Research Article Open Access

An On-line Analytical Processing (OLAP) Aggregation Function for Rising Aspects in Collaboration and Social Networks

Waqas Nawaz1, Kifayat Ullah Khan2 and Muhammad Shoaib Siddiqui1
  • 1 Islamic University of Madinah, Saudi Arabia
  • 2 National University of Computer and Emerging Sciences, Pakistan


The overwhelming usage of social and collaboration networks provides the opportunity to analyze evolution of relationships among individuals, like celebrities or co-authors. Discovering such phenomenon in large complex networks is non-trivial due to their large sizes. In this situation, the aggregation functions used in OLAP, are useful to analyze the summarized data. OLAP has successfully proven its worth on multidimensional or complex networks. However, existing aggregations in the current OLAP systems do not produce versatile results in case of social and collaboration networks. This happens because said type of networks have structural connectivity/links among nodes, which cannot be considered by OLAP during its execution. In this situation, a useful discovery in terms of identifying pairs of nodes whose relationships is emerging in recent time, is missed. Such discovery of pairs of nodes is important for various applications such as targeted marketing, future joint partnerships and predicting future correspondence to name a few. In this study, we call such pairs as Rising_Pairs and propose an aggregation function for performing OLAP on network data whose historical information is maintained over a period of times. Using structural information, Rising_Pairs, our proposed aggregation function, discovers the strongly coupled pairs in a network data by emphasizing their recent interactions and attribute similarities. In this way, useful information related to strongly coupled pairs in a network is identified. To verify the effectiveness of our proposal, we implemented it on various types of real-world networks like Facebook, Digital Bibliography and Library Project (DBLP) and Global Positioning System (GPS) trajectory datasets and observed interesting patterns.

Journal of Computer Science
Volume 16 No. 6, 2020, 735-748


Submitted On: 11 March 2020 Published On: 10 June 2020

How to Cite: Nawaz, W., Khan, K. U. & Siddiqui, M. S. (2020). An On-line Analytical Processing (OLAP) Aggregation Function for Rising Aspects in Collaboration and Social Networks. Journal of Computer Science, 16(6), 735-748.

  • 1 Citations



  • Social Networks
  • OLAP
  • Aggregation Functions
  • Data Analysis
  • Bibliographic Data
  • Rising Phenomenon
  • Temporal Trends
  • Summarization