Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Personality Analysis Using Classification on Turkish Tweets
Download
index.pdf
Date
2021-10-01
Author
Karagöz, Pınar
Toroslu, İsmail Hakkı
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
307
views
390
downloads
Cite This
According to the psychology literature, there is a strong correlation between personality traits and the linguistic behavior of people. Due to the increase in computer based communication, individuals express their personalities in written forms on social media. Hence, social media has become a convenient resource to analyze the relationship between personality traits and lingusitic behaviour. Although there is a vast amount of studies on social media, only a small number of them focus on personality prediction. In this work, the authors aim to model the relationship between the social media messages of individuals and big five personality traits as a supervised learning problem. They use Twitter posts and user statistics for analysis. They investigate various approaches for user profile representation, explore several supervised learning techniques, and present comparative analysis results. The results confirm the findings of psychology literature, and they show that computational analysis of tweets using supervised learning methods can be used to determine the personality of individuals.
Subject Keywords
Big Five Personality Traits
,
Deep Learning
,
Machine Learning
,
Personality
,
Social Media
,
Supervised Learning
,
Tweets
URI
https://hdl.handle.net/11511/93959
Journal
International Journal of Cognitive Informatics and Natural Intelligence
DOI
https://doi.org/10.4018/ijcini.287596
Collections
Department of Computer Engineering, Article
Suggestions
OpenMETU
Core
Classification based personality analysis on Turkish tweets
Maviş, Gökalp; Toroslu, İsmail Hakkı; Department of Computer Engineering (2019)
Psychology researches suggest that some of the personality traits correlate with lin-guistic behavior and nowadays people most commonly present themselves to theworld by using social media. In social media, users openly reveal insights into theirlives and details about their personality. Although, there are many studies related tosocial media, only a small number of them work on personality prediction. In thisproject, we used not only text data but also the other statistics of users of Twitterwhich is one o...
Cognitive aspects of personality disorders: influences of basic personality traits, cognitive emotion regulation, and interpersonal problems
Akyunus İnce, Miray; Gençöz, Tülin; Department of Psychology (2012)
The purpose of the study was to examine the influences of basic personality traits, cognitive emotion regulation and interpersonal problems on the cognitive aspects of personality disorders. 1298 adult participants (411 males and 887 females) between the ages of 18 and 68 (M = 26.85, sd = 7.95) participated in the study. In the first part of the study, Inventory of Interpersonal Problems was adapted to Turkish, and psychometric properties of the adapted inventory as well as Cognitive Emotion Regulation Ques...
Representations of Personality Disorders Beliefs on Interpersonal Circumplex Model
Akyunus, Miray; Gençöz, Tülin (2016-06-01)
Cognitive Theory and Interpersonal Circumplex Model explaining cognitive and interpersonal patterns of personality disorders (PD) are well established in personality literature. The main objective of the study is to investigate the representations of personality beliefs defined by Cognitive Theory on the Interpersonal Circumplex space and to integrate these two models. Analyses were conducted with 962 adults of a community sample (302 men, 660 women) after the participants who are on psychiatric treatment o...
Examination of Personality Characteristics in a Turkish Sample: Development of Basic Personality Traits Inventory
Gençöz, Tülin (2012-01-01)
The aim of the present study was to test the cross-cultural validity of the five-factor nature of personality. For this aim, an indigenous, psychometrically strong instrument measuring the basic personality dimensions within Turkish culture and language was developed through three consecutive studies. The first study aimed to reveal the adjectives that have been most frequently used to define people in the Turkish culture. In the second study, factor analysis of these personality characteristics revealed bi...
Social comparison orientation mediates the association between HEXACO and self-presentation
Demir, Sila; Özkan, Türker; DEMİR, BAŞAR (2022-04-01)
Various researchers have investigated the personality correlates of defensive and assertive self-presentation. Yet, only a few studies go beyond the direct relationships and examine the underlying mechanism. The current study examines whether the social comparison orientation (SCO) mediates the relationship between personality and self-presentation. We also tested whether our proposed model is invariant across genders. We collected data from 496 individuals using the HEXACO personality inventory, the self-p...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
P. Karagöz and İ. H. Toroslu, “Personality Analysis Using Classification on Turkish Tweets,”
International Journal of Cognitive Informatics and Natural Intelligence
, vol. 15, no. 4, pp. 1–18, 2021, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/93959.