Name

Experiments – Age Decaying h-index

1 1

3 3.41

14 7.David J. DeWitt

2 2

2 4.18

14 6.Jeffrey D. Ullman

13 21

69 2.85

15 5.Alon Y. Levy

25 22

100 2.79

16 4.Dan Suciu

6 5

13 3.08

16 3.Serge Abiteboul

5 6

23 3.19

16 2.Jennifer Widom

4 4

7 3.28

16 1.Rakesh Agrawal

Pos by h_t Pos

by h_c Pos

by h a_ad

h_ad Name

Experiments – h-index for scientists

Experiments – h-index for scientists

Experiments – h-index for scientists

Experiments – H-index for conferences

42 412

2.86 12

8.adbt

101 527

3.65 12

7.eds

434 658

3.89 13

6.edbt

1338 1486

5.80 16

5.er

1970 3307

6.83 22

4.icde

776 3883

5.74 26

3.pods

2192 9729

7.10 37

2.vldb

2059 12261

6.05 45

1.sigmod

N_p N_c,tot

a h Name

3 163

31 2.69

9 8.webdb

13 434

658 3.92

11 7.edbt

6 1074

243 4.08

11 6.kdd

11 313

580 5.27

12 5.icdt

22 1970

3307 8.01

17 4.icde

26 776

3883 5.32

20 3.pods

37 2192

9729 6.94

25 2.vldb

45 2059

12261 5.85

32 1.sigmod

N_p h

N_c,tot a_c

h_ad Name

Experiments – H-index for conferences

Experiments – H-index for conferences

Experiments – H-index for journals

4939 388

6.06 8

8.ipl

281 408

5.03 9

7.vldb

877 863

7.13 11

6.debu

378 740

4.37 13

5.tois

1349 1142

5.07 15

4.sigmod

934 1208

4.71 16

3.is

1388 1520

4.69 18

2.tkde

598 9329

3.88 49

1.tods

N_p N_c,tot

a h Name

6 318

156 5.67

6 8.jiis

16 934 1208

7.51 6

7.is

6 238

189 3.82

7 6.dpd

9 281

408 2.82

12 5.vldb

11 877 863

3.49 12

4.debu

18 1388

1520 5.77

12 3.tkde

15 1349

1142 4.94

13 2.sigmod

49 598 9329

7.71 13

1.tods

h N_p

N_c,tot a_ad

h_ad Name

Experiments – H-index for journals

Conclusion

z

Evaluation of scientists based on citation analysis

z

Evaluation of publication forums based on citation analysis

z

H-index shortcomings:

–

Active – inactive scientists

–

Significant works in the past – not any more significant

H-index generalizations on the time dimension

AGE DECAYING H-INDEX FOR SOCIAL NETWORKS OF CITATIONS

Thank you for your attention!

D. Katsaros, A. Sidiropoulos, Y. Manolopoulos

Presenter: Apostolos Papadopoulos