Pseudo-Cores: The Terminus of an Intelligent Viral Meme's Trajectory

TL;DR

This paper investigates the trajectory of viral memes in social networks by identifying pseudo-core shells that mimic core behavior, using shell-based hill climbing algorithms to predict meme spread paths.

Contribution

It introduces the concept of pseudo-cores and develops shell-based hill climbing algorithms to better understand and predict meme virality in social networks.

Findings

Pseudo-cores emulate core behavior in cascade size.

Algorithms outperform existing path-finding methods.

Pseudo-cores help predict meme spread trajectories.

Abstract

Comprehending the virality of a meme can help us in addressing the problems pertaining to disciplines like epidemiology and digital marketing. Therefore, it is not surprising that memetics remains a highly analyzed research topic ever since the mid 1990s. Some scientists choose to investigate the intrinsic contagiousness of a meme while others study the problem from a network theory perspective. In this paper, we revisit the idea of a core-periphery structure and apply it to understand the trajectory of a viral meme in a social network. We have proposed shell-based hill climbing algorithms to determine the path from a periphery shell(where the meme originates) to the core of the network. Further simulations and analysis on the networks behavioral characteristics helped us unearth specialized shells which we term Pseudo-Cores. These shells emulate the behavior of the core in terms of size of the cascade triggered. In our experiments, we have considered two sets for the target nodes, one being core and the other being any of the pseudo-core. We compare our algorithms against already existing path finding algorithms and validate the better performance experimentally.