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. (2020). What’s in a label? Negative credibility labels in partisan news. Online first at Journalism and Mass Communication Quarterly. DOI: https://doi.org/10.1177/1077699020961856
Duncan, M., & Culver, K. (2020). Technologies, Ethics and Journalism’s Relationship with the Public. Media and Communication, 8(3), 101-111. doi: http://dx.doi.org/10.17645/mac.v8i3.3039
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.