T228 Evidence-Based Theory and Practice of Science Communication in the Geosciences: New Methods, Avenues, and Audiences
Tuesday, 24 September 2019
1:30 PM - 5:30 PM
Room 104AB, West Building
“YOU CAN'T SIT WITH US”: WHAT TOPIC MODELING CAN REVEAL ABOUT PALEONTOLOGY ON TWITTER
Paper number: T228-5
Program: Technical Sessions
Time: 2:30 PM – 2:45 PM
Authors
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Lisa LundgrenNorth Carolina State University, Raleigh, NC
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Jennifer E. BauerUniversity of Florida, Gainesville, FL
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Kent J. CrippenUniversity of Florida, Gainesville, FL
Abstract
This longitudinal study used social network analysis and text mining to better understand how people participate in paleontology on Twitter. We used Netlytic, a network extraction software application, to pull tweets from the public Twitter search API every 15 minutes over a one-year period (July 2017 – August 2018) for the social network of an NSF-funded initiative, the FOSSIL Project (NSF-DRL 1322725), which focuses on uniting, developing, and growing the paleontology community. Sampling resulted in a corpus of 7,753 connections which were subjected to social network analysis and text mining using Latent Dirichlet Allocation (LDA). Participants (n = 1,369) were classified based upon a taxonomy for how they self-identify with paleontology (Lundgren, Crippen, Bex, 2018). Topics that reached diverse members and spanned the entire network included: opportunities to contribute to paleontology regardless of status and contributions by amateurs. One example of a topic in which we saw insular conversations and minimal bridging between diverse members occurred when paleontologists communicated about women in paleontology. Our results illustrate the diversity of the paleontological community, including how certain topics and messaging strategies reach different audiences within a single niche. Topic modeling provides a strategy for describing a network’s content, which can lead to the development of approaches to increase discourse related to science.
Geological Society of America Abstracts with Programs. Vol. 51, No. 5
doi: 10.1130/abs/2019AM-340682
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