Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
The presented project is intended to make use of growing amounts or textual data in social networks in the Russian language, In order to Hnd Ungulstlc correlates of the Dark Triad personality traits, comprising non-clinical Nareissism, Machiavellianism and Psychopathy. The baekgronnd for the ilwestigation includes, on the one haotl, psychological research on these phenomena and their measurement instruments, and on the other haod, recent advaoces In computational stylometry and text-based author profiling. The measures for these psychological phenomena are provided by recognized self-report psychological surveys adapted to Russian. Morphological and semantic analysis are applied to investigate the relationship between the Dark traits and their linguistic manifestation in social network texts. Slgnlflcant morphological and semantic correlates of Narcissism, MachlavelUanlsm and Psychopathy are ldentllled and compared to respective advaoces In Engltsh author proftUng. In order to deepen our underslanding of the relation between these psychological characteristics aod natural language use, the identified linguistic features are Interpreted In terms of the line-grained factor structure of the Dark traits. Identifying correlated features is a step towards automatic Dark trait prediction aod early detection of the potentially harmful mental states.
Original language | English |
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Title of host publication | Proceedings of the AINL FRUCT 2016 Conference |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 72 - 79 |
ISBN (Electronic) | 9789526839783 |
State | Published - 3 Apr 2017 |
Event | Artificial Intelligence and Natural Language FRUCT Conference - Saint-Petersburg, Russian Federation Duration: 10 Nov 2016 → 12 Nov 2016 Conference number: 5 http://ainlconf.ru/2016 |
Conference | Artificial Intelligence and Natural Language FRUCT Conference |
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Abbreviated title | AINL FRUCT 2016 |
Country/Territory | Russian Federation |
City | Saint-Petersburg |
Period | 10/11/16 → 12/11/16 |
Internet address |
ID: 7609549