IEEE Systems, Man and Cybernetics Magazine - October 2022 - 44

Explainable
ArtificialIntelligenceBased
Privacy
Preservation
Approach for
Information
Dissemination on
Social Networks
An Incremental Technique
by Shoayee Dlaim Alotaibi and Kusum Yadav
T
his article aims to address the issues above by
defining a social network information transmission
model with the amalgamation of
explainable artificial intelligence (XAI) compatible
with the paranormal connection. It
suggests a way of information transmission called local
greedy that aids in the preservation of user privacy. Its
impact acts as a buffer between the conflicting interests of
privacy protection and information dissemination. Aiming
at the enumeration problem of seed set selection, an incremental
technique is presented for constructing seed sets to
Digital Object Identifier 10.1109/MSMC.2022.3188406
Date of current version: 20 October 2022
minimize time overhead; a local influence subgraph method
for computing nodes is also proposed to evaluate the
influence of seed set propagation rapidly. The group meets
privacy protection conditions. A strategy is presented to
determine the upper bound on the likelihood of a node
leaking state without resorting to the time-consuming
Monte Carlo approach with XAI on the crawled Sina Weibo
dataset. The suggested technique is validated experimentally
and by example analysis, and the findings demonstrate
its usefulness.
Introduction
The privacy of users in social networks includes personal
information and communication information. To ensure
44 IEEE SYSTEMS, MAN, & CYBERNETICS MAGAZINE October 2022
2333-942X/22©2022IEEE

https://orcid.org/0000-0002-6658-6839

IEEE Systems, Man and Cybernetics Magazine - October 2022

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