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University of Michigan School of Information


MISC Talk: The Network Structure of Online Amplification

02/25/2021, 01:00 pm - 02:00 pm

The Michigan Interactive and Social Computing (MISC) research group connects researchers studying human-computer interaction, social computing, and computer-supported cooperative work across the University of Michigan. 



Social media relies on amplification. It is at the heart of how marginalized communities voice injustices, how elected officials communicate public health guidance, and how misinformation proliferates through vulnerable populations. Each instance of amplification is a networked process emerging from many separate interpersonal interactions around an event, news story, or hashtag. Using the case study of #MeToo, I demonstrate how interactions between those who disclosed early in the hashtag campaign likely reduced the stigma of disclosure, allowing for further amplification of the hashtag. As it continued to be used, these disclosures transcended any single disclosure and coalesced into a larger network, composed of the core participants whose experiences of sexual violence were amplified by a larger periphery of bystanders and other survivors. I argue that this core-periphery structure is a fundamental signature of online amplification, and propose statistical models for how it can be identified empirically in networks. Finally, by applying these models back to the #MeToo case study, I demonstrate their effect on our ability to measure the reach of a hashtag activism event, highlighting the importance of accounting for the core-periphery network structure of amplification.

Speaker Bio: 

Ryan Gallagher

Ryan Gallagher is a network science PhD candidate at Northeastern University. As a member of the Communication Media and Marginalization (CoMM) Lab at Northeastern's Network Science Institute, he studies how individuals use online communication networks to amplify their voices, and how that amplification resonates through online media ecologies. To do so, his research makes advances in network science and text-as-data methodology to develop new approaches for measuring the complexities of polarization, misinformation, and the networked public sphere. Ryan interned with Facebook Core Data Science and their Political Organizations & Society team, where he developed methods for identifying inauthentic coordinated information operations, and spent two summers as a visiting research assistant at the University of Southern California's Information Sciences Institute. He holds an MS in mathematics from the University of Vermont, where he worked with the Computational Story Lab at the Vermont Complex Systems Center, and a BA in mathematics from the University of Connecticut.


Zoom link:
Meeting ID: 916 4862 3329
Passcode: misc2021