Social networking analysis in Politics

Background

A political body such as the city council, state government or the federal government is supposed to discuss each issue that comes up for legislation and decide the same on its merits. But in the recent past, instead of political debates, political ties have started determining whether a bill would be passed or not. 

Hypothesis

There are groups within each legislative body with one or few influential leaders who determine the voting of that group.

The objective of doing this network analysis is to develop this model in each legislative body, verify this model using past voting on bills and then use the same to predict the future outcome of voting. The emphasis of the project is on identifying influential groups and/or leaders who have the last word on any issue. This will provide the following advantages:

1.   Allow corporations to better target their lobbying

2.  Allow voters to identify the decision makers and the power of their elected candidates

Data Needed

The data will be collected as follows:

1.   A questionnaire given to the politicians asking them to indicate their frequency of interaction with other politicians – socially and professionally. Besides, for each politician, the following attributes will be collected: political affiliation, region, educational background and views on abortion, gay marriages and economic policies. This data might be difficult to get for all politicians due to personal reservations

2.   To fill in the data gaps, a similar data will be collected from members of local newspapers who report on political affairs. This should be fairly easy to obtain

3.   Data on voting done by each member in the past. This data will be available in the archives unless  the voting was anonymous, in which case again the journalists will have to be asked

 Important Network Measures

Based on the data, network maps will be plotted. Using classification by attributes, the major groups as well as the influential people will be identified. Measures such as density can be used to verify this. Then using Eigen vectors, the most influential people in that group will be identified. This can be verified by measures such as degree.

  

Conclusion

 
Thus, using SNA the groups as well as the influential people will be identified. It will also help in identifying the attributes of the most influential people. Thereafter, the outcome of voting on bills can be predicted based on the views of the influential people.