Citation Analysis

Estimating Input Coefficients for Regional Input--Output Tables Using Deep Learning with Mixup
Shogo Fukui
https://arxiv.org/abs/2305.01201

Citation mentions

Cited references

Sections

8,160

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	2	8.0	0.139	0.874	100%
2	3	2	4.0	0.083	0.737	100%
3	2	2	3.0	0.056	0.644	100%
4	2	2	3.0	0.056	0.644	100%
5	1	1	1.0	0.028	0.406	100%
6	1	1	1.0	0.028	0.406	100%
7	1	1	1.0	0.028	0.406	100%
8	1	1	1.0	0.028	0.406	100%
9	1	1	1.0	0.028	0.406	100%
10	1	1	1.0	0.028	0.406	100%
11	1	1	1.0	0.028	0.406	100%
12	1	1	1.0	0.028	0.406	100%
13	1	1	1.0	0.028	0.406	100%
14	1	1	1.0	0.028	0.406	100%
15	1	1	1.0	0.028	0.406	100%
16	1	1	1.0	0.028	0.406	100%
17	1	1	1.0	0.028	0.406	100%
18	1	1	1.0	0.028	0.406	100%
19	1	1	1.0	0.028	0.406	100%
20	1	1	1.0	0.028	0.406	100%
21	1	1	2.0	0.028	0.406	100%
22	1	1	2.0	0.028	0.406	100%
23	1	1	2.0	0.028	0.406	100%
24	1	1	2.0	0.028	0.406	100%
25	1	1	2.0	0.028	0.406	100%
26	1	1	2.0	0.028	0.406	100%
27	1	1	2.0	0.028	0.406	100%
28	1	1	2.0	0.028	0.406	100%

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.