서울대학교

서울대학교 BK21 FOUR 자유롭고 책임있는 AI 미디어 교육연구단과 언론정보연구소에서 커뮤니케이션학계 해외 유수 학자들을 초청해 다양한 주제의 강연 시리즈를 개최하고 있습니다.

이 세션은 온라인으로 진행됩니다. 많은 분들의 관심과 참여 부탁드립니다.

일시 : 6월 29일 (수) 오전 9:30 - 11:00

참여 링크 : https://snu-ac-kr.zoom.us/j/94694364868

강연자 : Dhavan V. Shah (University of Wisconsin)

주제 : Digital Traces and Social Ties: How Computational Social Science is Transforming Communication Research

내용:
This talk examines the growing importance of computational social science in communication research, arguing that the turn toward data science is transforming this work through increased attention to digital trace data, electronic text and digital visual content, and network connections and communication interactions, often in combination. This is certainly true (a) for work connecting communication and health management, especially in chronic care of individuals in recovery from cancer and addiction and (b) for research examining political contention in response to societal events as reflected in our polarized and asymmetric media ecologies. The frameworks for research shared in this talk emphasize the role of network mapping and the power of text analytics for addressing pressing communication and societal questions, with the dual U.S. crises of the opioid epidemic and mass shootings used as exemplars. Data collected through multiple NIH-funded studies of health technology and foundation funded projects tracking political news and social media also point to larger conclusions about the intersection of data science and communication research.

강연자 소개:
Dhavan Shah is Maier-Bascom Professor at the University of Wisconsin, where he is Director of the Mass Communication Research Center (MCRC), Research Director of the Center for Communication and Civic Renewal (CCCR), and Scientific Director in the Center for Health Enhancement System Studies (CHESS). An abiding interest in the intersecting power of framing and social capital has shaped his research on: (1) the influence of message construction and processing, (2) the communication dynamics shaping civic participation, and (3) the effects of computer-mediated interactions on chronic disease management. This work has generated grants totaling nearly $50 million from private foundations and federal governments. He often applies computational approaches to social science questions, using digital trace data, natural language processing, network mapping, and predictive analytics to study politics and health. He is appointed in the School of Journalism and Mass Communication, with affiliations in Industrial and Systems Engineering, Marketing, and Political Science.