13-18 March 2016
Academia Sinica
Asia/Taipei timezone

Installation of Public Opinion Sensors: How a Community Based Web Survey Platform Facilitates the Collection of Qualitative Opinion Data

Not scheduled
20m
Academia Sinica

Academia Sinica

No. 128, Sec.2, Academia Road, Taipei, Taiwan
Humanities, Arts, and Social Sciences (HASS) Applications

Speaker

Dr Frank Liu (National Sun Yat-Sen University)

Description

The political polarization in democracies, such as the U.S. and Taiwan, has emerging as a critical challenge to the legitimacy of governance. Not only political elites are likely to become divided along their ideology or stance on salient policy issues, but the general public are also subject to today’s partisan media and self-selected news sources and are expected to become polarized in their partisanship. Employing the agent-based modeling (ABM) approach, we construct an artificial society where political parties, elites, news media, social networks, and ordinary citizens are considered as an ecosystem of preference formation. We pay close attention to the role of “independent voters,” who are less partisan in their partisanship and policy stances, and their willingness of voting participation in the environment of political polarization. The theory of spiral of silence and theories of network heterogeneity suggest that the independents are the group of people who are less likely to turn out to vote. Therefore, that the independents becoming partisan, or least becoming stronger in their partisan orientation, suggests that society-wide participation in voting will increase. Will this theory stand true in all possible situations in the lab? In what situations will the independents become partisan? Does the turnout of the independents suggest a change in the preference redistribution at the aggregate level? As these questions cannot be directly and systematically observed or empirically tested in the field, the lab-experiment approach like ABM employers researchers to explore possible answers to these critical questions. We use Netlogo and John Zaller’s (1992) Response-Accepance-Sample theoretical framework for the construction the model of voter turnout, use grid computing for system calibration and model validation, and then use linear models for testing hypotheses based on simulation data. Implications of the findings for the development of democratic governance are discussed.

Summary

This study employs the agent-based modeling approach (ABM), use Netlogo and employ John Zaller’s (1992) Response-Accepance-Sample theoretical framework to construction the model of voter turnout, by which we examine the extent to which a political polarized environment influences the independent voters' political participation in voting.

Primary authors

Dr Alex Yahja (National Center for Supercomputing Applications) Dr Frank Liu (National Sun Yat-Sen University)

Presentation materials

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