Citation Analysis – Estimation of Grouped Time-Varying Network Vector Autoregression Models

Estimation of Grouped Time-Varying Network Vector Autoregression Models
Degui Li, Bin Peng, Songqiao Tang, Weibiao Wu
https://arxiv.org/abs/2303.10117

109

Citation mentions

Cited references

Sections

9,100

Words (approx)

References by Citation Intensity

Ordered by composite index (descending). Higher values indicate more intensive citation.

#	Mentions	Breadth	Sec. Wtd	Share	Composite	Main %
1	5	3	8.0	0.046	1.000	100%
2	7	5	11.0	0.064	1.000	100%
3	10	7	16.5	0.092	0.966	90%
4	11	8	16.0	0.101	0.935	82%
5	3	3	5.0	0.028	0.843	100%
6	3	2	4.0	0.028	0.737	100%
7	3	2	5.0	0.028	0.737	100%
8	3	2	5.0	0.028	0.737	100%
9	3	2	6.0	0.028	0.737	100%
10	2	2	3.0	0.018	0.644	100%
11	2	2	3.0	0.018	0.644	100%
12	2	2	3.0	0.018	0.644	100%
13	2	2	3.0	0.018	0.644	100%
14	2	2	4.0	0.018	0.644	100%
15	3	1	3.0	0.028	0.585	100%
16	3	1	6.0	0.028	0.585	100%
17	6	3	4.5	0.055	0.550	17%
18	2	1	2.0	0.018	0.511	100%
19	3	2	3.0	0.028	0.511	33%
20	1	1	1.0	0.009	0.406	100%
21	1	1	1.0	0.009	0.406	100%
22	1	1	1.0	0.009	0.406	100%
23	1	1	1.0	0.009	0.406	100%
24	1	1	1.0	0.009	0.406	100%
25	1	1	1.0	0.009	0.406	100%
26	1	1	1.0	0.009	0.406	100%
27	1	1	1.0	0.009	0.406	100%
28	1	1	1.0	0.009	0.406	100%
29	1	1	1.0	0.009	0.406	100%
30	1	1	1.0	0.009	0.406	100%
31	1	1	1.0	0.009	0.406	100%
32	1	1	1.0	0.009	0.406	100%
33	1	1	1.0	0.009	0.406	100%
34	1	1	1.0	0.009	0.406	100%
35	1	1	1.0	0.009	0.406	100%
36	1	1	1.0	0.009	0.406	100%
37	1	1	2.0	0.009	0.406	100%
38	1	1	2.0	0.009	0.406	100%
39	1	1	2.0	0.009	0.406	100%
40	1	1	2.0	0.009	0.406	100%
41	1	1	2.0	0.009	0.406	100%
42	1	1	2.0	0.009	0.406	100%
43	1	1	2.0	0.009	0.406	100%
44	1	1	2.0	0.009	0.406	100%
45	1	1	2.0	0.009	0.406	100%
46	1	1	2.0	0.009	0.406	100%
47	1	1	2.0	0.009	0.406	100%
48	1	1	2.0	0.009	0.406	100%
49	1	1	2.0	0.009	0.406	100%
50	1	1	2.0	0.009	0.406	100%
51	1	1	0.5	0.009	0.087	0%
52	1	1	0.5	0.009	0.087	0%
53	1	1	0.5	0.009	0.087	0%

Reference

Year

Mentions

Breadth

Sec. Wtd

Composite

Main %

8.0

0.046

1.000

100%

11.0

0.064

1.000

100%

16.5

0.092

0.966

90%

16.0

0.101

0.935

82%

5.0

0.028

0.843

100%

4.0

0.028

0.737

100%

5.0

0.028

0.737

100%

5.0

0.028

0.737

100%

6.0

0.028

0.737

100%

3.0

0.018

0.644

100%

3.0

0.018

0.644

100%

3.0

0.018

0.644

100%

3.0

0.018

0.644

100%

4.0

0.018

0.644

100%

3.0

0.028

0.585

100%

6.0

0.028

0.585

100%

4.5

0.055

0.550

17%

2.0

0.018

0.511

100%

3.0

0.028

0.511

33%

1.0

0.009

0.406

100%

1.0

0.009

0.406

100%

1.0

0.009

0.406

100%

1.0

0.009

0.406

100%

1.0

0.009

0.406

100%

1.0

0.009

0.406

100%

1.0

0.009

0.406

100%

1.0

0.009

0.406

100%

1.0

0.009

0.406

100%

1.0

0.009

0.406

100%

1.0

0.009

0.406

100%

1.0

0.009

0.406

100%

1.0

0.009

0.406

100%

1.0

0.009

0.406

100%

1.0

0.009

0.406

100%

1.0

0.009

0.406

100%

1.0

0.009

0.406

100%

2.0

0.009

0.406

100%

2.0

0.009

0.406

100%

2.0

0.009

0.406

100%

2.0

0.009

0.406

100%

2.0

0.009

0.406

100%

2.0

0.009

0.406

100%

2.0

0.009

0.406

100%

2.0

0.009

0.406

100%

2.0

0.009

0.406

100%

2.0

0.009

0.406

100%

2.0

0.009

0.406

100%

2.0

0.009

0.406

100%

2.0

0.009

0.406

100%

2.0

0.009

0.406

100%

0.5

0.009

0.087

0.5

0.009

0.087

0.5

0.009

0.087

Measures: Mentions = total in-text citations; Breadth = distinct sections; Sec. Wtd = section-weighted count (body ×2, lit review/appendix ×0.5); Share = mentions / total citations in paper; Composite = geometric mean of normalised count, breadth, and main-text ratio; Main % = fraction of mentions in main text (excl. appendix). (self) = self-citation.