| Autor: |
Upasana Sharma, Rajnish Kumar |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). |
| DOI: |
10.1109/icrito51393.2021.9596353 |
| Popis: |
Social Network analysis starts with the identification of most influential nodes. However, it is always necessary to define centrality which is used for the creation of central node within the network and the type of transactional information being done within the network. In this paper, we identify influential nodes and hubs which are socially important, the nodes at the center of network is identified as most influential node in social networks which generally generate data online using principal component centrality (PCC). Hence, in order to establish the relationship and the comparison between principal component centrality with eigen vector and eigen value data (EVC), the actual measurement of node influence by integrity of their position in a network. We have taken data set from Kaggle and experiment was done on this dataset for online social network. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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