How much does inclusive local media cost?
A generalized workflow for journalism performance assessment and budget calculation.
Wil M. Dubree & Abby Qin
Democracy Fund | Comp-Comm-Coop | DeWitt Wallace Center
An ongoing project funded by the Duke University Democracy Fund and the Duke University DeWitt Wallace Center for Media and Democracy, this research grant was awarded to our team to work with Duke University researchers to improve the Journalism Ecosystem Model. Our team's was awarded $5000 to:
Build a large local news database, based on the UNC News Desert Database
Conduct a quantative analysis of a sample of local news outlets for racial representation
Conduct an in-depth analysis of exemplary news outlets to find best-practice budgeting models to generalize to the Journalism Ecosystem Model
Keywords: data scraping, diversity equity and inclusion, database management, local news
Abstract: Student news organizations, operating out of large universities, are critically understudied in media effects literature. In a study of 201 cases of sexual misconduct that occurred on U.S. university campuses, 19.4% were broken by student news outlets (Eckert et al. 2022), marking these organizations as important sources of original news reporting. Through this study, we hope to establish a groundwork for continuing inquiry into the unique agenda setting and framing effects of student news organizations in order to better understand their place in local media enviroments. Collecting online news articles from 6 student news organizations across 5 major US universities as well as tweets from those campuses, we observe a correlary relationship between student news reporting and rates of twitter conversation on topics of sexual misconduct across all 5 campuses. We also conclude that these relationships are stronger for campuses located in smaller communities. These results establish a strong link between student news reporting and online conversation and the importance of community size in local media effects. Future directions for research are discussed.
Keywords: data scraping, quantitative analysis, social media data, local news
Presentation scheduled for August 2023