Exploring Temporal Asymmetry in Human Behavior in Social Media Platforms

TL;DR

This paper explores how human behavior on social media changes around important time points, using data from Douban and Weibo to develop a model that captures these patterns.

Contribution

The study introduces a novel queue model that captures temporal asymmetry in human behavior influenced by deadlines on social media.

Findings

The proposed queue model effectively captures observed patterns of temporal asymmetry in social media behavior.

Neighbor effects and critical temporal frames significantly influence individual task performance around deadlines.

The model provides insights into how deadlines shape human activities on social media platforms.

Abstract

With the continuous advancement of information technology, there has been a growing interest in understanding the complexities of human behavior. In particular, asymmetry in human behavior has emerged as a topic of significant theoretical and practical importance. This study focuses on investigating asymmetries in the context of critical time periods, an area that warrants immediate scholarly attention. To address this, we conduct a comprehensive analysis of datasets obtained from Douban movie reviews and Weibo comments related to a major product launch event, examining asymmetrical human activities surrounding pivotal temporal moments on these prominent social media platforms. In our exploration of behavior influenced by deadlines in social media, we propose a queue model that considers the interaction between neighbor effects and critical temporal frames in shaping individual task performance. Our results demonstrate the model’s effectiveness in accurately capturing observed patterns of temporal asymmetry, highlighting its potential as a valuable tool for understanding the impact of deadlines on human behavior in social media contexts.

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