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Mapping and visualization of publication networks of public university faculty in computer science and electrical engineering

12 pagesPublished: March 9, 2020

Abstract

We present our process and development of a web-based system to explore the publication networks of faculty in California public universities in the fields of computer science and electrical engineering. Our project explores collaboration networks in the fields of computer science and electrical engineering with a focus on publication networks and an analysis of these collaborations with a focus on geospatial organization (which institutions are collaborating with which other institutions). We present our data gathering process, which relies on the Scopus[9] database (Scopus represents a “comprehensive overview of the world’s scientific research output across all disciplines”), and we present the development of a web-based tool using python and the Google Maps API [12] in order to allow visualizations and explorations of geospatial structures of the publications networks. These visualizations drove further network analysis, which we present here as well.

Keyphrases: Data Mining/Knowledge Discovery, graph theory, Human-Computer Visualization, team science

In: Gordon Lee and Ying Jin (editors). Proceedings of 35th International Conference on Computers and Their Applications, vol 69, pages 1--12

Links:
BibTeX entry
@inproceedings{CATA2020:Mapping_and_visualization_of,
  author    = {Conor Carroll and Nupur Garg and Theresa Migler and Barbara Walker and Zo\textbackslash{}"e Wood},
  title     = {Mapping and visualization of publication networks of public university faculty in computer science and electrical engineering},
  booktitle = {Proceedings of 35th International Conference on Computers and Their Applications},
  editor    = {Gordon Lee and Ying Jin},
  series    = {EPiC Series in Computing},
  volume    = {69},
  pages     = {1--12},
  year      = {2020},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {https://easychair.org/publications/paper/vvdq},
  doi       = {10.29007/dk44}}
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