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Modeling Periodic Impulsive Effects on Online TV Series Diffusion.

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Impulsive promotion significantly boosts TV series streaming, with viewing habits and online buzz being key drivers. Strategic timing of promotions, especially near update days, enhances audience engagement and predicts streaming trends.

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Area of Science:

  • Media Studies
  • Network Science
  • Data Science

Background:

  • Online broadcasting significantly impacts TV series production, distribution, and profitability.
  • Online word-of-mouth and on-demand streaming rates are critical for TV series diffusion and video supplier revenue.
  • Understanding streaming dynamics and forecasting trends is essential for online video platforms.

Purpose of the Study:

  • To investigate the effects of periodic impulsive stimulation and pre-launch promotion on on-demand streaming dynamics.
  • To model imbalanced audience distribution using an impulsive susceptible-infected-removed (SIR)-like model.
  • To analyze the correlation between online buzz volume and streaming fluctuations.

Main Methods:

  • Proposed a Periodic Impulsive SIR (PI-SIR) model to simulate audience dynamics and streaming fluctuations.
  • Utilized a coarse-to-fine, two-step fitting scheme to estimate model parameters using six South Korean TV series datasets.
  • Performed correlation analysis on online buzz volume using Baidu Index data.

Main Results:

  • Audience members exhibit consistent viewing habits, seeking new episodes on update days and then diminishing engagement.
  • Impulsive stimulation intensity, initial audience size, and online buzz significantly influence on-demand streaming diffusion.
  • On-demand streaming fluctuations show a high correlation with online buzz fluctuations.

Conclusions:

  • Investing in promotion near update days and strong pre-launch campaigns are effective strategies to stimulate audience attention and diffusion.
  • Avoid promoting multiple popular TV series on the same update day to prevent audience fragmentation.
  • Inter-period accumulation serves as a feasible forecasting tool for on-demand streaming trends, and social media buzz can evaluate advertising value.