relation: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/2790/
title: Targeted Misinformation Blocking on Online Social Networks
creator: Pham, Canh V.
creator: Phu, Quat V.
creator: Hoang, Xuan Huan
subject: Information Technology (IT)
description: In this paper, we investigate a problem of finding smallest set of nodes to remove from a social network so that influence reduction of misinformation sources at least given threshold γ, called Targeted Misinformation Blocking (TMB) problem. We prove that TBM is #P-hard under LT model. For any parameter � ∈ (0,γ), we designed Greedy algorithm which return the solution A with the expected influence reduction greater than γ−�, and the size of A is within factor 1+ln(γ/�) of the optimal size. To speed-up Greedy algorithm, we designed an efficient heuristic algorithm, called STBM algorithm. Experiments were conducted on real world networks which showed the effectiveness of proposed algorithms in term of both effectiveness and efficiency.
date: 2018-03-19
type: Conference or Workshop Item
type: PeerReviewed
format: application/pdf
language: en
identifier: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/2790/1/TBM_correct.pdf
identifier:   Pham, Canh V. and Phu, Quat V. and Hoang, Xuan Huan  (2018) Targeted Misinformation Blocking on Online Social Networks.  In: 10th Asian Conference on Intelligent Information and Database Systems (AIIDS), 19-21 March 2018, Dong Hoi City, Vietnam.