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資訊系統與應用研究所
[Nov-28] Newsfeed Filtering and Dissemination for Behavioral Therapy on Social Network Addictions

Seminar of Institute of Information Systems and Applications

Speaker :

帥宏翰 Dr. Shuai, Hong-Han

Assistant Professor, Electrical and Computer Engineering, NCTU

Topic :

Newsfeed Filtering and Dissemination for Behavioral Therapy on Social Network Addictions

Date :

13:30-15:00 Wednesday 28-Nov-2018

Place :

台達館R105Delta Building R105

Host :

Prof. Chih Ya Shen

Abstract

While the popularity of online social network (OSN) apps continues to grow, little attention has been drawn to the increasing cases of Social Network Addictions (SNAs). We argue that by mining OSN data in support of online intervention treatment, data scientists may assist mental healthcare professionals to alleviate the symptoms of users with SNA in early stages. Our idea, based on behavioral therapy, is to incrementally substitute highly addictive newsfeeds with safer, less addictive, and more supportive newsfeeds. To realize this idea, we propose a novel framework, called Newsfeed Substituting and Supporting System (N3S), for newsfeed filtering and dissemination in support of SNA interventions. New research challenges arise in 1) measuring the addictive degree of a newsfeed to an SNA patient, and 2) properly substituting addictive newsfeeds with safe ones based on psychological theories. To address these issues, we first propose the Additive Degree Model (ADM) to measure the addictive degrees of newsfeeds to different users. We then formulate a new optimization problem aiming to maximize the efficacy of behavioral therapy without sacrificing user preferences. Accordingly, we design a randomized algorithm with a theoretical bound. A user study with 716 Facebook users and 11 mental healthcare professionals around the world manifests that the addictive scores can be reduced by more than 30%. Moreover, experiments show that the correlation between the SNA scores and the addictive degrees quantified by the proposed model is much greater than that of state-of-the-art preference based models.

Bio

Dr. Shuai received the B.S. degree from the Department of Electrical Engineering, National Taiwan University (NTU), Taipei, Taiwan, R.O.C., in 2007, the M.S. degree in computer science from NTU in 2009, and the Ph.D. degree in Graduate Institute of Communication Engineering in 2015. He was a visiting scholar in University of Illinois at Chicago, USA from 2013 to 2014 and a postdoctoral fellow in Research Center for Information Technology Innovation from 2015 to 2016. He is now an assistant professor in Department of ECE, National Chiao Tung University (2016~).

All faculties and students are welcome to join.

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