Evaluating the effectiveness of Network Centrality in the Context of Shakespear's Plays
Advisor Information
Sanjukta Bhowmick
Location
Milo Bail Student Center Council Room
Presentation Type
Oral Presentation
Start Date
8-3-2013 3:30 PM
End Date
8-3-2013 3:45 PM
Abstract
Networks are popular models for representing interactions between entities in systems, such as in sociology, bioinformatics and epidemiology. The entities in the networks are represented as vertices and their pair-wise interactions are represented as edges. Many network metrics such as degree centrality (number of connections of an entity) and betweenness centrality (number of shortest paths passing through the entity) have been developed to rank the entities according to their importance. In this presentation, we study the effectiveness of these metrics in closed-form social interactions— particularly in the context of Shakespeare’s dramas. In plays the dialogues amongst characters are very precise to express the gist of their interactions in a short time frame. We are interested in understanding how this sort of interaction differs in a qualitative sense from the interactions seen in social media such as Facebook and Twitter. Our observations show that the popular network metrics are not always successful in correctly identifying the lead characters of the play and in the presentation we discuss some of the new metrics that we have developed to address this issue.
Evaluating the effectiveness of Network Centrality in the Context of Shakespear's Plays
Milo Bail Student Center Council Room
Networks are popular models for representing interactions between entities in systems, such as in sociology, bioinformatics and epidemiology. The entities in the networks are represented as vertices and their pair-wise interactions are represented as edges. Many network metrics such as degree centrality (number of connections of an entity) and betweenness centrality (number of shortest paths passing through the entity) have been developed to rank the entities according to their importance. In this presentation, we study the effectiveness of these metrics in closed-form social interactions— particularly in the context of Shakespeare’s dramas. In plays the dialogues amongst characters are very precise to express the gist of their interactions in a short time frame. We are interested in understanding how this sort of interaction differs in a qualitative sense from the interactions seen in social media such as Facebook and Twitter. Our observations show that the popular network metrics are not always successful in correctly identifying the lead characters of the play and in the presentation we discuss some of the new metrics that we have developed to address this issue.