| Abstrakt: |
Numerous studies in the context of Indian migration have been conducted to understand the change in underlying trends, its impact on the Indian economy, etc. Still, none has deployed network analytics to uncover the migration data’s hidden structures and patterns using six migration factors—birth, employment, household, education, marriage, and business, provided with census data. We leverage social networks’ power to identify the central factors of the migration process, exploiting the direction and capacity of flow between Indian states. We found that Maharashtra, Karnataka, and Delhi are preferred places for male and female immigrants, as revealed by the rankings based on weighted in-degree and Pagerank centralities. The movement is primarily attributed to marriage and employment factors for all migrants. On the contrary, rankings by weighted out-degree and local reachability show that Uttar Pradesh is facing maximum emigration for all the factors. Further, the community structures in the networks reveal that clusters of states are formed around the top rankers—Delhi, Maharashtra. Also, it is observed that Delhi and Uttar Pradesh, being the popular states for immigration and emigration, respectively, are always part of the same community for all factors. |
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