Voters, Emotions, and Memory

In this paper we argue that emotional response to information encountered in campaigns has implications for the likelihood of remembering that information at the time of the vote. Most voting models are built on what voters remember—whether it is the placement of candidates on issues, or opened ended responses to prompts. That recall of memory is biased is well-known, but the extent to which those biases are driven by affective response to candidate information has not been studied. Using dynamic process tracing, we examine voters' emotional responses, information search, and candidate evaluations during a simulated presidential primary campaign. By manipulating anxiety and the amount of incongruent information that voters encounter, we can detect the direct influence of affect in information processing. We find evidence that voters are more likely to remember information that generates any affective reaction as opposed to information for which the subjects report no emotional response. However, we find little evidence that anxiety has a special role, compared to enthusiasm or anger, in increasing the likelihood that an individual item is remembered. This challenges a primary contention of the theory of Affective Intelligence that anxiety leads to more memories for campaign information.     

The Limitations of Heuristics for Political Elites

Despite the extensive literature on citizens' use of cognitive heuristics in political settings, far less is known about how political elites use these shortcuts. Legislative elites benefit from the efficiency of the accessibility heuristic, but their judgments can also be flawed if accessible information is incomplete or unrepresentative. Using personal interviews and a quasi-experimental design, this paper examines the use of the accessibility heuristic by professional legislative staff when assessing the importance of natural resources issues to their constituents. Staff members recall only a small subset of the relevant constituents in the district, and this subset is biased in favor of active and resource-rich constituents over other, equally relevant constituents. This paper provides a new application of cognitive psychology to political elites and addresses important normative questions about the importance of information processing for political representation. By drawing on the psychology literature on heuristics, this paper identifies the cognitive mechanisms of congressional representation and provides new evidence of old biases.     

Depressive symptoms and parenting competence: An analysis of 13 regulatory processes

Mechanisms that lead depressive symptoms to undermine parenting are poorly understood. This review examines cognitive, affective, and motivational processes thought to be responsible for the impact of depressive symptoms on parenting. We present a five-step, action-control model and review 152 studies relevant to 13 regulatory processes. Evidence suggests that depressive symptoms undermine parenting because they reduce child-oriented goals, undermine attention to child input, increase negative appraisals of children and parenting competence, activate low-positive and high-negative emotion, and increase positive evaluations of coercive parenting. Yet, this review reveals significant limitations in knowledge of these processes. Evidence that they mediate depression-parenting relations is scare; important processes remain unstudied; conceptions of regulation are undifferentiated; children’s contributions are largely unexamined; moderating variables are largely unexplored; and methods fail to capture the dynamics of processing input from children. Rigorous testing of such process models holds promise for clarifying the basis of depression-related parenting problems.     

Answer comparison in automated question answering

In the context of Question Answering (QA) on free text, we assess the value of answer comparison and information fusion in handling multiple answers. We report improvements in answer re-ranking using fusion on a set of location questions and show the advantages of considering candidates as allies rather than competitors. We conclude with some observations about answer modeling and evaluation methodology, arising from a more recent experiment with a larger set of questions and a greater diversity of question types and candidates.     

情绪社会分享的研究现状与发展趋势

情绪事件发生后,人们倾向自愿与他人分享自己的情绪体验,这种现象表现出普遍性、时间性、传播性和限制性等特征。事件的情绪强度、道德属性、情绪分享对象的反应等影响情绪社会分享。情绪社会分享有助于人们调节情绪,检验情绪体验的社会一致性,建构情绪意义,促进人际关系的建立、维持和协调,以及社会秩序的构建等。最后,文章从情绪社会分享的主动调控、情绪社会比较以及情绪社会分享发生的人际网络环境展望了该研究领域     

文本检索模型综述

文本检索是信息检索一个重要的分支。随着互联网信息的迅速膨胀,如何检索到用户最需要的信息变得越来越关键。文本检索模型是文本检索中的核心技术,其性能直接影响到搜索引擎的检索质量。本文对当前的经典检索模型及其研究进展进行介绍,并分析各个模型之间的优缺点。     

The Collective Preference for Shared Information

Decision-making groups prefer to discuss shared information that all members know instead of unshared information that a single member knows. This bias toward discussing shared information can lead groups to make suboptimal decisions when unshared information is critical for good decision making. This preference for discussing shared information may stem from group members' positive evaluations of each other's task capabilities when shared information is communicated. Members who already are perceived as capable (i.e., those high in status, experts, and leaders) need not bolster their image by communicating shared information. Instead, they discuss unshared information more than members perceived as less capable. As members low in status gain respect by communicating shared information, they may risk mentioning unshared information later during discussion. Assigning group leaders, informing members of their expert roles, and allowing ample time for discussion may increase groups' discussion of unshared information.     

What Determines Visual Statistical Learning Performance? Insights From Information Theory

In order to extract the regularities underlying a continuous sensory input, the individual elements constituting the stream have to be encoded and their transitional probabilities (TPs) should be learned. This suggests that variance in statistical learning (SL) performance reflects efficiency in encoding representations as well as efficiency in detecting their statistical properties. These processes have been taken to be independent and temporally modular, where first, elements in the stream are encoded into internal representations, and then the co‐occurrences between them are computed and registered. Here, we entertain a novel hypothesis that one unifying construct—the rate of information in the sensory input—explains learning performance. This theoretical approach merges processes related to encoding of events and those related to learning their regularities into a single computational principle. We present data from two large‐scale experiments with over 800 participants tested in support for this hypothesis, showing that rate of information in a visual stream clearly predicts SL performance, and that similar rate of information values leads to similar SL performance. We discuss the implications for SL theory and its relation to regularity learning.     

Diagnosticity,confidence, and the need for information

Recent research has suggested that people prefer to use the most diagnostic available information as the basis for their choices and decisions, and are most confident in those decisions when information is highly diagnostic. However, the effect of information diagnosticity on the need for additional information has yet to be investigated; that is, in an optional stopping task, will the amount of information requested depend upon information diagnosticity? Three models of the role of diagnosticity in information use were examined; expected value, a confidence criterion, and information cost. Subjects attempted to categorize stimuli with the aid of information of varying costs and diagnosticity levels. They requested more information when it was obtained at a low cost. More importantly, across cost conditions, subjects consistently requested greater amounts of information when that information was of a low diagnosticity. These data seem most consistent with use of a confidence criterion that is adjusted for information costs.     

A call for a statement of expectations for the global information infrastructure

This paper considers the relationship between ethics, technology and law, and the roles and limitations each has in this relationship. It argues that ethics has the key role in establishing a resilient, comprehensive and sensitive information infrastructure. It puts forward a Bill of Rights and Responsibilities for the electronic community.

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