Computer Science, Artificial Intelligence, Computer Vision and Pattern Recognition, Multidisciplinary
2
Scopus Publications
50
Scholar Citations
3
Scholar h-index
1
Scholar i10-index
Scopus Publications
I Feel it in Your Fingers: Inference of Self-Assessed Personality Traits from Keystroke Dynamics in Dyadic Interactive Chats Abeer A. N. Buker, Alessandro Vinciarelli 2021 9th International Conference on Affective Computing and Intelligent Interaction Acii 2021, 2021 The question at the core of this work is whether it is possible to infer self-assessed personality traits from keystroke dynamics (the way people type on a keyboard). The experiments were performed over a corpus of 30 dyadic chats, 60 participants in total, collected through a text-based chat interface similar to those available in popular products (e.g., Skype). The results show that keystroke dynamics (typing speed, frequency of deletions, etc.) allow one to infer whether someone is below median or not along the Big Five personality traits. In particular, it was possible to achieve F1 Scores up to 72% depending on the trait. To the best of our knowledge, this is the first work aimed at recognizing personality traits through analysis of keystroke dynamics.
Type like a man! Inferring gender from keystroke dynamics in live-chats Abeer A. N. Buker, Giorgio Roffo, Alessandro Vinciarelli IEEE Intelligent Systems, 2019 Nonverbal communication is often referred to as body language, an expression that accounts for the major role that the body plays in interaction, especially when it comes to conveying socially and psychologically relevant information. Such a role is the result of a long evolutionary process that has shaped the brain to be sensitive to the signals sent by co -located others more than to any other signal in the environment (e.g., the human voice is one of the sounds that requires the lowest energy to be heard). Still, despite such an evolutionary history, people communicate increasingly more frequently through technologies that prevent, partially or totally, the use of nonverbal behavior. For example, phones allow one to use nonverbal vocal behavior (laughter, sobbing, intonation, pauses, etc.), but not facial expressions or gestures. In the context outlined above, it is important to investigate whether body language is still possible when the body cannot play its role. For this reason, this article has shown that there is a significant interplay between gender and keystroke dynamics at least in the case of interactions taking place through live -chat interfaces. In particular, the experiments have shown that it is possible to infer the gender of a person from her typing behavior with an accuracy higher than 95%. In addition, the experiments have shown that such a performance relies mostly on features (physical and machine detectable measures extracted through a key -logging platform) that account for implicit and explicit expression of affect, social presence, and planning problems. According to a recent survey, 36% of adults owning a smartphone use messaging systems (https://www.pewinternet.org/2015/08/19/mobilemessaging-and-social-media-2015D. In addition, The market for technologies supporting live -chats is expected to 40 50 60 grow with an average rate of 7.3% until 2023 when it is expected to reach a total volume close to one billion dollars per year (https://
RECENT SCHOLAR PUBLICATIONS
Reading between the lines: Automatic inference of self-assessed personality traits from dyadic social chats A Buker, A Vinciarelli Computers in Human Behavior: Artificial Humans 1 (2), 100026 , 2023 2023.0 Citations: 2
I feel it in your fingers: the automatic analysis of dyadic online chats using typing behaviour AA Buker University of Glasgow , 2023 2023.0
Who is typing? Automatic gender recognition from interactive textual chats using typing behaviour A Buker, A Vinciarelli Enabling Machine Learning Applications in Data Science: Proceedings of Arab … , 2021 2021.0 Citations: 5
I Feel it in Your Fingers: Inference of Self-Assessed Personality Traits from Keystroke Dynamics in Dyadic Interactive Chats A Buker, A Vinciarelli Proceedings of the IEEE International Conference on Affective Computing and … , 2021 2021.0 Citations: 7
Type like a man! inferring gender from keystroke dynamics in live-chats AAN Buker, G Roffo, A Vinciarelli IEEE Intelligent Systems 34 (6), 53-59 , 2020 2020.0 Citations: 36
Developing a Mobile Application for the Nonclinical Population to Promote Positive Mental Attitude (PMA) Through the Application of Behavioural Change Techniques (BCTs) and … A Buker University of Strathclyde , 2018 2018.0
Keep The Peace: Inference Of Conflict Management Style From Typing Behavior in Interactive Online Chats A Buker, A Vinciarelli, N Aloshban Available at SSRN 6118347 , 0
MOST CITED SCHOLAR PUBLICATIONS
Type like a man! inferring gender from keystroke dynamics in live-chats AAN Buker, G Roffo, A Vinciarelli IEEE Intelligent Systems 34 (6), 53-59 , 2020 2020.0 Citations: 36
I Feel it in Your Fingers: Inference of Self-Assessed Personality Traits from Keystroke Dynamics in Dyadic Interactive Chats A Buker, A Vinciarelli Proceedings of the IEEE International Conference on Affective Computing and … , 2021 2021.0 Citations: 7
Who is typing? Automatic gender recognition from interactive textual chats using typing behaviour A Buker, A Vinciarelli Enabling Machine Learning Applications in Data Science: Proceedings of Arab … , 2021 2021.0 Citations: 5
Reading between the lines: Automatic inference of self-assessed personality traits from dyadic social chats A Buker, A Vinciarelli Computers in Human Behavior: Artificial Humans 1 (2), 100026 , 2023 2023.0 Citations: 2
I feel it in your fingers: the automatic analysis of dyadic online chats using typing behaviour AA Buker University of Glasgow , 2023 2023.0
Developing a Mobile Application for the Nonclinical Population to Promote Positive Mental Attitude (PMA) Through the Application of Behavioural Change Techniques (BCTs) and … A Buker University of Strathclyde , 2018 2018.0
Keep The Peace: Inference Of Conflict Management Style From Typing Behavior in Interactive Online Chats A Buker, A Vinciarelli, N Aloshban Available at SSRN 6118347 , 0
