Graphing Influence

As today seems to be the day of cool visualizations on this blog, so on this note I’d like to highlight a really cool way of analyzing the influence of various people (philosophers, coding languages, etc) on history.

One of the basic strategies is to feed the information in Wikipedia info-boxes into a computer program called gephi that creates graphs of influence. The more connections a particular node has the bigger it appears, and distinct groupings of objects have the same color. I won’t reproduce the images here because they are typically so big (>10MB) but they are quite fascinating so here is a list of links to the relevant posts.

  • Graphing the history of philosophy by Simon Raper. Note how the the algorithm successfully manages to recognize distinct schools just by analyzing the number of connections within them. The biggest nodes are those of Plato, Aristotle, Kant, Hegel, Nietzsche, Marx and Schopenhauer which is broadly consistent with general informed opinion on the greatest voices in Western philosophy.
  • Following up on the The Graph of Ideas by Griff’s Graphs (who is also the author of all subsequent graphs linked to here). It goes beyond the above by also including authors (including sci-fi/fantasy) and comedians. We get an idea of the most influential authors – Hemingway, Kafka, Dostoevsky, Faulkner, Borges, Nabokov, Stephen King, H.P. Lovecraft; though the Big 7 philosophers both within philosophy and overall.
  • This was followed up by a Graph of Ideas 2.0 in which nodes were sized not by direct influence but by the total number of other nodes with which they were connected with (so, theoretically, an obscure ancient Greek philosopher with just one connection to Plato would also have access to Plato’s entire network). This results in a pretty meaningless graph in which the influence of ancient philosophers is over-weighed.
  • Graph of Mathematicians isn’t very useful because too many outright philosophers creep up and achieve prominent (Bertrand Russell? Avicenna?). There is no clearly dominant grouping.
  • The Graph of Programming Languages is more interesting; Haskell, Java, C dominate, followed by a dozen or so of the likes of Algol-68, C++, Fortran, Perl, Python, Lua, Ruby, Smalltalk, Pascal, and Lisp. I do not have the background to assess if this is an accurate representation of reality, though I’ve never heard of Haskell, and would have guessed Fortran and Lisp would be higher.
  • The Graph of Sports Teams.
  • The Graph of Beer though they don’t really influence each other all that much.
  • The Graph of Human Diseases is apparently dominated by colon cancer, breast cancer, leukemia, and deafness.

There is clearly a lot of scope to continue building on these graphs, especially involving ideas (philosophers, politicians, economists, sociologists, authors, etc) though finding or building the requisite databases is a time-consuming endeavour. Interesting patterns will also emerge. For instance, now that I think of it, the most influential person in history is Jesus Christ, and Karl Marx is surely in the top ten. Amazing really how deep Jewish over-achievement goes even on the biggest historical scale.

Another interesting project would be to build a graph of influence in the blogosphere perhaps based on some combination of blogroll connections and visitor numbers. This will of course be a very computationally demanding project given that there are something like 100 million blogs in existence today.

Comments

  1. Hi, thanks for the link. You gave a pretty good wrap of the graphs though did you suggest that Bertrand Russell and Avicenna are only philosophers? They both contributed to the field of mathematics it quite significant ways. Avicenna’s Book Of Healing and Canon Of Medicine are cornerstone works of their time (especially notions involving motion and optics). Also Russell’s Principles Of Mathematics significantly contributed to the field of logic and challenged a number of ideas of the time.

    You’re right, Graph 2.0 isn’t much hey. I thought it would be a bit more insightful but it turned into a bit of a mess.

    You’re also very right – creating the databases is a very time consuming endeavor! I must return to creating a new one of academics for my next series.

    Great summary. All the best.
    Griff.

  2. Kibernetika says:

    Haskell? Wasn’t he the neighbor in Leave It to Beaver? Eto shutka :) Fortran and Cobol are sort of like the Neanderthals and Denisovans, but I don’t want to get involved in any code wars, either :)

    Another interesting visualization would capture where and when comp languages originated. Or current use of languages. Some of the entities in the programming graph are better identified as scripting languages or markup languages (e.g., XML), though. But that’s more a question of semantics in this case, rather than influence.

    I dig Lua. E’ do Brasil :)

    And different [scripting]languages have different applications. A complex subject!

    Griff, good work :)

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