Please use this identifier to cite or link to this item:

Title: 即時資訊處理模型與投票行為研究的運用-以美國選民投票行為分析為例
On-line Information Processing and Its Application in Voting Behavior Research-An Analysis of U. S. Voting Behavior
Authors: 盛治仁
Sheng, Emile C. J.
Keywords: 資訊處理模型;投票行為;記憶資訊處理;及時資訊處理及開放式問卷
information processing;voting behavior;on-line information processing;memory-based information processing;and open- ended questions
Date: 2001-11
Issue Date: 2017-11-08 11:32:09 (UTC+8)
Abstract: 多數選舉研究把焦點放在變項之間的關係,但是我們對選民處理政治資訊的認知過程卻不十分瞭解,許多基於實驗設計的研究發現過去慣用的記憶資訊處理假設無法正確地形容人們處理資訊的過程,並提出即時資訊處理假設作爲較好的選擇。本文除了討論即時資訊處理模型及其在投票行爲研究的應用之外,還以調查研究的實證檢測提供輔助性的證據,以補實驗設計方法的限制。問卷資料分析顯示即時資訊處理模式較能正確地描述人類處理資訊的過程,因此,我們對過去許多基於記憶資訊處理假設的模型結論都必須重新檢視,並且對開放式問卷的運用也必須特別小心。對選民資訊處理過程的瞭解是一個重要的領域,將能幫助我們建構更好的投票行爲模型。
Most electoral studies emphasize the relationships among variables, but paid little attention to how voters process political information. Past studies based on experimental design concluded that the memory-based information processing model can not correctly describe how people process political information, and proposed on-line information processing model as a better alternative. This article discusses the on-line information processing model and its application in voting behavior research. The author also uses NES survey data to provide supplementary evidence to the experimental design findings on the on-line model. We found that the online information processing model is a more plausible model than the memory-based model. Therefore, we have to be careful in generalizing past results based on the memory-based models, and have to be especially careful when analyzing open-ended questionnaires. It is important for us to enhance our understanding of voter information processing to help construct better voting behavior models.
Relation: 選舉研究 , 8(2) , 31-64
Data Type: article
DOI 連結:
Appears in Collections:[選舉研究 TSSCI] 期刊論文

Files in This Item:

File Description SizeFormat
8(2)(031-064).pdf1664KbAdobe PDF118View/Open

All items in 學術集成 are protected by copyright, with all rights reserved.

社群 sharing