Exploring Temporal Asymmetry in Human Behavior in Social Media Platforms

Area of Science:

• Information Science
• Social Computing
• Behavioral Economics

Background:

• Growing interest in understanding complex human behavior, particularly behavioral asymmetry.
• Behavioral asymmetry is a significant topic with theoretical and practical implications.
• Need for scholarly attention on asymmetries within critical time periods.

Purpose of the Study:

• Investigate asymmetries in human behavior during critical time periods.
• Analyze asymmetrical human activities on social media platforms surrounding pivotal temporal moments.
• Examine deadline-influenced behavior in social media contexts.

Main Methods:

• Comprehensive analysis of datasets from Douban movie reviews and Weibo comments.
• Focus on data related to a major product launch event.
• Proposal and application of a queue model incorporating neighbor effects and critical temporal frames.

Main Results:

• The proposed queue model effectively captures observed patterns of temporal asymmetry.
• Demonstrated the model's accuracy in reflecting deadline-influenced human behavior.
• Identified significant asymmetrical human activities on social media during critical time periods.

Conclusions:

• The queue model is a valuable tool for understanding deadline impacts on social media behavior.
• Human behavior exhibits distinct asymmetries influenced by critical temporal frames.
• Further research can explore these dynamics in various online environments.