NITLE Shared Academics: Networks and the Liberal Arts


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Networks provide educators in the liberal arts tradition with an excellent opportunity to incorporate technology and technical ideas into the arts and humanities curriculum. How can we incorporate networks and network thinking to foster multidisciplinary learning at the undergraduate level? Tom Lombardi, assistant professor of computing and information studies at Washington & Jefferson College explores this question and demonstrates the exciting role networks can play in liberal education. Hosted by NITLE Shared Academics.

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  • John Major, 15th Century, Square of Opposition, Image in Public Domain
  • Graph theory gives us a powerful way to model many kinds of real world networks with a rather small set of concepts.We only need Vertices to represent what we want capture in the real world and edges to represent the relationships between those things.
  • Creative Commons image-This constitutes a kind of motif as these saints are portrayed very, very often together
  • Copyright Thomas Lombardi
  • Although we tend to think reflexively of Facebook when we discuss social networks, these techniques have existed since well before Mark Zuckerberg was born. Social network analysis is a mature discipline that attempts to understand human behavior with networks.Padgett and Ansell(1993), Robust Action and the Rise of the Medici, analyze the social network of the Medici Family in Florence in the 1420s and 1430s.They built the social network from marriage contracts and business contracts. They attribute the rise of the Medici family to the advantages conferred on them by their position in the network of families in Florence at the time.The size of the circle reflects each family’s centrality on the network as measured by betweenness.Betweenness measures a node’s ability to control the flow of information to other nodes. In 3 cases, the Medici are in the position to broker on behalf of other families. Moreover, the fact that they have a less dense network gives them freedom to build a broad coalition. Compare this to the highly clustered system of old noble Florentine families at the bottom of the network. You will recognize some of the names from important contributions to the city of Florence such as the Strozzi Chapel in Santa Maria Novella. These old families sit in the most highly clustered part of the network. These families were extremely inefficient in their political organization due to this structure. Their rivalries kept them from properly organizing against the powerful Medici party. Strangely enough, as Padgett and Ansell point out, the Medici were neither the wealthiest nor did they hold the most political offices in the city. They had what social network analysts call social capital that they used to distribute favors in a broad system of patronage.Exiled 1433; returned in 1434 due to capital flight. When he left, so did the money.
  • Copyright Thomas Lombardi
  • Moretti does a brilliant job of establishing how Hamlet is caught between two worlds.-The court centered around Claudius-The state centered around HoratioMoretti wishes that he could model these with weight and direction.Those working on novels incorporated weight by calculating the volume of speech between characters.Although this is innovative and interesting, weighting purely by volume has some problems.Sometimes people just babble. Sometimes a single word or sentence undermines important plot points.
  • Fragonard’s illustration of Letter 44 from 1796 version of the novel. This image is in the public domain.Unfortunately, it wasn’t immediately obvious how we handle this in the classroom.I thought about simulating some networks and I thought about trying to build something from other networks, but nothing seemed quite right.Moreover, I was extremely picky about what I wanted.The material had to structural variety meaning it couldn’t look the same over time. I wanted fairly clear transitions that we could try to connect to the story.The network had to show signs of evolution that brought up features common in the dynamics of other networksDisconnected to connectedQuickly changing properties of nodesIt had to include a several examples of triadic closure.It has to be simple to model – only 13 charactersThe story had to be thematically relevant including things like gossip, different kinds of networks, the nature of social networks, etc.After researching and creating networks for several epistolary novels, I settled on Dangerous Liaisons because it came closest to this set of features. In fact, it met them all.Dangerous Liaisons is a french epistolary novel written by Pierre Choderlos de Laclos that reveals the inner world of people trying to flaunt the social conventions and mores of their time.In many cases, the characters are trying to seduce other characters in their social network without paying the penalties of such actions.Through a series of letters the author reveals how difficult it is to rise above the bounds set by our social networks.
  • Simple model that includes direction, weight, temporal element, and thematic relevance. Disease, contact, gossip, and even competing interpretations of the network itself.A software package called Pajek let’s us build time event networks that help us to trace the development and evolution of any kind of network.So we built a time event network of the letters in Dangerous Liaisons.
  • I needed a decent test case and Les Liaisons dangereuses. Copyright Thomas LombardiLaclos’ brilliant 18th century novel was by far the most interesting case.1- 175 letters, it was of sufficient length to build a complex network including a time-event network to study evolution.2- It had a complex plot3- It had a reasonable number of characters4- It demonstrated features interesting to network science.betweenness, brokerage, triadic closure5- Public editions of the text exist
  • Danceny’s letter gives us an opportunity to discuss gender homophily.Much of this plot revolves around coupling. Does the pattern of links between men and women bear this out?
  • 174 links – total is 175 but we throw out the one from anonymous7 female characters7/13 = 0.54ff = .296 male characters6/13 = 0.46mm = .21Cross gender About half .587 links cross gender10 links between men54 links between women174-64 = 100 links cross gender57% of links are cross-gender – no homophily certainly. Relatively close to random.
  • NITLE Shared Academics: Networks and the Liberal Arts

    1. 1. Networks and the Liberal Arts Thomas Lombardi Assistant Professor, Computing and Information Studies, Washington & Jefferson College
    2. 2. Networks and the Liberal Arts NITLE Shared Academics Seminar October 15th, 2013 2:00 PM Dr. Thomas Lombardi Assistant Professor Computing & Information Studies Washington & Jefferson College
    3. 3. From Graph Theory to Networks Vertices People Alice Chuck Edges Friendship Bob
    4. 4. Constructing Networks: Method Christ Mary Giotto, Crucifixion, Tempera on wood, ca. 1290-1300. Source: John
    5. 5. Network of Saints in Images of St. Francis
    6. 6. 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
    7. 7. The Rhyme Scheme of The Raven
    8. 8. Network of Characters in Hamlet Franco Moretti. Network Theory, Plot Analysis. New Left Review. 2011.
    9. 9. Dangerous Liaisons: Networks & Liberal Education Encourages multidisciplinary thinking Integrates critical-thinking skills: Quantitative Reasoning Visual Acumen Analytical Thinking Communication Promotes the exploration of values: Diversity via Homophily Values in Engineering Image from Fragonard, Letter 44 of 1796 version of the Novel. Website:
    10. 10. Dangerous Liaisons: Networks & Liberal Education Vicomte de Valmont Marquise de Merteuil Letter 44:The Vicomte de Valmont to the Marquise de Merteuil
    11. 11. Dangerous Liaisons: Networks & Liberal Education
    12. 12. Skills Integration: Quantitative, Visual, Analytical Gender homophily in network of correspondence from Susannah Gunning’s Barford Abbey (1767). Gender and the novel Measurement for homophily p2 + 2pq +q2 = 1 p: probability of male node q: probability of female node Example p=5/11 (0.45) q=6/11 (0.54) 2pq = 2(0.45)(0.54) = 0.48 We expect roughly 4/8 links m/f We actually have only 1/8.
    13. 13. Diversity via Gender Homophily More links than expected between female and male correspondents No evidence of gender homophily Consistent with plot; seduction Absence of gender homophily in network of correspondence from Dangerous Liaisons. Techniques apply to directed communications old and new; fictional and historical.
    14. 14. Relevance of Networks in Liberal Education Larry Abramson, NPR, How a Look at your Gmail Reveals the Power of Metadata Cesar Hidalgo, MIT Media Lab Without the content: important people important groups identifying information
    15. 15. Relevance of Networks in Liberal Education Networks and Civic Life Terrorist Networks Network analysis of voting Network economics Networks in the Sciences Food Webs Systems Biology Complex Systems William Cronon, “Only Connect…” The Goals of a Liberal Education The liberal arts approach to networks
    16. 16. Group Discussion: Networks & Education • How might your institution use networks and network thinking to create multidisciplinary learning opportunities for students? • In what ways could network thinking enhance the value of liberal arts education for the 21st century student? • In what areas might you experiment with it? • Questions, Comments, Jokes, Recipes?