PeopleMap: Visualization Tool for Mapping Out Researchers using Natural Language Processing

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PeopleMap visually maps out researchers based on their research interests and publications. Here, a PeopleMap user is exploring the research topics of the faculty members at the Institute of Data Engineering and Science (IDEaS) at Georgia Tech (https://poloclub.github.io/people-map/ideas/) A. Map View visualizes the embedding of researchers generated using their research topics and publication data, with each dot representing a researcher. B. Research Query allows users to search for researchers and query areas of study, allowing the user to both locate specific individuals and see the researchers most associated with a queried field in the Map View. C. Researcher View shows the detailed information (e.g., affiliation, citations, interests) of a researcher highlighted in Map View. D. Control Panel allows users to adjust the hyperparameters of the Map View visualization (e.g., show research names and cluster information).
Abstract
Discovering research expertise at institutions can be a difficult task. Manually curated university directories easily become out of date and they often lack the information necessary for understanding a researcher's interests and past work, making it harder to explore the diversity of research at an institution and identify research talents. This results in lost opportunities for both internal and external entities to discover new connections and nurture research collaboration. To solve this problem, we have developed PeopleMap, the first interactive, open-source, web-based tool that visually "maps out" researchers based on their research interests and publications by leveraging embeddings generated by natural language processing (NLP) techniques. PeopleMap provides a new engaging way for institutions to summarize their research talents and for people to discover new connections. The platform is developed with ease-of-use and sustainability in mind. Using only researchers' Google Scholar profiles as input, PeopleMap can be readily adopted by any institution using its publicly-accessible repository and detailed documentation.
Citation
PeopleMap: Visualization Tool for Mapping Out Researchers using Natural Language Processing
@article{saad-falconPeopleMapVisualizationTool2020,
  title = {{{PeopleMap}}: {{Visualization Tool}} for {{Mapping Out Researchers}} Using {{Natural Language Processing}}},
  shorttitle = {{{PeopleMap}}},
  author = {{Saad-Falcon}, Jon and Shaikh, Omar and Wang, Zijie J. and Wright, Austin P. and Richardson, Sasha and Chau, Duen Horng},
  year = {2020},
  month = jun,
  archivePrefix = {arXiv},
  eprint = {2006.06105},
  eprinttype = {arxiv},
  journal = {arXiv:2006.06105 [cs]},
  primaryClass = {cs}
}