Using Gephi to Visualise Game of Throne’s


There are many visualization tools out there that can enable somebody to see data in a whole new way. The tool I used is called Gephi which allows users to create visualizations using datasets comprised of nodes and edges. I decided to use the tool to visualize the character relationships in a few episodes of the first season of game of thrones to show the characters with the most influence and to visualize how the story is told using a data set I made myself using Microsoft excel. The reason I made a data set in the first place was because Gephi was very specific about the files you imported into the software

Before looking at game of thrones or any topic I inspected different visualization tools. One of the tools I looked at called RAW was capable of taking in different forms data to create visualizations. I did not choose RAW because I felt the visualizations where too simplistic and bland. I choose Gephi because I liked the look of examples I found online and I found the UI offered good opportunities for effective data manipulation. Even though I picked Gephi in the end I had one major issue with using the program and that was actually getting data to use in Gephi. I looked online and found data that was in formats that can be used in Gephi but came with two more problems. The first being that Gephi is specific about what way the data is presented in different formats and the second being that anything I got to work wasn’t really strong data.

I found my best option was to create the data myself using a feature in Gephi to import two spreadsheets in the CSV format comprised of nodes and edges. At this point I decided to visualize the character relationships of the characters in the TV series Game of Thrones. What inspired me to do this was apart from being a fan of the show I thought Gephi best use would be in displaying the relationship of characters in a story. I decided to only visualize the beginning, middle and end episodes of season one as I believe it would give me a brief understanding of the relationships in the world and help me Identify the central character in the beginning middle and end.

In order to make a visualization in Gephi I had to create two spreadsheets one for nodes and one for edges. Nodes are items represented by a number and a label which is a name for the node. An edge is a single connection between a pair of nodes that represents the nodes having a relationship. To make characters interactions into nodes and edges I had to list the characters as nodes and the interactions of each character as edges. To get the information I went to a wiki for game of thrones where you can read the events of every episode. I believed if I gathered the data as I watched the show or read the book it would take too much time. In creating the edges I made them under the following criteria. If character was in a scene with two other characters that character would have an edge made for connecting them with each of the other characters in that scene. The other characters in that scene are connected with each other thus that scene can be represented in Gephi.

The following images are the four visualizations I created in Gephi using a layout known as ‘Fruchterman Reingold’. I kept this layout because I found it to be very presentable with the way the nodes are lay out along with making easy to tell the relationships. To make the information more clear in Gephi I did some actions to make the visualizations easier to understand. The first thing I did was make the node change size based on Average weighted Degree. The degree is a representation of how connected a node is, the greater the degree the node has the bigger it is in my visualization. I also did the same with the color so the nodes will be darker based on degree. I did the same thing with color for the edges and increased the edge thickness to make it easier to interpret.

Game of thrones graphs


The visualization labelled “episode one” is the first episode of Game of Thrones where the family known as the Starks are the main focal point of the episode. The Starks take up the most density in the display in terms of node size and color as multiple members of this group are in most of the scenes. The graph also introduces the Lannister’s and the King Robert Baratheon who are central to the episodes plot. The graph also features a group known as the Targaryen’s who are enemies of King Robert in another country which is why they don’t connect.  The three other visualizations are more interesting as multiple groups in all the visualizations are separate from one another.


Game of thrones follows different groups who are in different parts of the world during a time where there is political instability. As a result of this it is rare to see central characters interacting with other central Characters; this is shown especially in the bottom two visualizations. The visualization for ‘episode six’ is a good example  of what I am talking about as the four groups shown in the visualization are in for different locations in the world Kings Landing, Winterfell, the Narrow Sea and the Veil. These groups are shown to either to have a lot of interaction among st each other or have little interaction. The visualization does not tell us what the state of the relationships are but do tell us how close the characters are.

The following is combination of all the Nodes and Edges for all four maps using the ‘Fruchterman Reingold’ layout. The second image is the same visualization using the ‘Force Atlas 2’ layout since the visualization in the first image does not give a clear picture of anything other than who is the most dominant character.  The ‘Force atlas 2’ layout sets a distance for nodes based on how closely they are related to each other which is helpful to show my. The visualization shows multiple huge clusters of Nodes separate from one another with only a few nodes connecting these groups. This shows that even though there are many characters huge groups of them don’t communicate with the other groups.

game of thrones full graphwestoros graph

The group in the top right of the visualization are the characters in Winterfell and other places in northern Westeros who are strongly connected. This is due to most of these characters seeing each other as family while in the bottom left there is Kings Landing. In Kings Landing the characters aren’t as strongly connected as those in the north as these characters are both friend and enemy amongst each other. The bottom right represents the veil where a trial is happening and the top right is the edge of the narrow sea where an army is being built to take Westeros.

These visualization help solve one question that people have about game of thrones which is who is the central character? Based on my visualizations the most influential character in season one is Eddard Stark who is the hand of the king. Eddard Stark as hand of the king does most of the king’s work which includes making decisions and holding meetings while being responsible for advising the king. In reality it is a more powerful role than the king, in having such a powerful role Eddard is made the central character in the plot which is why in my visualization he has the strongest node. In my visualization for episode ten Eddard Stark is not present yet is still dominant when I put all the visualizations together.

My Datasets:

Nodes – GOT all nodes

Edges – GOT all edges


Gephi –


Game Of Thrones wikia   –






Storify: Critical Review

I have used stuff like WordPress and Drupal in the past to post content online with my best post tending to be the stuff that goes on a step by step approach like a story. I recently in last two months used Storify which had its ups and downs but overall I enjoyed my use of it. Storify is a blogging style site like WordPress you can sign up for free to post your own content. Storify feature a unique search mechanism that I haven’t seen in other such services but It has its flaws in terms of performance.

The purpose of Storify is to write content in the form of a story and display that content with various resources. With Storify you can type what you want much like you would using a word processor followed by using a search mechanic to display content such as image, tweets, gif etc. to parts of the story. In presenting information in a story like style you are not only trying to inform the individual reading your content you are also trying to change how they act in relation (Bruzzese, 2012). With Storify you are expected to provide a beginning, middle and end to have a change of events to keep the reader interested.

The thing that makes Storify different is the mechanism to search content and drag it into your story. If you are searching a topic Storify will display some tabs which will be under a category of info under your choosing. This could go for tweets which can be searched for based on what word you search for. I believe this is a good feature of Storify but it has some serious flaws based on my own experience of using it. The search does yes get very good stuff sent back to you but it can get a lot of useless items as it is something not said by an expert who can make a story more stronger and believable (Widrich, 2012). This is because certain search types only display content that is less than ten days old and I have my problems with this since it limits what I as a user can gather. However if I found the source link for something that was ten days old I could use that link to create information I can drag into my Storify, this does require I use search engines instead.

I could be missing in the search one of the best sources of information out their cause it was eleven days old. The main reason this system bugged me is because I deleted one of  items I searched and was unable to get it back as I found it a month earlier. However even though I find it problematic there are some good points to it like the content that can be found is likely different every day, since it is recent it is probably a good source of information since it’s up to date. The only other issues I have found with the Storify would relate to the interface however it still performed well.

I made a piece using Storify about robots and archaeology and how I went about it was that I wrote my stuff in a word processor. I used a word processor because when you write paragraphs in Storify you can either write it together or in separate blocks. The option of separate blocks is a better choice since information you find using the search mechanism can be put in between your paragraphs. However if you do it this way it could be a bit frustration depending on how much you are writing and how many pieces of information you are dragging in to your Storify. What I mean by frustrating is that if I want to change something or read over my work. I would have trouble since you have to use a slider to look over your page; this in turn includes having to load in the blocks which take their time.


The people who would best use Storify would be researchers who can use the search mechanism to find information around a recent topic. People who are into writing news stories would get a kick out of Storify since it is very adaptable to a news type of storytelling.  I had my issues with Storify but it did prove a useful tool in terms of content creation and information gathering. I will probably use it again in the future to make some more content and to search for recent items on a topic I am researching.



Widrich, L. (2012, May 12th). The Science of Storytelling: Why Telling a Story is the Most Powerful Way to Activate Our Brains. Lifehacker. Retrieved from

Bruzzese, A. (2012, December 10th). Tips for Effective Storytelling at Work, The Fast Track – Intuit QuickBase Blog. Retrieved from

Critical Discourse in DH my thoughts.

Recently I read a piece by Fred Gibbs called “Critical Discourse in Digital Humanities” where Gibbs examines how Critical Discourse applies in the Digital Humanities. Critical Discourse means both Criticism and Debate, criticism being saying something negative about something while debate is where two people argue over a topic. In the paper Fred says he was asked where the Critical Discourse in the Digital Humanities is. Gibbs has trouble figuring it out for him thus discusses it in the text. In the end Gibbs appears to believe that there is not really any one criticizing projects other than peers who do so slightly.

One of the arguments is that peer reviews is not good enough and allows people on the outside to not understand the projects as well as the people who made it. I believe this is not really true as we are trying in the digital humanities to give people outside of digital humanities an easier way of learning things through our projects.  A second argument is that the work done in the digital humanities is not good enough for evaluation due to our methods. I’m against this as well as I believe if someone cant evaluate something its either because they are not good at evaluating or they are not really interested in what they are evaluating. The third argument for is that Digital humanities needs its own reviewing system for criticising material. I am neutral in this aspect because I am not against someone coming up with a style to criticize projects but I am against meeting criteria that could change how a Digital Humanist goes about their work by establishing limits. Limits imposed by Criticism can affect the creativity and enthusiasm of the writer in Debates in the Digital Humanities Jamie Bianco states “All Criticism tends to shift the interest from the work of art to something else” where the way we criticize can just as likely change the entire project and how we interact with it.

The whole thing with critical discourse puts in the question on is Digital Humanities a different thing to the Humanities? I believe he is putting into context is Digital Humanities really humanities at all is it just a separate subject that has nothing to do with humanities. I disagree as I believe that digital humanities are a subject that tries to be an improved system for humanities, a upgrade not a competitor. In the field of science and technology we strive to improve our current methods with new ones and I believe that is what the digital humanities are.

I believe Criticism is a factor that ensures improvement in the next round of projects. I don’t think that a lack of criticism in something is a bad thing but if there is not criticism at all then there is a problem.  A person in charge of a project is responsible to get their project to the right people to get most accurate feedback available. If you are not getting any bit of criticism after that then there is a problem. Gibbs goes on to point out MLA guidelines for projects and discusses some interesting guidelines like Transparency and Reusability of the project. Those and other guidelines are all things people would think about while working on projects anyway. The one about transparency is the one people are most likely to break. I come across a lot of text where the author of the book assumes people know what they are talking about so leave no real description of their topic in the beginning.

Fred Gibbs 2011 – Critical Discourse in Digital Humanities

Jamie Bianco 2012 – Debates in the Digital Humanities: This Digital Humanities Which is not One

Crowd sourcing: a phenomenon of co-operation

I recently read a blog post by a Digital Humanities lecturer named Stuart Dunn who wrote in his post an overview of the academics in crowd sourcing. He also tries to make the post a guide to making an academic crowd source based on his own experiences.

Crowd sourcing is where members of the public contribute to development of a large project. The purpose of allowing the public to contribute is to complete a task quicker and more efficiently. Dunn clarifies that there are two types of crowds sourcing one being for profit and the other for knowledge. Private companies looking for profit will use crowd sourcing to complete task that require a lot of funding and time to do if they employed a small group of people to do it. Academic crowd sourcing which is what Dunn focuses on is for the purpose of creating knowledge or making knowledge available to the public.

I have taken part in academic crowd sourcing before such as open street map which is in my opinion an example of academic crowd sourcing gone right. In other cases academic crowd sourcing could go from good to bad depending on various factors including those that Dunn describes in his post. One of the obvious factors is the contributors who are creating the knowledge. Dunn says that contributors are either the norm that do it just for a short amount time contributing to not much while the other is what Dunn calls the super contributors. The super contributors are people who are dedicated to contributing to the crowd source project. Their dedication would be the result of interest in the project, the community surrounding the project and how easy it is to contribute.

The super contributors relate to another factor Dunn thinks is important with crowd sourcing which is the addition of a forum to the website used in the crowd sourcing. Forums create a community for the crowd source allowing users to interact with one another and exchange knowledge as “crowdsourcing is reconnecting workers with their work and taming the giants of big business by reviving the importance of the consumer in the design process” (Brabham 2008, 84). I see the importance of a forum as every big website these days has its own forum. I usually end up in a forum looking for help with something technical so I personally know how useful they can be for people. Dunn says the most important thing about the forum is that it keeps the crowd source going after the group behind the project are done so that the project can go on.

The third factor is funding by universities for academic crowd source. To get funding from a university you would have to convince them that results are possible. Dunn highlights that universities are not keen on crowd sourcing because members of the public are likely not qualified academics. This usually results in funding being short if they do go through with it but the chances of success are lower. I don’t think this factor is important seeing as the point of crowd sourcing is to have the public do work that you are not going to pay for, Dunn even mentions that a lot of successful academic crowd sources go without funding supporting my opinion.

Daren, C.B., (2012) ‘Crowdsourcing as a Model for Problem Solving’, Sage Publications, pp. 84

Stuart Dunn – “More than a business model: crowd-sourcing and impact in the humanities”