Project Title

Social Network Analysis is USA Supreme court rulings

Presenters

Academic department under which the project should be listed

CCSE - Data Science and Analytics

Faculty Sponsor Name

Dr. Joseph DeMaio

No. This is a class presentation project.

Abstract (300 words maximum)

With the emergence of social media networks such as LinkedIn, Facebook, Twitter and many more, greater research attention is currently being channeled to social networks. Link prediction is increasingly a topic of great interest to many. The topic focusses on social network analysis. The basic idea is that by exploiting networks information of current networks, especially the characteristics of the vertices and edges, we can predict imminent relationships that will be formed in the future by the network. This paper seeks to discuss the current popular link prediction methods for social networks. Link prediction has many applications. Some of these include online advertisement, disruption of terrorist networks and many more. The project is based on data collected from US Supreme court rulings from the years 1946 to 2015. Consider the judge’s problem of identifying precedent court cases that are most relevant and important to the current case. The network that will be created will be as follows: Given a new court case, the importance of a previous case is to look at the network of citations used in related cases. That is, if a particular case cites a previous case to help support its argument, then a link exists from between the two cases in the citation network. In this project, we seek to use social network analysis in analyzing US supreme court rulings. Some of the metrics that will be used include vertex centrality measures such as Betweenness, Closeness, and Degree. We also seek to predict the cases that will continue to have an impact on US Supreme court rulings in the future by applying link prediction metrics.

Project Type

Poster

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Social Network Analysis is USA Supreme court rulings

With the emergence of social media networks such as LinkedIn, Facebook, Twitter and many more, greater research attention is currently being channeled to social networks. Link prediction is increasingly a topic of great interest to many. The topic focusses on social network analysis. The basic idea is that by exploiting networks information of current networks, especially the characteristics of the vertices and edges, we can predict imminent relationships that will be formed in the future by the network. This paper seeks to discuss the current popular link prediction methods for social networks. Link prediction has many applications. Some of these include online advertisement, disruption of terrorist networks and many more. The project is based on data collected from US Supreme court rulings from the years 1946 to 2015. Consider the judge’s problem of identifying precedent court cases that are most relevant and important to the current case. The network that will be created will be as follows: Given a new court case, the importance of a previous case is to look at the network of citations used in related cases. That is, if a particular case cites a previous case to help support its argument, then a link exists from between the two cases in the citation network. In this project, we seek to use social network analysis in analyzing US supreme court rulings. Some of the metrics that will be used include vertex centrality measures such as Betweenness, Closeness, and Degree. We also seek to predict the cases that will continue to have an impact on US Supreme court rulings in the future by applying link prediction metrics.