Exploiting Social Networks for Large-Scale Human Behavior Modeling

2011 ◽  
Vol 10 (4) ◽  
pp. 45-53 ◽  
Author(s):  
Nicholas D. Lane ◽  
Ye Xu ◽  
Hong Lu ◽  
Andrew T. Campbell ◽  
Tanzeem Choudhury ◽  
...  
Keyword(s):  
Social Networks ◽  
Human Behavior ◽  
Large Scale ◽  
Behavior Modeling ◽  
Human Behavior Modeling

Human Behavior Modeling Method Based on the Causality Between the Situation and the Behavior

2011 ◽  
Vol 131 (3) ◽  
pp. 635-643 ◽  
Author(s):  
Kohjiro Hashimoto ◽  
Kae Doki ◽  
Shinji Doki ◽  
Shigeru Okuma ◽  
Akihiro Torii
Keyword(s):  
Human Behavior ◽  
Modeling Method ◽  
Behavior Modeling ◽  
Human Behavior Modeling

scholarly journals Reports of the AAAI 2009 Spring Symposia

AI Magazine ◽  
2009 ◽  
Vol 30 (3) ◽  
pp. 89
Author(s):  
Jie Bao ◽  
Uldis Bojars ◽  
Ranzeem Choudhury ◽  
Li Ding ◽  
Mark Greaves ◽  
...  
Keyword(s):  
Human Behavior ◽  
Predictive Analytics ◽  
Temporal Reasoning ◽  
Behavior Modeling ◽  
Event Processing ◽  
Human Behavior Modeling ◽  
Reasoning Systems ◽  
Learning By Reading ◽  
Human Teachers ◽  
Social Semantic Web

The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University's Department of Computer Science, was pleased to present the 2009 Spring Symposium Series, held Monday through Wednesday, March 23–25, 2009 at Stanford University. The titles of the nine symposia were Agents that Learn from Human Teachers, Benchmarking of Qualitative Spatial and Temporal Reasoning Systems, Experimental Design for Real-World Systems, Human Behavior Modeling, Intelligent Event Processing, Intelligent Narrative Technologies II, Learning by Reading and Learning to Read, Social Semantic Web: Where Web 2.0 Meets Web 3.0, and Technosocial Predictive Analytics. The goal of the Agents that Learn from Human Teachers was to investigate how we can enable software and robotics agents to learn from real-time interaction with an everyday human partner. The aim of the Benchmarking of Qualitative Spatial and Temporal Reasoning Systems symposium was to initiate the development of a problem repository in the field of qualitative spatial and temporal reasoning and identify a graded set of challenges for future midterm and long-term research. The Experimental Design symposium discussed the challenges of evaluating AI systems. The Human Behavior Modeling symposium explored reasoning methods for understanding various aspects of human behavior, especially in the context of designing intelligent systems that interact with humans. The Intelligent Event Processing symposium discussed the need for more AI-based approaches in event processing and defined a kind of research agenda for the field, coined as intelligent complex event processing (iCEP). The Intelligent Narrative Technologies II AAAI symposium discussed innovations, progress, and novel techniques in the research domain. The Learning by Reading and Learning to Read symposium explored two aspects of making natural language texts semantically accessible to, and processable by, machines. The Social Semantic Web symposium focused on the real-world grand challenges in this area. Finally, the Technosocial Predictive Analytics symposium explored new methods for anticipatory analytical thinking that provide decision advantage through the integration of human and physical models.

Mobile Sensing: Leveraging Machine Learning for Efficient Human Behavior Modeling

2020 ◽  
Author(s):  
Erin K. Barrett ◽  
Cameron M. Fard ◽  
Hannah N. Katinas ◽  
Charles V. Moens ◽  
Lauren E. Perry ◽  
...  
Keyword(s):  
Machine Learning ◽  
Human Behavior ◽  
Mobile Sensing ◽  
Behavior Modeling ◽  
Human Behavior Modeling

DEVS for Human Behavior Modeling in CGFs

2007 ◽  
Vol 4 (3) ◽  
pp. 196-228 ◽  
Author(s):  
Mamadou Seck ◽  
Norbert Giambiasi ◽  
Claudia Frydman ◽  
Lassaad Baati
Keyword(s):  
Human Behavior ◽  
Behavior Modeling ◽  
Human Behavior Modeling

scholarly journals Fostering Cyber-Physical Social Systems through an Ontological Approach to Personality Classification Based on Social Media Posts

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6611
Author(s):  
Alexandra Cernian ◽  
Nicoleta Vasile ◽  
Ioan Stefan Sacala
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Systems ◽  
Behavior Modeling ◽  
Human Behavior Modeling ◽  
Novel Approach ◽  
Ontological Approach ◽  
Social Media Platforms ◽  
Smart Communities ◽  
Personality Classification

The exponential increase in social networks has led to emergent convergence of cyber-physical systems (CPS) and social computing, accelerating the creation of smart communities and smart organizations and enabling the concept of cyber-physical social systems. Social media platforms have made a significant contribution to what we call human behavior modeling. This paper presents a novel approach to developing a users’ segmentation tool for the Romanian language, based on the four DISC personality types, based on social media statement analysis. We propose and design the ontological modeling approach of the specific vocabulary for each personality and its mapping with text from posts on social networks. This research proposal adds significant value both in terms of scientific and technological contributions (by developing semantic technologies and tools), as well as in terms of business, social and economic impact (by supporting the investigation of smart communities in the context of cyber-physical social systems). For the validation of the model developed we used a dataset of almost 2000 posts retrieved from 10 social medial accounts (Facebook and Twitter) and we have obtained an accuracy of over 90% in identifying the personality profile of the users.

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