Analysis of Personality Traits from Text Based Answers using HEXACO Model

P. William, Abhishek Badholia
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引用次数: 19

Abstract

Analysis was made to propose an algorithmic method that is less complex and efficient in the prediction of personality for applying it to machine learning. Prior before applying the machine learning algorithm, Cronbach's Alpha is applied for testingthe questionnaire made usingHEXACO model to check the reliability of the factor and variables considered. By designing a method to change Cronbach's alpha, we aimed to analyse the influence of conflicting responses on the internal reliability of a dataset. Contrary to popular opinion, random reactions can inflate the alpha of Cronbach when their mean differs from that of the true reactions. Except in scales of both positive and negative polarity products, set answers inflate the alpha of Cronbach. There is not much effect on the effects of inconsistent answers by the amount of response groups. For the study, the mean score is calculated compared against the standard value using One sample test to identify there is a significant difference. The result indicates that there is no significant difference in mean score and standard value. It means that all the interviewees has reasonable level personality with respect to Honesty-Humility, Extraversion and Conscientiousness. For the factors; Emotionality, Agreeableness and Openness there is a significant difference in mean score and standard value. Through the Mean score calculated using One-Sample Statistics, it can be interpreted that the Interviewees have more than significant level of Agreeableness and Openness Personality but less Emotionality. This result is compared to the result of many HR professionals. To make the comparison of the resultPearson correlation method is applied, to know is there a significant relationship between the result given by HR managers and personality predicted using the HEXACO Model. The result indicates, there is a significant relationship between HR manager report and the HEXACO model algorithm constructed for personality prediction. Also, the estimated Pearson correlation value (0.819) indicates that there is 81.9% similarity in the result given by HR managers and the HEXACO model algorithm constructed for personality prediction.
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使用HEXACO模型分析基于文本的答案的人格特征
通过分析,提出了一种将人格预测应用于机器学习的简单高效的算法方法。在应用机器学习算法之前,使用Cronbach's Alpha对使用hexaco模型制作的问卷进行测试,以检查所考虑的因素和变量的可靠性。通过设计一种改变Cronbach's alpha的方法,我们旨在分析冲突响应对数据集内部可靠性的影响。与普遍观点相反,当随机反应的均值与真实反应的均值不同时,会使Cronbach的alpha值膨胀。除了正极性积和负极性积的量表外,设定答案会使Cronbach的alpha值膨胀。回答组的数量对不一致答案的影响不大。在本研究中,使用单样本检验将平均得分与标准值进行比较,以确定是否存在显著差异。结果表明,两组的平均得分和标准值无显著差异。这意味着所有受访者在诚实-谦卑、外向性和责任心方面都具有合理水平的人格。对于因子;情绪性、宜人性和开放性在均分和标准值上存在显著差异。通过单样本统计计算的均分,可以解释受访者的宜人性和开放性人格水平高于显著性,而情绪性人格水平低于显著性。这个结果与许多人力资源专业人士的结果进行了比较。为了对结果进行比较,应用pearson相关法,了解人力资源经理给出的结果与HEXACO模型预测的人格之间是否存在显著关系。结果表明,人力资源经理报告与构建的HEXACO人格预测模型算法之间存在显著的相关关系。Pearson相关估计值(0.819)表明,人力资源经理给出的结果与构建的HEXACO模型算法的人格预测结果相似度为81.9%。
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