Citation Analysis

Collusion Detection with Graph Neural Networks
Lucas Gomes, Jannis Kueck, Mara Mattes, Martin Spindler, Alexey Zaytsev
https://arxiv.org/abs/2410.07091
58
Citation mentions
27
Cited references
15
Sections
10,413
Words (approx)

References by Citation Intensity

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

# Reference Year Mentions Breadth Sec. Wtd Share Composite Main %
1 12 7 15.0 0.207 1.000 100%
2 4 3 4.0 0.069 0.928 100%
3 8 2 5.0 0.138 0.874 100%
4 4 2 2.5 0.069 0.811 100%
5 3 2 2.5 0.052 0.737 100%
6 3 2 6.0 0.052 0.737 100%
7 2 2 1.5 0.034 0.644 100%
8 2 2 2.5 0.034 0.644 100%
9 2 1 2.0 0.034 0.511 100%
10 1 1 1.0 0.017 0.406 100%
11 1 1 1.0 0.017 0.406 100%
12 1 1 1.0 0.017 0.406 100%
13 1 1 0.5 0.017 0.406 100%
14 1 1 0.5 0.017 0.406 100%
15 1 1 0.5 0.017 0.406 100%
16 1 1 0.5 0.017 0.406 100%
17 1 1 0.5 0.017 0.406 100%
18 1 1 0.5 0.017 0.406 100%
19 1 1 0.5 0.017 0.406 100%
20 1 1 2.0 0.017 0.406 100%
21 1 1 2.0 0.017 0.406 100%
22 1 1 2.0 0.017 0.406 100%
23 1 1 2.0 0.017 0.406 100%
24 1 1 2.0 0.017 0.406 100%
25 1 1 2.0 0.017 0.406 100%
26 1 1 2.0 0.017 0.406 100%
27 1 1 2.0 0.017 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.