Habituation Effect in Social Networks as a Potential Factor Silently Crushing Influence Maximisation Efforts
Jaroslaw Jankowski

TL;DR
This paper investigates how habituation in social networks diminishes message influence over time, affecting information spread and influence maximization efforts, and proposes sequential seeding to mitigate this effect.
Contribution
It introduces a model incorporating habituation effects into spreading processes and demonstrates how sequential seeding can reduce negative impacts on influence maximization.
Findings
Habituation significantly reduces network coverage even at low levels.
Decreased propagation probability impacts influence spread.
Sequential seeding mitigates habituation effects effectively.
Abstract
Information spreading processes are a key phenomenon observed within real and digital social networks. Network members are often under pressure from incoming information with different sources, such as informative campaigns for increasing awareness, viral marketing, rumours, fake news, or the results of other activities. Messages are often repeated, and such repetition can improve performance in the form of cumulative influence. Repeated messages may also be ignored due to a limited ability to process information. Learning processes are leading to the repeated messages being ignored, as their content has already been absorbed. In such cases, responsiveness decreases with repetition, and the habituation effect can be observed. Here, we analyse spreading processes while considering the habituation effect and performance drop along with an increased number of contacts. The the ability to…
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