Dark personalities on Facebook: Harmful online behaviors and language

被引:50
作者
Bogolyubova, Olga [1 ]
Panicheva, Polina [2 ]
Tikhonov, Roman [2 ]
Ivanov, Viktor [2 ]
Ledovaya, Yanina [2 ]
机构
[1] Clarkson Univ, Dept Psychol, POB 5825, Potsdam, NY 13699 USA
[2] St Petersburg State Univ, 7-9 Univ Skaya Nab, St Petersburg 199034, Russia
关键词
Dark Triad; Facebook; Cyber aggression; Russian language; Distributional semantics; Word clustering; MORPHOLOGICAL TYPOLOGY; COLLEGE-STUDENTS; TEXT ANALYSIS; TRIAD; MACHIAVELLIANISM; DEPRESSION; NARCISSISM; TRAITS; TETRAD; WORDS;
D O I
10.1016/j.chb.2017.09.032
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
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. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:151 / 159
页数:9
相关论文
共 58 条
[1]  
[Anonymous], 2010, P 19 INT C WORLD WID, DOI [DOI 10.1145/1772690.1772862, 10.1145/1772690.1772862]
[2]  
[Anonymous], 2016, ART INT NAT LANG C A
[3]  
[Anonymous], 2016, THESIS U TECHNOLOGY
[4]  
[Anonymous], FDN STAT NATURAL LAN
[5]  
[Anonymous], 2006, P 1 WORKSHOP GRAPH B, DOI DOI 10.3115/1654758.1654774
[6]  
Baker L. D., 1998, Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, P96, DOI 10.1145/290941.290970
[7]  
Baroni M., 2014, LINGUISTIC ISSUES LA, V9, P242
[8]   Cyber Aggression Among College Students: Demographic Differences, Predictors of Distress, and the Role of the University [J].
Bauman, Sheri ;
Baldasare, Angela .
JOURNAL OF COLLEGE STUDENT DEVELOPMENT, 2015, 56 (04) :317-330
[9]   CONTROLLING THE FALSE DISCOVERY RATE - A PRACTICAL AND POWERFUL APPROACH TO MULTIPLE TESTING [J].
BENJAMINI, Y ;
HOCHBERG, Y .
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 1995, 57 (01) :289-300
[10]   Psychometric evaluation of the Serbian dictionary for automatic text analysis - LIWCser [J].
Bjekic, Jovana ;
Lazarevic, Ljiljana B. ;
Zivanovic, Marko ;
Knezevic, Goran .
PSIHOLOGIJA, 2014, 47 (01) :5-32