1 / 19

Networks and the Digital Humanities

Networks and the Digital Humanities. THATCamp Pittsburgh October 5 th and 6 th , 2013 Dr. Elaine Frantz Parsons Associate Professor of History Duquesne University & Dr. Thomas Lombardi Assistant Professor Computing & Information Studies Washington & Jefferson College.

valiant
Download Presentation

Networks and the Digital Humanities

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Networks and the Digital Humanities THATCamp Pittsburgh October 5th and 6th, 2013 Dr. Elaine Frantz Parsons Associate Professor of History Duquesne University & Dr. Thomas Lombardi Assistant Professor Computing & Information Studies Washington & Jefferson College

  2. From Graph Theory to Networks People Vertices Alice Chuck Edges Friendship Bob

  3. Constructing Networks: Method Christ Mary John Giotto, Crucifixion, Tempera on wood, ca. 1290-1300. Source: commons.wikimedia.org

  4. Network of Saints in Images of St. Francis

  5. Analyzing Network Models Centrality Degree Betweenness Weighted Edges Directed Edges Clustering Affiliation Networks Community Detection

  6. Degree Centrality Number of links connected to a node Node A has a degree centrality of 6 Nodes B, C, D, E, F, G: degree of 1 Degree centrality measures the ease with which information can reach a particular node

  7. Betweenness Centrality % of shortest paths running through a node H has a low degree, but high betweenness Cut vertices Bridges Betweenness confers the ability to control the flow of information in a network

  8. Network of Characters in Hamlet Franco Moretti. Network Theory, Plot Analysis. New Left Review. 2011.

  9. Edge Weights Some links between nodes are more important than others Edges can be weighted to record the importance of a connection For example, some characters interact more than others in a novel Each interaction increases the weight of the link between characters

  10. The Rhyme Scheme of The Raven

  11. Edge Direction Vicomte de Valmont Marquise de Merteuil Letter 44:The Vicomte de Valmont to the Marquise de Merteuil

  12. Dangerous Liaisons: Network of Letters

  13. Clustering Some nodes are situated in extremely dense parts of the network Node E is entirely embedded: all of the node’s neighbors are neighbors Other nodes are in relatively sparse parts of the network None of I’s neighbors are neighbors

  14. Network of Relationships in Florence Padgett & Ansell, 1993 Network structure accounts for Medici rise to power in the 1430s Brokerage Constraints amongst old families of Florence made them ineffective Clustering

  15. Affiliation Networks Networks often track more than 1 kind of entity Students and their classes These networks are flexible because they can be transformed into a network of students and a network of classes Networks can also have more than one type of link: multi-relational networks

  16. Union County Affiliation Network

  17. Community Detection In large networks, we frequently want to find the dense clusters of nodes These often represent communities of interest These communities often relate to other groups in interesting ways

  18. Communities within William Faucett’s K-Neighbors

  19. Hands-on Activities Flash drives contain some of the networks we’ve discussed Perform some basic analysis of a network with Pajek Create your own network model for analysis in Pajek Experiment with networks

More Related