Malatya Centrality based Algorithm for Positive Influence Dominating Set

Social networks are used by individuals not so much for communication as for influencing each other. Social networks are modelled as graphs, and a special Dominating Set is obtained from the resulting graph. A new algorithm has been proposed for the Dominating set, where at least half of the neighbours of each node are elements of the Dominating Set. This algorithm is called as Malatya Positive Influence Algorithm, and its results for some graphs are given in this study.

Authors

Institutions

Publication Details

Journal
Computer Science
Published
2026-04-07
DOI
https://doi.org/10.53070/bbd.1905449
Primary Topic
Game Theory and Voting Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Malatya Centrality based Algorithm for Positive Influence Dominating Set

Maral Kıyıcı
Computer Science
Game Theory and Voting Systems
article

Malatya Centrality based Algorithm for Positive Influence Dominating Set

Maral Kıyıcı
article en

Abstract

Social networks are used by individuals not so much for communication as for influencing each other. Social networks are modelled as graphs, and a special Dominating Set is obtained from the resulting graph. A new algorithm has been proposed for the Dominating set, where at least half of the neighbours of each node are elements of the Dominating Set. This algorithm is called as Malatya Positive Influence Algorithm, and its results for some graphs are given in this study.

Computer Science(2026)
Inonu University (TR)
Reduced inequalities
Openalex Percentile: Top 20%
Game Theory and Voting Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.