کد مقاله کد نشریه سال انتشار مقاله انگلیسی ترجمه فارسی نسخه تمام متن
4936998 1363606 2018 9 صفحه PDF ندارد دانلود رایگان
عنوان انگلیسی مقاله
Dark personalities on Facebook: Harmful online behaviors and language
ترجمه فارسی عنوان
شخصیت های تیره در فیس بوک: رفتارهای مضر آنلاین و زبان
کلمات کلیدی
تیره تایی؛ فیس بوک؛ تجاوز سایبری؛ زبان روسی؛ معانی توزیعی؛ خوشه کلمه؛
Dark Triad; Facebook; Cyber aggression; Russian language; Distributional semantics; Word clustering;
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی

•We explore the interplay of the Dark Triad, harmful online behaviors and language.•Psychopathy and male gender predict engagement in harmful online behaviors.•Facebook users with dark traits have identifiable language characteristics.•Findings are consistent with previous research using non-linguistic criteria.

The goal of this paper was to assess the connection between dark personality traits and engagement in harmful online behaviors in a sample of Russian Facebook users, and to describe the language they use in online communication. A total of 6724 individuals participated in the study (mean age = 44.96 years, age range: 18–85 years, 77.9% — female). Data was collected via a purpose-built application, which served two purposes: administer the survey and download consenting user's public wall posts, gender and age from the Facebook profile. The survey included questions on engagement in harmful online behaviors and the Short Dark Triad scale; 15,281 wall posts from 1972 users were included in the dataset. These posts were subjected to morphological, lexical and semantic analyses. More than 25% of the sample reported engaging in harmful online behaviors. Males were more likely to send insulting or threatening messages and post aggressive comments; no gender differences were found for disseminating other people's private information. Psychopathy and male gender were the unique predictors of engagement in harmful online behaviors. A number of significant correlations were found between the dark traits and numeric, lexical, morphological and semantic characteristics of the participants' posts.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers in Human Behavior - Volume 78, January 2018, Pages 151-159
نویسندگان
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