Psychometric and Validity Issues in Machine Learning Approaches to Personality Assessment: A Focus on Social Media Text Mining

In the age of big data, substantial research is now moving toward using digital footprints like social media text data to assess personality. Nevertheless, there are concerns and questions regarding the psychometric and validity evidence of such approaches. We seek to address this issue by focusing on social media text data and (i) conducting a review of psychometric validation efforts in social media text mining (SMTM) for personality assessment and discussing additional work that needs to be done; (ii) considering additional validity issues from the standpoint of reference (i.e. ‘ground truth’) and causality (i.e. how personality determines variations in scores derived from SMTM); and (iii) discussing the unique issues of generalizability when validating SMTM for personality assessment across different social media platforms and populations. In doing so, we explicate the key validity and validation issues that need to be considered as a field to advance SMTM for personality assessment, and, more generally, machine learning personality assessment methods. © 2020 European Association of Personality Psychology     

New Directions in the Conceptualization and Assessment of Personality—A Dynamic Systems Approach

In this paper, we demonstrate how an integrative approach to personality—one that combines within-person and between-person differences—can be achieved by drawing on the principles of dynamic systems theory. The dynamic systems perspective has the potential to reconcile both the stable and dynamic aspect of personality, it allows including different levels of analysis (i.e. traits and states), and it can account for regulatory mechanisms, as well as dynamic interactions between the elements of the system, and changes over time. While all of these features are obviously appealing, implementing a dynamic systems approach to personality is challenging. It requires new conceptual models, specific longitudinal research designs, and complex data analytical methods. In response to these issues, the first part of our paper discusses the Personality Dynamics model, a model that integrates the dynamic systems principles in a relatively straightforward way. Second, we review associated methodological and statistical tools that allow empirically testing the PersDyn model. Finally, the model and associated methodological and statistical tools are illustrated using an experience sampling methodology data set measuring Big Five personality states in 59 participants (N = 1916 repeated measurements). © 2020 The Authors. European Journal of Personality published by John Wiley & Sons Ltd on behalf of European Association of Personality Psychology     

To Challenge the Morning Lark and the Night Owl: Using Smartphone Sensing Data to Investigate Day–Night Behaviour Patterns

For decades, day–night patterns in behaviour have been investigated by asking people about their sleep–wake timing, their diurnal activity patterns, and their sleep duration. We demonstrate that the increasing digitalization of lifestyle offers new possibilities for research to investigate day–night patterns and related traits with the help of behavioural data. Using smartphone sensing, we collected in vivo data from 597 participants across several weeks and extracted behavioural day–night pattern indicators. Using this data, we explored three popular research topics. First, we focused on individual differences in day–night patterns by investigating whether ‘morning larks’ and ‘night owls’ manifest in smartphone-sensed behavioural indicators. Second, we examined whether personality traits are related to day–night patterns. Finally, exploring social jetlag, we investigated whether traits and work weekly day–night behaviours influence day–night patterns on weekends. Our findings highlight that behavioural data play an essential role in understanding daily routines and their relations to personality traits. We discuss how psychological research can integrate new behavioural approaches to study personality.     

Applying theory to the black box: A model for empirically scoring biodata

Despite being an effective predictor of job performance, empirically keyed biodata assessments have been criticized as black box empiricism unlikely to generalize to new contexts. This paper introduces a model that challenges this perspective, explicating how biodata content, job demands, and criterion variables collectively influence the construct validity, and generalizability of empirically scored biodata. Across two field studies, expected changes in scale correlations with external measures were found that coincided with changes in the contextual similarity between calibration and holdout contexts, the criteria used, and the content validity of biodata items. Collectively, this paper offers a framework that helps understand and optimize empirical biodata keying in practice, furthering confidence for their use in applied settings.     

熊十力《新唯识论》的易学渊源与理论创新

研究《周易》生命哲学,单向度地从宇宙论演绎太极阴阳变化,或从心性论凸显易道生命实践的主体能动性,都无法实证宇宙大生命一体贯通的诚明合一之境。在熊十力哲学多元文化渊源和思想元素中,《周易》无疑是其哲学创新的最深邃的理论源泉和精神根基。宇宙本体与生命主体圆融为一,以生生之道涵化主体心灵,用主体心灵担当天地之情,成为熊十力《新唯识论》生命哲学理论突破的关键所在。     

“自爱”指标与维度的初探——《四库全书》中“自爱”的心理学研究

从《四库全书》中检索到1700部涉及“自爱”的古籍,形成包含2370条句段的语料库并逐条进行内容分析。结果发现,自爱包含自我珍重、自我接纳与自我约束三个主要指标以及个我自爱、小我自爱与大我自爱三个主要维度。未来研究将依据我国社会文化和历史的脉络,结合新时代人们对自爱的理解,编制相应的测量工具,从而为健全人格养成服务。     

变量间的网络分析模型及其应用

变量间的网络分析模型近年来被广泛应用于心理学研究。不同于将潜变量作为观测变量的共同先导因素的潜变量模型, 网络分析模型将观测变量作为初级指标, 采用图论的方法建立观测变量之间的关系网络, 其中变量为网络的节点, 而变量间的关系是节点之间的连线。因此网络分析可以突显观测变量之间的联系以及观测变量相互影响而形成的系统。通过变量网络中基于各个节点特征的指标(如中心性)以及基于整体结构特征的指标(如小世界性), 网络分析为研究各种心理现象提供了新的可视化的描述方式和理解视角。近10年来, 网络分析的方法已在人格心理学、社会心理学和临床心理学等领域得到一定的应用。未来研究应继续发展和完善网络分析模型的理论和方法, 使之运用到更多的数据类型和更广的研究领域中。     

青少年自我描述归类与人格维度特点

对青少年自我描述的内容进行归类时发现,依据不同的归类标准会得到不同的人格结构。500多名青少年学生提供了620个不同的对自我的描述,除9个项目属于对身体和家庭状况的描述外,所有的人格特征既可以归属到中国青少年人格结构的19个二级因素,又可以归属到西方大五人格结构的30个层面。这一结果表明,外显的人格特征分类无法准确表达人格结构的实际构成,人格结构的确定还需要实证评定及对内隐结构的探索。文中还讨论了心理学研究中国化（本土化）的思路与策略。