Latest research

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My research gets at the problem of disinformation and a chaotic news eco system by asking: How will audiences respond to credibility indicators used at scale? In other words, when journalists or tech platforms implement top-down solutions to encourage choosing credible news, will audiences listen? I have a few projects in the works to examine the effectiveness of crowdsourcing and several published pieces about credibility labels.

I think it’s important to go past simple perceptions of credibility and measure the ways audiences engage with news they find credible or not. Because of that, I have completed several studies measuring commenting behaviors of audiences.

Find my most recently published work here:

Duncan, M., Perryman, M., & Shaughnessy, B. (2021). “Same scandal, different standards: The effect of partisanship on expectations of news reports about whistleblowers.” Online first from Mass Communication & Society. doi:

Duncan, M. (2020). What’s in a label? Negative credibility labels in partisan news. Online first at Journalism and Mass Communication Quarterly. DOI:

Duncan, M., & Culver, K. (2020). Technologies, Ethics and Journalism’s Relationship with the Public. Media and Communication, 8(3), 101-111. doi:

Duncan, M., Pelled, A., Wise, D., Gosh, S., Shan, Y., Zheng, M., & McLeod, D. (2020). “Staying silent and speaking out in online comments sections: The influence of spiral of silence and corrective action in reaction to news.” Computers in Human Behavior 102, 192-205. DOI: 10.1016/j.chb.2019.08.026

 Duncan, M. & Coppini, D. (2019). “Party v. The People: Testing corrective action and supportive engagement in a partisan political context.” Journal of Information Technology and Politics. 16(3), 265-289. DOI: 10.1080/19331681.2019.1644266.

 Duncan, M. (2019). “The effectiveness of credibility indicator interventions in a partisan context.” Newspaper Research Journal. 40(4), 487-503. DOI: 10.1177/0739532919873707.

 Duncan, M., Culver, K. B., McLeod, D., & Kremmer, C. (2019). Don’t Quote me: Effects of Named, Quoted, and Partisan News Sources. Journalism Practice. 13(9), 1128-1146. DOI: 10.1080/17512786.2019.1588148.

I am an assistant professor in the School of Communication at Virginia Tech.

Within a media effects tradition, I research how audiences are adapting to emerging forms of journalism. I’m particularly interested in ways to help the audience navigate partisan news and news about partisan issues. My research has been accepted at Computers in Human Behavior, Newspaper Research Journal, Journal of Information Technology and Politics, and Journalism Practice.

My professional background is print and multimedia journalism. I spent five years as a daily newspaper reporter, and additionally I worked on multiple multimedia journalism special projects. Find writing samples and more details here.

I bring that experience to the classroom. My teaching experience includes 10 semesters working with students on media writing and storytelling skills. I have experience of teaching my own course, as well. Additionally, I co-created a data journalism/ visualization class here, and co-authored the e-text now used by students here.

I’m very proud of my two years spent at the Center for Journalism Ethics, an organization that provides outreach to the public and journalists on contemporary ethical issues.