|Talks|

How Political Information Travels, and What It Does to Trust in Institutions

Dissertation proposal
Virtual
Past Talk
Hong Qu
PhD student Network Science Institute
Mon
,
Sep 14, 2026
12:00 pm
EST
Sep 14, 2026
12:00 pm
In-person
Portsoken Street
London, E1 8PH, UK
The Roux Institute
Room
100 Fore Street
Portland, ME 04101
Network Science Institute
2nd floor
Network Science Institute
11th floor
177 Huntington Ave
Boston, MA 02115
Network Science Institute
2nd floor
Room
58 St Katharine's Way
London E1W 1LP, UK
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Talk recording

Most of what we know about how political information spreads comes from the places researchers can watch: television, newspapers, and the open social media platforms. Americans increasingly get their news somewhere else—in group chats and private messages, from podcasts, search results and AI assistants, and from people they know. These channels are not merely harder to study. Many are built so that no outsider can see what moves through them, and the rules written to govern online speech assume a visibility they do not have. This dissertation asks what follows. The first paper measures how far political conspiracy claims travel through private messaging, where neither platforms nor researchers can follow them. The second asks why American confidence in public institutions has fallen, and finds that what is usually described as a collapse of trust in science is largely something else: trust in agencies that changes hands with each election, while confidence in scientists themselves barely moves. The third maps the whole information environment by what can be counted and who can be held responsible, then simulates what becomes of a false claim, and of a correction, as audiences move into channels nobody can observe.
About the speaker
Hong Qu is a PhD candidate at the Network Science Institute at Northeastern University, advised by David Lazer. His research examines how political news and misinformation move through online networks, and how that movement shapes public opinion, political beliefs, and trust in institutions including science and the public health agencies. Before joining academia he spent a decade in technology and journalism, beginning as an early engineer at YouTube and later working as a technologist in newsrooms. He teaches data visualization as an adjunct lecturer at the Harvard Kennedy School.
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Sep 14, 2026