International Journal of Information and Communication Technology Research
مجله بین المللی ارتباطات و فناوری اطلاعات
International Journal of Information and Communication Technology Research
Engineering & Technology
http://ijict.itrc.ac.ir
1
admin
2251-6107
2783-4425
doi
1652
25391
en
jalali
1401
11
1
gregorian
2023
2
1
15
1
online
1
fulltext
en
Recognizing Personality Traits using Twitter & Facebook for Arabic Speaking Users in Lebanon
فناوری اطلاعات
Information Technology
پژوهشي
Research
<span style="font-size:10pt"><span style="text-justify:inter-ideograph"><span style="font-family:"Times New Roman",serif"><b><span style="font-size:9.0pt">Nowadays, Social media is heading toward personalization more and more. People express themselves and reveal their beliefs, interests, habits, and activities, simply giving a glimpse of their personality traits. The thing that pushed us toward further investigating the mutual relation between personality and social media, taking into consideration the shortage in covering such important topic, especially in rich morphological languages. In this paper, we work on the connection between usage of Arabic language on social outlets (mainly Facebook and Twitter) and personality traits</span></b><b><span style="font-size:9.0pt">. We indicate the personality traits of users based on the information extracted from their activities and the content of their posts/tweets in Social Networks. We use linguistic features, beside some other features like emoticons. </span></b><b><span style="font-size:9.0pt">We gathered personality data using Arabic personality test based on Myers-Briggs Type Indicator (MBTI), which contains Thinking, Feeling, Intuition, Introversion, Sensation, Extroversion, Perceiving and Judgement traits. We collected our dataset from <span style="color:black">522 </span>volunteers<span style="color:black">, </span>who permitted us to crawl their tweets and posts in Twitter and Facebook. Analysis of this dataset proved that some linguistic features could be used to differentiate between different personality traits. We used and implemented Deep Learning, and BERT to reveal personality and create a model for this purpose. Up to our knowledge, this is the first work on detection of personality traits from social network’s data in Arabic language.</span></b></span></span></span><br>
Personality Detection, Social Networks, Arabic Language Processing, Linguistic Features
45
55
http://ijict.itrc.ac.ir/browse.php?a_code=A-10-4416-1&slc_lang=en&sid=1
Mokhaiber
Dandash
mdnahle@yahoo.com
10031947532846002121
10031947532846002121
No
Electrical and Computer Engineering Artificial intelligence and robotics group Ph.D. Student, University of Tehran Beirut, Lebanon
Masoud
Asadpour
asadpour@ut.ac.ir
10031947532846002122
10031947532846002122
Yes
Electrical and Computer Engineering Assistant Prof. Director of Social Networks Lab University of Tehran Tehran, Iran