Citation Analysis

Evaluating Large Language Model Capabilities in Assessing Spatial Econometrics Research
Giuseppe Arbia, Luca Morandini, Vincenzo Nardelli
https://arxiv.org/abs/2506.06377
49
Citation mentions
27
Cited references
9
Sections
6,444
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 DeepSeek AI 2025 6 3 12.0 0.122 1.000 100%
2 OpenAI 2025 3 3 6.0 0.061 0.843 100%
3 Llama Team 2025 3 3 6.0 0.061 0.843 100%
4 DeepSeek AI 2025 3 3 6.0 0.061 0.843 100%
5 Anthropic 2025 3 3 6.0 0.061 0.843 100%
6 Anthropic 2025 3 3 6.0 0.061 0.843 100%
7 Arbia, G. (self) 2014 2 2 1.5 0.041 0.644 100%
8 DeepSeek API Docs 2025 2 2 4.0 0.041 0.644 100%
9 Birhane, Abeba and Kasirzadeh, Atoosa and Leslie, ... 2023 2 1 1.0 0.041 0.511 100%
10 Pataranutaporn, Pat and Needleman, Kian and Vianna... (self) 2025 2 1 1.0 0.041 0.511 100%
11 Zheng, Lianmin and Chiang, Wei-Lin and Sheng, Ying... 2023 2 1 1.0 0.041 0.511 100%
12 Hosseini, Mohammad and Horbach, Serge P. 2023 2 1 1.0 0.041 0.511 100%
13 Shin, Jinyoung and Lee, Hwanhee and Kim, Yoonjoo a... 2025 2 1 1.0 0.041 0.511 100%
14 Anselin, L. 1988 1 1 1.0 0.020 0.406 100%
15 LeSage, J. P. and Pace, R. K. 2009 1 1 1.0 0.020 0.406 100%
16 Tobler, W. R. 1970 1 1 0.5 0.020 0.406 100%
17 1995 1 1 0.5 0.020 0.406 100%
18 Zhao, Wayne Xin and Zhou, Kun and Li, Junran and T... 2023 1 1 0.5 0.020 0.406 100%
19 Liang, Weixin and Yuksekgonul, Merve and Mao, Yini... 2024 1 1 0.5 0.020 0.406 100%
20 Naddaf, Miryam 2025 1 1 0.5 0.020 0.406 100%
21 Lewis, Patrick and Perez, Ethan and Piktus, Aleksa... 2020 1 1 0.5 0.020 0.406 100%
22 OpenAI API Documentation 2025 1 1 2.0 0.020 0.406 100%
23 OpenAI 2025 1 1 2.0 0.020 0.406 100%
24 xAI Developer Docs 2025 1 1 2.0 0.020 0.406 100%
25 xAI Developer Docs 2025 1 1 2.0 0.020 0.406 100%
26 Google AI for Developers Docs 2025 1 1 2.0 0.020 0.406 100%
27 Google Blog 2025 1 1 2.0 0.020 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.