Location
Hilton Hawaiian Village, Honolulu, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
3-1-2024 12:00 AM
End Date
6-1-2024 12:00 AM
Description
Academic research conferences play a critical role in national and international scientific production. For example, the Hawaii International Conference on System Sciences is one of the longest running academic conferences in the world. HICSS consistently produces a wide range of high-quality, peer-reviewed research papers, distributed amongst 10 core tracks, and multiple minitracks. This paper provides a computational method for assessing academic research conferences by exploring the intellectual composition of the HICSS conference asking: what themes are most prevalent across the conference? Are topics identifiable? Can we predict the track of a paper from its abstract? To answer these questions, we analyze the HICSS papers from 2017-2022 (n=5,024). Applying inductive and deductive text-mining techniques, including: “Bag of Words” frequencies, NLP, unsupervised and supervised machine learning, we find several consistent themes and topics over the past five years, as well as meaningful divergence. Finally, the abstract of a paper predicts its track.
Recommended Citation
Cogburn, Derrick; Ochieng, Theodore; Buehlman Barbeau, Sierra; and Wong, Haiman, "Exploring the Intellectual Composition of Academic Research Conferences: Computational Text Analysis of the HICSS Paper Archive from 2017-2022" (2024). Hawaii International Conference on System Sciences 2024 (HICSS-57). 3.
https://aisel.aisnet.org/hicss-57/da/big_data_and_analytics/3
Exploring the Intellectual Composition of Academic Research Conferences: Computational Text Analysis of the HICSS Paper Archive from 2017-2022
Hilton Hawaiian Village, Honolulu, Hawaii
Academic research conferences play a critical role in national and international scientific production. For example, the Hawaii International Conference on System Sciences is one of the longest running academic conferences in the world. HICSS consistently produces a wide range of high-quality, peer-reviewed research papers, distributed amongst 10 core tracks, and multiple minitracks. This paper provides a computational method for assessing academic research conferences by exploring the intellectual composition of the HICSS conference asking: what themes are most prevalent across the conference? Are topics identifiable? Can we predict the track of a paper from its abstract? To answer these questions, we analyze the HICSS papers from 2017-2022 (n=5,024). Applying inductive and deductive text-mining techniques, including: “Bag of Words” frequencies, NLP, unsupervised and supervised machine learning, we find several consistent themes and topics over the past five years, as well as meaningful divergence. Finally, the abstract of a paper predicts its track.
https://aisel.aisnet.org/hicss-57/da/big_data_and_analytics/3