The role of causality in discourse processing: Effects of expectation and coherence relations

因果关系(物理学) 连贯性(哲学赌博策略) 理解力 心理学 认知心理学 背景(考古学) 因果模型 句子处理 关系(数据库) 计算机科学 口译(哲学) 心理语言学 语言学 自然语言处理 认知 数学 哲学 古生物学 神经科学 物理 程序设计语言 统计 生物 数据库 量子力学
作者
Willem M. Mak,Ted Sanders
出处
期刊:Language and Cognitive Processes [Informa]
卷期号:28 (9): 1414-1437 被引量:30
标识
DOI:10.1080/01690965.2012.708423
摘要

Research on the processing of causality has shown that causally related sentences lead to faster reading, better recall, and better comprehension than sentences that are not causally related. In this study, we investigate two ways in which causality can influence processing: through the expectation that readers may have of a causal relation and the ease with which the sentences can be related in a causal way on the basis of their content. We ran two eye tracking experiments to investigate the online effects of these factors. In the experiments we looked at the influence of these factors on the process of establishing referential and relational coherence. Experiment 1 shows that immediate effects of causal relatedness on referential processing occur even with a connective that is not explicitly causal (when). Moreover, the results show that the early effect only occurs when readers expect a causal relation. Experiment 1 also shows that causal expectations facilitate the processing of causally related sentences. Experiment 2 shows that this is only the case when the content of the second clause actually allows a causal interpretation. The data show that causal expectations have differential effects on the processing of referential and relational coherence. Referential coherence is influenced proactively by the focusing of one of the referents in the context. Relational coherence, on the other hand, is influenced retroactively: only when there turns out to be a causal link between the sentences is processing facilitated by causal expectation.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
CodeCraft应助柠檬采纳,获得10
1秒前
库里晚安完成签到,获得积分10
1秒前
A1len完成签到 ,获得积分10
2秒前
星辰大海应助sokach采纳,获得10
3秒前
新一发布了新的文献求助30
3秒前
守夜人完成签到,获得积分10
3秒前
习习应助孔雀翎采纳,获得10
4秒前
liu完成签到,获得积分10
4秒前
田様应助玉衡璇玑采纳,获得10
5秒前
成就梦松发布了新的文献求助10
5秒前
123完成签到,获得积分10
5秒前
5秒前
5秒前
7秒前
Orange应助123采纳,获得10
7秒前
9秒前
仄言完成签到,获得积分10
9秒前
10秒前
儒雅的斑马完成签到,获得积分10
10秒前
汉堡包应助咕噜仔采纳,获得10
10秒前
FashionBoy应助momo采纳,获得10
10秒前
11秒前
11秒前
12秒前
第七兵团司令完成签到,获得积分10
13秒前
13秒前
qwq应助追梦采纳,获得10
13秒前
13秒前
14秒前
我爱Chem完成签到 ,获得积分10
14秒前
半生发布了新的文献求助30
15秒前
15秒前
成就梦松完成签到,获得积分10
15秒前
byyyy完成签到,获得积分10
15秒前
温暖的俊驰完成签到,获得积分10
16秒前
Isabel完成签到,获得积分10
16秒前
yx应助陈强采纳,获得30
17秒前
sokach发布了新的文献求助10
19秒前
缓慢荔枝发布了新的文献求助10
19秒前
123发布了新的文献求助10
20秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527304
求助须知:如何正确求助?哪些是违规求助? 3107454
关于积分的说明 9285518
捐赠科研通 2805269
什么是DOI,文献DOI怎么找? 1539827
邀请新用户注册赠送积分活动 716708
科研通“疑难数据库(出版商)”最低求助积分说明 709672