1209: RECENT ADVANCES ON SOCIAL MEDIA ANALYTICS AND MULTIMEDIA SYSTEMS: ISSUES AND CHALLENGES An integrated approach: using knowledge graph and network analysis for harnessing digital advertisement Siraj Munir 1 & Rauf Ahmed Shams Malick 2 & Syed Imran Jami 1 & Ghufran Ahmed 2 & Suleman Khan 3 & Joel J. P. C. Rodrigues 4,5 Received: 7 October 2020 /Revised: 14 October 2021 /Accepted: 23 December 2021 # The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 Abstract Complex network analysis helps in finding hidden patterns within a graph network. This concept is extended for knowledge graphs to identify hidden concepts using state-of-the- art network analysis techniques. In this paper, a profiling knowledge graph is analyzed to identify hidden concepts which result in the identification of implicit communities within a campus network. The proposed work is verified with the interesting results achieved by applying different metrics using a state-of-the-art network analysis algorithm. The results of the proposed work are mapped in the domain of digital advertisement to answer intelligent semantic queries. Various factors of centrality measures identify the prospec- tive influencers within a campus network. Moreover, bridge analysis determines amplifier nodes in the knowledge graph that will help in the digital advertisement. The proposed work concludes with a discussion on link prediction. It shows the future interactions to design digital advertising campaigns through billboards. Keywords Knowledge graph . Network analysis . Community detection . Semantics 1 Introduction Semantics play a vital role in finding or mapping information among real-world entities. The semantic web is the area of computing that aids machines to digest real-world information. To achieve this task effectively semantic web uses different graph-based approaches like ontol- ogy, RDF, knowledge graph, etc. In this paper, network analysis approaches are used like centrality measures, community detection, and overlapping communities over the profiling Multimedia Tools and Applications https://doi.org/10.1007/s11042-021-11856-2 * Siraj Munir sirajmunir93@gmail.com Extended author information available on the last page of the article