Bryan Perozzi

3.9k citations
25 papers · 855 · 1 hit paper · h-index 9

Impact in

Papers in

Bryan Perozzi

21 papers receiving 819 citations

Bryan Perozzi's Hit Papers

Statistically Significant Detection of Linguistic Change 2015 · 211 citations
2110+3+7Years since publication50100150200

Peers

Bryan Perozzi
Comparison fields: 5 of 87
  • Statistical and Nonlinear Physics 346
  • Artificial Intelligence 677
  • Cultural Studies 79
  • General Social Sciences 20
  • Computer Vision and Pattern Recognition 105
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Citations per field
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Citations per year

Countries citing papers authored by Bryan Perozzi

Since Specialization
Citations

This map shows the geographic impact of Bryan Perozzi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Bryan Perozzi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bryan Perozzi more than expected).

Fields of papers citing papers by Bryan Perozzi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bryan Perozzi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Bryan Perozzi. The network helps show where Bryan Perozzi may publish in the future.

Co-authors

The 25 scholars most cited alongside Bryan Perozzi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Bryan Perozzi Line = papers co-authored together Bryan Perozzi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Statistically Significant Detection of Linguistic Change
Hit paper breakdown →
2015211
2 2018181
3 2014143
4 201794
5 201569
6 201759
7 201820
8 201514
9 202212
10
Watch Your Step: Learning Graph Embeddings Through Attention.
20178
11 20148
12 20167
13 20207
14 20215
15 20234
16 20174
17 20113
18 20162
19 20232
20 20241

About Bryan Perozzi

Bryan Perozzi is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Computer Vision and Pattern Recognition, Information Systems and Molecular Biology, having authored 25 papers that have together received 855 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (15 papers), Complex Network Analysis Techniques (11 papers), Topic Modeling (8 papers), Natural Language Processing Techniques (4 papers), Graph Theory and Algorithms (4 papers), Advanced Clustering Algorithms Research (2 papers), Privacy-Preserving Technologies in Data (2 papers) and Recommender Systems and Techniques (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (346 citations), Artificial Intelligence (677 citations), Cultural Studies (79 citations), General Social Sciences (20 citations) and Computer Vision and Pattern Recognition (105 citations). Bryan Perozzi has collaborated with scholars based in United States, Switzerland and Italy. Frequent co-authors include Steven Skiena, Vivek Kulkarni, Rami Al‐Rfou, Haochen Chen, Leman Akoglu, Yifan Hu, Patricia Iglesias Sánchez, Emmanuel Müller, Sami Abu-El-Haija and Alexander A. Alemi. Their work appears in journals such as Information Systems, ACM Transactions on Knowledge Discovery from Data, Social Network Analysis and Mining, Proceedings of the International AAAI Conference on Web and Social Media and arXiv (Cornell University).

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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