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Summary
This summary is machine-generated.

Multiple exposures to a message on social networks increase forwarding likelihood, but only up to two exposures. Beyond this peak, additional views do not enhance the chance of information diffusion.

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Area of Science:

  • Social Network Analysis
  • Information Diffusion Dynamics
  • Computational Social Science

Background:

  • Social contagion theories often assume a cumulative effect on behavior and influence spread.
  • Empirical validation of cumulative effects in large-scale information diffusion on social networks remains limited.

Purpose of the Study:

  • To empirically investigate the existence and extent of the cumulative effect in information diffusion.
  • To analyze user forwarding preferences and message popularity variations within diffusion networks.

Main Methods:

  • Analysis of a population-scale dataset from a major Chinese microblogging platform.
  • Construction and examination of message diffusion networks, mapping user interactions and forwarding relationships.
  • Investigation of structural motifs and temporal patterns within diffusion processes.

Main Results:

  • Multiple exposures to a message significantly increase the probability of forwarding.
  • The positive effect of exposure on forwarding probability plateaus after two exposures, questioning the cumulative effect hypothesis.
  • Structural and temporal network characteristics offer insights into message popularity variations.

Conclusions:

  • The cumulative effect in information diffusion is limited, with diminishing returns after initial exposures.
  • Understanding user preferences and diffusion network structures is crucial for explaining message popularity.
  • Findings contribute to a nuanced understanding of information spread dynamics on social media.