کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7248522 | 1471986 | 2018 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Detecting the dark side of personality using social media status updates
ترجمه فارسی عنوان
تشخیص طرف تاریکی شخصیت با استفاده از به روز رسانی وضعیت رسانه های اجتماعی
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کلمات کلیدی
شخصیت، سوابق دیجیتال، زبان، رسانه های اجتماعی، روان سنجی،
موضوعات مرتبط
علوم زیستی و بیوفناوری
علم عصب شناسی
علوم اعصاب رفتاری
چکیده انگلیسی
Organizations use personality assessments to inform recruitment decisions as they are predictive of work-related outcomes. While accurate, these assessments are time-consuming and expensive. Using digital records of behavior to assess personality may offer an alternative solution to overcome these limitations. In this study, we explore whether the “dark side” of personality (non-clinical dysfunctional dispositions) can be inferred through the language used in Facebook Status Updates. Using the Hogan Development Survey (HDS), machine learning methods, and the Linguistic Inquiry and Word Count, language use was found to hold a relationship with HDS scores. The Excitable, Dutiful and Bold scales held the strongest relationship with language (Râ¯=â¯0.27, 0.25 & 0.22, respectively), while the Cautious, Colorful and Leisurely scales held the weakest relationship (Râ¯=â¯0.06, 0.07, & 0.08, respectively). This study extends previous research by demonstrating that the full spectrum of dysfunctional dispositions can be measured using online language. Implications for theory and practice are discussed.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Personality and Individual Differences - Volume 132, 1 October 2018, Pages 90-97
Journal: Personality and Individual Differences - Volume 132, 1 October 2018, Pages 90-97
نویسندگان
Reece Akhtar, Dave Winsborough, Uri Ort, Abigail Johnson, Tomas Chamorro-Premuzic,