Facilitating natural flow of information among "taste-based" groups

Authors:
Yefeng Liu;Todorka Alexandrova;Satoshi Hirade;Tatsuo Nakajima
Affiliations:
Waseda University, Tokyo, Japan;Waseda University, Tokyo, Tokyo, Japan;Waseda University, Shinjyuku-ku, Tokyo-to, Japan;Waseda University, Tokyo, Japan
Venue:
CHI '13 Extended Abstracts on Human Factors in Computing Systems
Year:
2013

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Abstract

Social science studies have shown that the disconnection of people from different social classes or opinion groups may reinforce serious problems to our society (e.g., residential segregation, group polarization, or confirmation bias). With the emerging trend of the Web 2.0, however, different kinds of people are likely having less chance to share information with each other. How to design for supporting better information flow among different social, taste, or opinion groups of people becomes a challenging question for digital designers. In this work-in-progress paper we present our on-going research of exploring a crowd-based system for facilitating natural information flow among different types of people. We conducted a Wizard-of-OZ study to simulate push-based human powered recommendation, and learn how participants react when receiving unexpected information. Based on the findings, we designed and implemented a web application for encouraging different kinds of people to exchange information in a peer-to-peer way. Next steps include designing pairing strategy and conducting user study.