The role of corpus size and syntax in deriving lexico-semantic representations for a wide range of concepts

One of the most significant recent advances in the study of semantic processing is the advent of models based on text and other corpora. In this study, we address what impact both the quantitative and qualitative properties of corpora have on mental representations derived from them. More precisely, we evaluate models with different linguistic and mental constraints on their ability to predict semantic relatedness between items from a vast range of domains and categories. We find that a model based on syntactic dependency relations captures significantly less of the variability for all kinds of words, regardless of the semantic relation between them or their abstractness. The largest difference was found for concrete nouns, which are commonly used to assess semantic processing. For both models we find that limited amounts of data suffice in order to obtain reliable predictions. Together, these findings suggest new constraints for the construction of mental models from corpora, both in terms of the corpus size and in terms of the linguistic properties that contribute to mental representations.     

Pauses in elementary school children's verbatim and gist free recall of a story

The aim of the research was to explore the function of pauses in children's oral verbatim and gist-based free recall, assuming that pauses indicate cognitive processing. The main question guiding this research was whether verbatim and gist recall constituted two different ways of cognitive processing associated with different time patterns of speech. Elementary school children (n = 180) between the ages of 8 and 10 years heard a story and were then instructed to either retell the story verbatim or retell its gist. They orally recalled the story for the first time immediately after hearing the story and again 1 week later. The results confirmed the main hypothesis of independence of verbatim and gist traces in that mean pause lengths were longer when verbatim retrieval was asked for as compared to gist retrieval. High correct gist recall was characterized by more and shorter pauses, indicating fluent retrieval.     

明清四种注《孟》著作散论

明清两代 ,有四部以“孟子”为书名前冠的著作 ,作者分别是黄宗羲、戴震、焦循、康有为。他们在《孟子师说》、《孟子字义疏证》、《孟子正义》、《孟子微》中 ,对《孟子》这一经典文本注入了自己有创意的见解。这些独创的观点 ,不仅较好地体现了这四位思想家不同于传统的启蒙风貌与近代意识 ,也体现了中国文化发展历史的规律与特点。     

Prediction and classification in nonlinear data analysis: Something old,something new,something borrowed,something blue

Prediction and classification are two very active areas in modern data analysis. In this paper, prediction with nonlinear optimal scaling transformations of the variables is reviewed, and extended to the use of multiple additive components, much in the spirit of statistical learning techniques that are currently popular, among other areas, in data mining. Also, a classification/clustering method is described that is particularly suitable for analyzing attribute-value data from systems biology (genomics, proteomics, and metabolomics), and which is able to detect groups of objects that have similar values on small subsets of the attributes.This article is based on the Presidential Address Jacqueline Meulman gave on July 9, 2003 at the 68th Annual Meeting of the Psychometric Society held near Cagliari, Italy on the island of Sardinia.—Editor     

小学生羞怯特质预测及语言风格模型构建

收集在线教学平台上1306名小学生的作文、日记及评论, 采用自然语言处理技术进行文本分析, 并应用机器学习模型实现对羞怯特质的自动预测, 构建小学生羞怯行为、认知和情绪的语言风格模型。研究发现：(1)扩充的心理词典适合分析小学生文本; (2)分别存在羞怯行为、认知和情绪问题的学生其日常用语既有共性也有特性, 且与普通学生存在差异; (3)羞怯各维度在不同分类器上达到较好的预测效果, 其中随机森林模型的整体表现相对最好。     

我国大陆地区网络心理咨询现状和伦理议题：“大数据”视角及伦理评估

随着计算机的发展,网络心理咨询受到越来越多的关注。本研究搜索和爬取网络心理咨询网站及咨询师信息,并采用16项伦理清单对其伦理规范进行评估。结果显示(1)网络心理咨询服务网站不断增多,网络心理咨询师数量逐年升高,但实际活跃数相对较少;(2)24个望网络心理咨询网站对咨询师的信息要求较为严格,对来访者信息要求模糊,且注意事项呈现不够充分。我国的网络心理咨询正在慢慢壮大,但是需要进一步加强伦理规范。     

Real-time detection of drivers’ texting and eating behavior based on vehicle dynamics

With rapid advancement in cellphones and intelligent in-vehicle technologies along with driver’s inclination to multitasking, crashes due to distracted driving had become a growing safety concern in our road network. Some previous studies attempted to detect distracted driving behaviors in real-time to mitigate their adverse consequences. However, these studies mainly focused on detecting either visual or cognitive distractions only, while most of the real-life distracting tasks involve driver’s visual, cognitive, and physical workload, simultaneously. Additionally, previous studies frequently used eye, head, or face tracking data, although current vehicles are not commonly equipped with technologies to acquire such data. Also those data are comparatively difficult to acquire in real-time during traffic monitoring operations. To address the above issues, this study focused on developing algorithms for detecting distraction tasks that involve simultaneous visual, cognitive, and physical workload using only vehicle dynamics data. Specifically, algorithms were developed to detect driving behaviors under two distraction tasks – texting and eating. Experiment was designed to include the two distracted driving scenarios and a control with multiple runs for each. A medium fidelity driving simulator was used for acquiring vehicle dynamics data for each scenario and each run. Several data mining techniques were explored in this study to investigate their performance in detecting distraction. Among them, the performance of two linear (linear discriminant analysis and logistic regression) and two nonlinear models (support vector machines and random forests) is reported in this article. Random forests algorithms had the best performance, which detected texting and eating distraction with an accuracy of 85.38% and 81.26%, respectively. This study may provide useful guidance to successful development and implementation of distracted driver detection algorithms in connected vehicle environment, as well as to auto manufacturers interested in integrating distraction detection systems in their vehicles.     

The Semantic Drift of Quotations in Blogspace: A Case Study in Short‐Term Cultural Evolution

We present an empirical case study that connects psycholinguistics with the field of cultural evolution, in order to test for the existence of cultural attractors in the evolution of quotations. Such attractors have been proposed as a useful concept for understanding cultural evolution in relation with individual cognition, but their existence has been hard to test. We focus on the transformation of quotations when they are copied from blog to blog or media website: by coding words with a number of well‐studied lexical features, we show that the way words are substituted in quotations is consistent (a) with the hypothesis of cultural attractors and (b) with known effects of the word features. In particular, words known to be harder to recall in lists have a higher tendency to be substituted, and words easier to recall are produced instead. Our results support the hypothesis that cultural attractors can result from the combination of individual cognitive biases in the interpretation and reproduction of representations.     

Cultural Studies Methodologies and Narrative Family Therapy: Therapeutic Conversations About Pop Culture

Therapists recognize that popular media culture is an influential force that shapes identities and relationships in contemporary society. Indeed, people have serious relationships with the commodities and practices that emerge from pop culture. However, they often lack the conceptual and conversational resources to engage meaningfully with clients about pop culture's influence in their lives. Cultural studies is introduced as an interdisciplinary approach that provides frameworks for both theory and practice that position therapists and clients to critically examine the role of pop culture in their lives. Cultural studies and narrative therapy are discussed as praxis allies that share a populist political intention and counter‐hegemonic discursive practices. The integration of cultural studies methodologies into narrative therapy practice with a parent and her teenage daughter is illustrated through a case vignette.     

眼动追踪技术与婴幼儿研究:程序、方法与数据分析

眼动技术在婴幼儿研究中成为一种流行的研究工具。如何合理地选择和使用眼动仪进行数据收集及分析,是婴幼儿眼动研究者需要考虑的重要问题。本文从眼动仪使用的流程出发,主要对婴幼儿眼动研究过程中所涉及的四个方面的问题进行了梳理和分析:(1)正确选择仪器;(2)合理校准;(3)提高数据质量;(4)有效分析和挖掘数据。同时,针对这些方面提出了相应的操作性建议。