Using Perceptual Tomography for Balance Clustering in Network Construction and Assessing the Success of Community-Level Interventions


DATE
Wednesday December 11, 2019
TIME
11:00 AM - 12:30 PM
Location
ANSO 2107

In the first part of this talk, Lee will introduce a new method for acquiring and interpreting data on cognitive (or perceptual) networks. We refer to the method as perceptual tomography, it aggregates multiple 3rd-party data on the perceived presence or absence of individual properties and pairwise relationships. Key features of the method include: its low respondent burden, flexible interpretation, as well as its ability to find robust intransitive ties in the form of perceived non-edges.

In the second part, a new prevention evaluation method is presented to disentangle the social influences assumed to influence prevention effects within communities. We formally introduce the method and its utility for a suicide prevention program implemented in several Alaskan Native villages. The results show promise to explore eight sociological measures of intervention effects in: the face of social diffusion, social reinforcement, and direct treatment. Policy and research implication are discussed.

 

About Hsuan-Wei (Wayne) Lee

Hsuan-Wei (Wayne) Lee is an Assistant Research Fellow at the Institute of Sociology, Academia Sinica in Taiwan. He received his Ph.D. in Mathematics from UNC-Chapel Hill in 2016. His research, as well as a considerable portion of my collaborative work, addresses complex systems, computational sociology, dynamics on networks, and evolutionary games. Often using computer simulations and knowledge in graph theory, differential equations, combinatorics, stochastic processes, applied statistics, and machine learning techniques, he investigates all kinds of networks, especially social systems, their characteristics, formation, evolution, and often predictions of system behavior. His has publications in Physical Review E, Social Science Research, PloS ONE, Journal of Complex Systems, and Social Network.