Doctoral Dissertation Research: How Voters Use Campaign Information: On-line Versus Memory-Based Processing in a Presidential Election

博士论文研究：选民如何使用竞选信息：总统选举中的在线处理与基于内存的处理

• 批准号: 9411162
• 负责人: Richard Lau
• 金额: $ 0.62万
• 依托单位: Rutgers University New Brunswick
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1994
• 资助国家: 美国
• 起止时间: 1994-08-01 至 1995-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9411162&HistoricalAwards=false
• 关键词: Doctoral; Dissertation; Research; How; Voters

9411162 Lau During election campaigns voters are exposed to large amounts of information about candidates. In some cases voters can choose whether to pay attention, while in other cases the information is so ubiquitous that voters can hardly avoid it. But in all cases, the flow of information is dynamic, one day information of a candidate's position on an issue is readily available, the next day it can hardly be found. Yet, researchers use static surveys as the method of choice for studying campaigns. Surveys, however, can only capture a single point in time, relying generally on the voters' memories of what they have seen and paid attention to. The elections's dynamic nature is missing. One important result of this mismatch is that while we can make good predictions of the vote choice, we cannot do nearly as good a job describing how voters come to their choice. This Doctoral Dissertation research project is designed to develop a better understanding of the vote decision process by using a dynamic, computer-based methodology to trace information acquisition and decision-making while it is occurring. In particular, the question of whether voters employ an "on-line" or a "memory-based" evaluation process will be explored. Traditional voting models all suggest a memory-based model, where voters store information about candidates during the campaign and search the contents of memory in order to evaluate and choose at the "moment-of-decision." Were the model correct, then surveys conducted near the time of decision would be an ideal methodology for studying the vote decision because memories could be accurately recalled. The on-line model argues instead that voters maintain an "on-line tally" representing the current evaluation of a candidate; when the time comes to make a choice, voters need not search memory for detailed information. Indeed, that information has often been forgotten. Instead, they merely recall the tally associated with each candi date and choose accordingly.

小行星9411162 在竞选活动中，选民会接触到关于候选人的大量信息。 在某些情况下，选民可以选择是否关注，而在另一些情况下，信息是如此无处不在，选民很难避免它。但在所有情况下，信息的流动是动态的，一个候选人对一个问题的立场信息，今天是现成的，第二天就很难找到。然而，研究人员使用静态调查作为研究竞选活动的首选方法。 然而，调查只能捕捉一个时间点，通常依赖于选民对他们所看到和关注的事情的记忆。 选举缺乏动态性。 这种不匹配的一个重要结果是，虽然我们可以很好地预测投票选择，但我们无法很好地描述选民如何做出选择。 该博士论文研究项目旨在通过使用动态的，基于计算机的方法来跟踪信息获取和决策过程，从而更好地了解投票决策过程。 特别是，选民是否采用“在线”或“记忆为基础的”评价过程的问题将进行探讨。 传统的投票模型都建议基于记忆的模型，选民在竞选期间存储有关候选人的信息，并在“决策时刻”搜索记忆内容以进行评估和选择。“如果模型是正确的，那么在投票决定时进行的调查将是研究投票决定的理想方法，因为记忆可以准确地回忆起来。 在线模型认为，选民保持一个“在线计票”，代表候选人的当前评价;当做出选择的时候，选民不需要搜索记忆中的详细信息。 事实上，这一信息常常被遗忘。 相反，他们只是回忆与每个坎迪日期相关的计数，并相应地选择。