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Principal Researchers

Deen Freelon

Deen Freelon is an Associate Professor in the UNC Hussman School of Journalism and Media. His research covers two major areas of scholarship: 1) political expression through digital media and 2) data science and computational methods for analyzing large digital datasets. He has authored or co-authored more than 30 journal articles, book chapters, and public reports, in addition to co-editing one scholarly book. He has served as principal investigator on grants from the Knight Foundation, the Spencer Foundation, and the U.S. Institute of Peace. He has extensive experience in computational methods for social science research, including text preprocessing, computational description, network analysis, machine learning, and open-source research software development. He has written research-grade software to calculate intercoder reliability for content analysis (ReCal), analyze large-scale network data from social media (TSM), and collect data from Facebook (fb_scrape_public).

@dfreelon
Homepage

Deen Freelon

Deen Freelon is an Associate Professor in the UNC Hussman School of Journalism and Media. His research covers two major areas of scholarship: 1) political expression through digital media and 2) data science and computational methods for analyzing large digital datasets. He has authored or co-authored more than 30 journal articles, book chapters, and public reports, in addition to co-editing one scholarly book. He has served as principal investigator on grants from the Knight Foundation, the Spencer Foundation, and the U.S. Institute of Peace. He has extensive experience in computational methods for social science research, including text preprocessing, computational description, network analysis, machine learning, and open-source research software development. He has written research-grade software to calculate intercoder reliability for content analysis (ReCal), analyze large-scale network data from social media (TSM), and collect data from Facebook (fb_scrape_public).

@dfreelon
Homepage

Deen Freelon

Deen Freelon is an Associate Professor in the UNC Hussman School of Journalism and Media. His research covers two major areas of scholarship: 1) political expression through digital media and 2) data science and computational methods for analyzing large digital datasets. He has authored or co-authored more than 30 journal articles, book chapters, and public reports, in addition to co-editing one scholarly book. He has served as principal investigator on grants from the Knight Foundation, the Spencer Foundation, and the U.S. Institute of Peace. He has extensive experience in computational methods for social science research, including text preprocessing, computational description, network analysis, machine learning, and open-source research software development. He has written research-grade software to calculate intercoder reliability for content analysis (ReCal), analyze large-scale network data from social media (TSM), and collect data from Facebook (fb_scrape_public).

@dfreelon
Homepage

Deen Freelon

Deen Freelon is an Associate Professor in the UNC Hussman School of Journalism and Media. His research covers two major areas of scholarship: 1) political expression through digital media and 2) data science and computational methods for analyzing large digital datasets. He has authored or co-authored more than 30 journal articles, book chapters, and public reports, in addition to co-editing one scholarly book. He has served as principal investigator on grants from the Knight Foundation, the Spencer Foundation, and the U.S. Institute of Peace. He has extensive experience in computational methods for social science research, including text preprocessing, computational description, network analysis, machine learning, and open-source research software development. He has written research-grade software to calculate intercoder reliability for content analysis (ReCal), analyze large-scale network data from social media (TSM), and collect data from Facebook (fb_scrape_public).

@dfreelon
Homepage

Deen Freelon

Deen Freelon is an Associate Professor in the UNC Hussman School of Journalism and Media. His research covers two major areas of scholarship: 1) political expression through digital media and 2) data science and computational methods for analyzing large digital datasets. He has authored or co-authored more than 30 journal articles, book chapters, and public reports, in addition to co-editing one scholarly book. He has served as principal investigator on grants from the Knight Foundation, the Spencer Foundation, and the U.S. Institute of Peace. He has extensive experience in computational methods for social science research, including text preprocessing, computational description, network analysis, machine learning, and open-source research software development. He has written research-grade software to calculate intercoder reliability for content analysis (ReCal), analyze large-scale network data from social media (TSM), and collect data from Facebook (fb_scrape_public).

@dfreelon
Homepage

Deen Freelon

Deen Freelon is an Associate Professor in the UNC Hussman School of Journalism and Media. His research covers two major areas of scholarship: 1) political expression through digital media and 2) data science and computational methods for analyzing large digital datasets. He has authored or co-authored more than 30 journal articles, book chapters, and public reports, in addition to co-editing one scholarly book. He has served as principal investigator on grants from the Knight Foundation, the Spencer Foundation, and the U.S. Institute of Peace. He has extensive experience in computational methods for social science research, including text preprocessing, computational description, network analysis, machine learning, and open-source research software development. He has written research-grade software to calculate intercoder reliability for content analysis (ReCal), analyze large-scale network data from social media (TSM), and collect data from Facebook (fb_scrape_public).

@dfreelon
Homepage