Al-Mosaiwi Mohammed, Johnstone Tom
Department of Psychology, School of Psychology and Clinical Languages, University of Reading, UK.
Pers Individ Dif. 2018 Nov 1;134:119-124. doi: 10.1016/j.paid.2018.06.004.
In social, personality and mental health research, the tendency to select absolute end-points on Likert scales has been linked to certain cultures, lower intelligence, lower income and personality/mental health disorders. It is unclear whether this response style reflects an absolutist cognitive style or is merely an experimental artefact. In this study, we introduce an alternative, more informative, flexible and ecologically valid approach for estimating absolute responding, that uses natural language markers. We focussed on 'function words' (e.g. particles, conjunctions, prepositions) as they are more generalizable because they do not depend on any specific context. To identify such linguistic markers and test their generalizability, we conducted a text analysis of online reviews for films, tourist attractions and consumer products. All written reviews were accompanied by a rating scale (akin to Likert scale), which allowed us to label text samples as absolute/moderate. The data was split into independent 'training' and 'test' sets. Using the training set we identified a rank order of linguistic markers for absolute and moderate text, which were evaluated in a classifier on the test set. The top three markers alone ("but", "!" and "seem") produced 88% classification accuracy, which increased to 91% using 31 linguistic markers.
在社会、人格和心理健康研究中,在李克特量表上选择绝对端点的倾向与某些文化、较低的智力、较低的收入以及人格/心理健康障碍有关。目前尚不清楚这种反应方式是反映了一种绝对主义的认知风格,还是仅仅是一种实验假象。在本研究中,我们引入了一种替代方法,该方法更具信息量、灵活性和生态效度,用于估计绝对反应,它使用自然语言标记。我们关注“功能词”(如小品词、连词、介词),因为它们更具通用性,因为它们不依赖于任何特定语境。为了识别此类语言标记并测试其通用性,我们对电影、旅游景点和消费品的在线评论进行了文本分析。所有书面评论都附有一个评分量表(类似于李克特量表),这使我们能够将文本样本标记为绝对/适度。数据被分为独立的“训练”和“测试”集。我们使用训练集确定了绝对文本和适度文本的语言标记的排名顺序,并在测试集的分类器中对其进行评估。仅前三个标记(“but”、“!”和“seem”)的分类准确率就达到了88%,使用31个语言标记时,准确率提高到了91%。