The document discusses analyzing Facebook data to test hypotheses about gender differences in migration patterns and social network strength. It finds that the percentage of female migrants is less than 48% according to UN statistics, and that males build stronger social networks than females as measured by mutual friend relationships. The analysis had some limitations including a small and biased sample size as well as tool restrictions.

1. By
Shweta Singh
Shazia Ilahi
Krishnaveni Ganapathi
*

2. • Feminization of Migration
• Network Strength: Male vs Female
Related research
• Research by the Population Division of the United Nations
Department of Economic and Social Affairs
• The role of Facebook users' self-systems in generating
social relationships and social capital effects
*Problem Definition

3. Null Hypothesis: H0: p = 0.48
(UN global migration statistics: 48% of the migrants are
females)
Alternate Hypothesis: Ha: p < 0.48 (We claim that
according to our face book data, the null hypothesis is
false)
*

4. *

5. *
Type 1 Error (α) = 0.0202 which is extremely small
Type II Error (β)

6. *
Null Hypothesis: H0: μ1-μ2 = 0 (Males
and
females are building their network with
equal strength)
Alternate Hypothesis: Ha: μ1-μ2 > 0
(Males are building a stronger network
than females)

7. *

8. *
Type 1 Error (α) = 0.0345; 0.01<p<0.05, there is a strong evidence against H0
Type II Error (β)

9. *

10. • The collected data was biased and very male centric
• For big data analysis, the sample size collected was very small
• Node XL tool is restricted in getting profile details on work and
education
• Sample data turned out to be Multiple non-linear regression
model which was not easy to deal with
Conclusion -
• Women who migrated < 48%
• Male have more mutual friend relationship strength then female
• Most migrated people are in age group between 18 -30
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