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Abstract
In an earlier study one of us had developed a model of influence spreading for analysing human behaviour and interaction with others in a social network. Here we apply this model and corresponding influence centrality measures to real data of mobile phone call detail records. From this we get structures of human ego-centric networks and use a simple model, based on the number of phone calls, to describe the strengths of social relationships. To analyse 48,000 egos in their ego-centric networks we define normalised out-centrality and in-centrality influence measures, by dividing with out-degree and in-degree, respectively. With these and the betweenness centrality measures, we analyse the influence spreading in the ego-centric networks under different scenarios of link strengths between individuals reflecting the network structure being either interaction or connectivity oriented. The model reveals characteristics of social behaviour that are not obvious from the data analysis of raw empirical data or from the results of standard centrality measures. A transition is discovered in behaviour from young to older age groups for both genders and in both normalised out-centrality and in-centrality as well as betweenness centrality results.
| Original language | English |
|---|---|
| Article number | 126524 |
| Journal | Physica A: Statistical Mechanics and its Applications |
| Volume | 588 |
| DOIs | |
| Publication status | Published - 15 Feb 2022 |
| MoE publication type | A1 Journal article-refereed |
Funding
The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Daniel Monsivais and Kimmo Kaski acknowledge support from the EU Horizon2020 project SoBigData++: European Integrated Infrastructure for Social Mining and Big Data Analytcss rant agreement ID: 871042.
Keywords
- Centrality measure
- Ego-centric network
- Influence spreading model
- Mobile phone call detail record
- Social network
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Dive into the research topics of 'Influence spreading model in analysing ego-centric social networks'. Together they form a unique fingerprint.Projects
- 1 Finished
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-: SoBigData-PlusPlus
Roy, C. (Project Member), Kaski, K. (Project Member) & Bhattacharya, K. (Project Member)
01/01/2020 → 31/12/2025
Project: EU H2020 Framework program