Description/Abstract/Artist Statement
Title: Investigation of The Digital Footprint of Scientific Research in Social Media – Preliminary Findings
Authors: Lee Logan, Sean Baker, Dominik Soos, Jian Wu
The spread of scientific information and research beyond the confines of academic institutions plays a central role in how the public understands and trusts modern sciences. Social media has become an essential means of dissemination for scholarly news, papers, and other forms of engagement. This research aims to explore how scientific research is disseminated over social media to understand its role as a bridge between peer-reviewed research and the public's overall understanding. To support the research we created a data collection pipeline that utilizes focused web scraping to collect the metadata of research articles from mainstream digital library portals and associated news from prominent science news outlets. The scraper extracts embedded links from search engine result pages that point to the related scientific papers. After cleaning and normalizing the data, the pipeline retrieves the relevant metadata through the OpenAlex API and their appearance on Twitter (now X.com), a popular social media website for research paper dissemination. We have built a structured dataset containing the metadata of 693 peer-reviewed papers published from 1952 and 2024. This dataset provides a foundation for the analysis of the potential discrepancies of the dissemination between scientific papers and science news using a homogeneous sample. Ultimately this research hopes to contribute to the understanding of whether social media provides a more effective vehicle in boosting the dissemination of scientific discoveries, and how this boosting effect(if it exists) has been changed over time. Our preliminary findings show that the average number of tweets per paper fluctuates around 128 between 2012 and 2022, with 2021 emerging as a significant outlier. This spike suggests unusually high user engagement with scientific papers, presumably due to heightened public interest in scientific discourse during the Covid-19 pandemic. We also found that the average number of tweets/paper is in general below 100 before 2012 (with 2010 an outlier), indicating relatively low user engagement with scientific paper on Twitter during those years.
Faculty Advisor/Mentor
Jian wu
Faculty Advisor/Mentor Department
Computer science
College Affiliation
College of Sciences
Presentation Type
Poster
Disciplines
Data Science | Earth Sciences | Numerical Analysis and Scientific Computing | OS and Networks | Other Computer Sciences | Theory and Algorithms
Upload File
wf_yes
Included in
Data Science Commons, Earth Sciences Commons, Numerical Analysis and Scientific Computing Commons, OS and Networks Commons, Other Computer Sciences Commons, Theory and Algorithms Commons
36 - Investigation of The Digital Footprint of Scientific Research in Social Media – Preliminary Findings
Title: Investigation of The Digital Footprint of Scientific Research in Social Media – Preliminary Findings
Authors: Lee Logan, Sean Baker, Dominik Soos, Jian Wu
The spread of scientific information and research beyond the confines of academic institutions plays a central role in how the public understands and trusts modern sciences. Social media has become an essential means of dissemination for scholarly news, papers, and other forms of engagement. This research aims to explore how scientific research is disseminated over social media to understand its role as a bridge between peer-reviewed research and the public's overall understanding. To support the research we created a data collection pipeline that utilizes focused web scraping to collect the metadata of research articles from mainstream digital library portals and associated news from prominent science news outlets. The scraper extracts embedded links from search engine result pages that point to the related scientific papers. After cleaning and normalizing the data, the pipeline retrieves the relevant metadata through the OpenAlex API and their appearance on Twitter (now X.com), a popular social media website for research paper dissemination. We have built a structured dataset containing the metadata of 693 peer-reviewed papers published from 1952 and 2024. This dataset provides a foundation for the analysis of the potential discrepancies of the dissemination between scientific papers and science news using a homogeneous sample. Ultimately this research hopes to contribute to the understanding of whether social media provides a more effective vehicle in boosting the dissemination of scientific discoveries, and how this boosting effect(if it exists) has been changed over time. Our preliminary findings show that the average number of tweets per paper fluctuates around 128 between 2012 and 2022, with 2021 emerging as a significant outlier. This spike suggests unusually high user engagement with scientific papers, presumably due to heightened public interest in scientific discourse during the Covid-19 pandemic. We also found that the average number of tweets/paper is in general below 100 before 2012 (with 2010 an outlier), indicating relatively low user engagement with scientific paper on Twitter during those years.