Using the Netvizz app on Facebook I was able to extract and download my personal network as a .gdf. I imported my Facebook network into Gephi and performed a Force Atlas algorithm on node degree. The nodes and labels have been ranked by degree centrality so that the node size is representative of the amount of mutual friends shared.
My Facebook Network [A]
Here we can already see clearly defined clusters without having to performing community detection. In this image there are 3 major clusters. The major cluster in the south west is divided into two sub-groups and the major cluster in the south east is divided into three sub-groups. [A]
The top cluster primarily consists of friends I met in high school. I grew up with the majority of these people and they all attended Mountain Ridge High School. Outliers around this group include family members and people I have met through friends from high school. [B]
Below that we have a small cluster of friends which I cosplay and attend anime conventions with. Jeff Lam is a cousin of mine who attended Mountain Ridge High School and is friends with many of the people I frequent conventions with. His node is one of the few links between these two community of friends. My girlfriend Dash Tinonina also serves as a link between my high school cluster and my anime cluster. We both participate in cosplaying events within the anime community, and we both hike and camp with my friends from high school. [C]
South west of the anime group is another smaller cluster of people I met through living in the U of A Fine Arts dorm and living at the Geronimo House. Many of the people on the right side of this cluster went to Ironwood High School. Josh Bowdish lived in the same hall with me freshman and sophomore year of my undergrad and we have pretty much been living together from 2008-2013. Because he is friends with my anime group, dorm group, and the larger cluster to the southeast, his node has one of the largest diameters on my map. [D]
This is the greater southeast cluster. These are all people I’ve met through drinking. Back when Kevin Kobashigawa lived in Tucson, you would be able find people from this cluster at his house Thursday-Saturday night. [E]
The greater south west cluster is the largest cluster filled with all kinds of creative people from different disciplines. Bradley Bowman lived in the same dorms with Josh and me. He has also introduced me to everyone I know in the southern portion of this cluster making him one of the largest nodes in my network. The southern half of this cluster enjoys Tucson nightlife and is current with the music scene. The north portion of the cluster consists of printmakers, illustrators, graphic designers, photographers, painters, and sculptors. Rachel Martin, Edward Paul McCarthy IV, and April Putney are sculptors I’ve worked with throughout my undergrad who also participate in Tucson’s nightlife and bar scene. It is interesting to see that Anabelle Dimang and I have a mutual friend from Mountain Ridge High School. She is one of the few distinct links between my creative cluster and my high school group. [F]
Using gender to color code the nodes we can see that the majority of friends in high school were male whereas the majority of my friends in college were female (In hindsight I should have made each node the same diameter for a more accurate visual representation, but it's pretty fun picking out the lead male and female roles in my story). [G]
Modularity Community Detection[H]
After performing modularity algorithm for community detection we can see several of the same groups we found while using degree as the ranking measure along with some new groups. Some differences between the two maps include splitting up my high school cluster into new groups after the modularity algorithm. To the south in light blue is my high school cluster. Within the same area is a family I used to be very close with in highschool represented by the purple cluster of 5. My own family is above this group in Yellow. There is also a well defined split in the fine arts cluster in this version. The music/night life/ bar scene group is represented by small hot pink dots in the north west right above the rest of the fine arts cluster represented by larger pink dots. I wonder why this version decided to represent the north east area as one group type even though there appears to be distinct sections. This group is represented by the tiniest red dots and are a combination of my dorm group and the group I drink with. It is also curious to see a small peninsula forming on the top left of this section comprised by classmates from my Chinese class. [H]
Betweenness Centrality [I]
Betweenness centrality is the geodesic distance between nodes. In this version of my network It makes sense that Dash Tinonina is the largest node. She is my girlfriend and she is a part of many aspects of my life. She is well aware of the different types of friends that I have in all of my clusters, whereas the other large nodes are more specialized and therefore do not have as high of a betweenness centrality. This is mainly because I met Josh Bowdish, Bradley Bowman, and Edward Paul McCarthy IV at the University and they have little to no connection with my high school cluster. I also met Dash Tinonina at the University, but we visit my highschool friends from time to time. [I]
This social network analysis has been enlightening. I was surprised at how much information could be derived from data I was already aware of. Gephi has also been surprisingly nice and intuitive to use. By using Gephi I was able visualize my social network in different forms making it easy to analyze. The most interesting part about this project was discovering key players and outliers in my map. In the future I hope to perform similar analysis to compare and contrast changes in my network over time.
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