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Detection of IAD based on personality questionnaires of Chinese college students and SVMs

机译:基于中国大学生和SVM人格问卷的IAD检测

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The unprecedented development of the Internet brings many benefits but it also manifests the Internet addiction disorder (IAD) which has a huge impact on some people in our society. However, it is hard to diagnose and prevent IAD. In this study, we propose a new way to detect IAD using C-SVM and V-SVM by inviting 580 Chinese College Students to complete the questionnaires which consist of Brief Self Control Scale (BSCS), the 11th version of Barratt Impulsiveness Scale (BIS-11), Chinese Big Five (CBF) and Chen Internet Addiction Scale (CIAS). BSCS, BIS-11 and CBF evaluate one's personality in nine subscales. CIAS score is used to label the high and low group. We compare the performances of two SVMs on two datasets with different features by 5-fold cross validation after normalization. It is found that IAD could be detected from personality questionnaire data using SVM effectively. In particular, C-SVM with RBF function on the dataset with only subscales normalized in the range of [-1,1] was preferred.
机译:互联网的前所未有的发展带来了许多好处,但它也表现出对我们社会中的一些人产生了巨大影响的互联网成瘾障碍(IAD)。但是,很难诊断和预防IAD。在这项研究中,我们提出了一种通过C-SVM和V-SVM邀请580名中国大学生来填写调查问卷来检测IAD的新方法,该问卷由简短的自我控制量表(BSC),第11版的Barratt冲动量表(BIS -11),中国大五(CBF)和陈互联网成瘾量表(CIAS)。 BSC,BIS-11和CBF在九个分量中评估一个人的个性。 CIAS分数用于标记高低组。我们在标准化后5倍交叉验证,将两个SVMS对两个数据集的表现进行比较。发现IAD可以有效地使用SVM从人格问卷数据中检测到。特别是,在数据集上具有RBF功能的C-SVM优选在[-1,1]范围内归一化的数据集上。

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