When wanting to look at social networks for specific fandoms, I think the context of a more significant event and a broader culture are needed for context. To see this context we will start by examining a social networking graph that represents the recent New York Comic-Con as a whole. Then we will compare that to a social networking graph that focuses on the Doctor Who fandom. For further context; New York Comic-Con is one of the largest pop culture conventions in the world and featured a guest count of over 180,000 in the year 2016. There is a multitude of entertainment companies that participate in the convention from all over the world to promote their creations. Doctor Who is one such creation. Doctor Who is a British Sci-Fi Television show that has been running for over fifty years. The year 2018 marks the first time the show has had a lead female actor, which has made it an exciting time for fans of the show.
https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=169821
The first graph I would like to examine is the different communities that mentioned New York Comic Con on Twitter from Saturday, September 29th to Monday, October 1st. Following, Smith et al.s network archetypes you can clearly see that this represents the community cluster model. There are 5,962 nodes in the graph which represent Twitter users mentioning “Comic_Con” in a tweet, or those users that replied to or were mentioned in tweets containing “Comic_Con.” The graph is mixed, and there are three types of edges. The first edge type is “replies-to” tweets, the second type is “mentions” tweets, and the third is for each tweet that is not “replies-to” or “mentions.” In total there are 7516 edges.
Each community on the graph represents a smaller group within the larger community of New York Comic Con discussions on twitter. For example, in G1 the show Star Trek Discovery was discussed the most on Twitter according to the top hashtags of G1. While in G2, the most mentioned hashtag was cosplay. Overall the most mentioned hashtags were nycc (New York Comic Con), criticalrole, and fnafhs. According to the graph there well over one hundred distinct communities on Twitter talking about New York Comic Con during the data collection period.
These communities are mainly sharing information with each other in many directions, hence why the graph is a mixed directional network. You can clearly see from the data below the graph that after a few groups there is no centralized point of information, which differs from the graph that will be discussed next.
https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=159671
The next graph zooms in on a specific event that happened during San Diego Comic-Con, specifically relating to the Doctor Who panel. According to Smith et al., this graph shows a broadcast network. It’s a broadcast network because the news announcements caused discourse on twitter amongst different groups of individuals. The graph represents 4,008 across over fourth groups, with 8,665 unique edges. The data was collected from Monday, July 9th, 2018 to Thursday, July 19th, 2018. Tweets containing “DoctorWho_BBCA,” or users that replied to or mentioned the tweets.
The graph on “DoctorWho_BBCA” contains three types of edges; “replies-to,” “mentions,” and self-loops. Top hashtags for the entire graph include doctorwho, sdcc, and jodiewhittaker. The largest group G1 had the exact same top three tweets as the whole community. This could be due to it being the broadcast group where information was sourced.
Due to the fact, the graph is a Broadcast Network each of the smaller groups mostly follows a similar pattern when it comes to top domains and top tweets. The information coming from a specific source, in this case, San Diego Comic-Con, means that the data is being mediated by the participants of that particular Doctor Who panel (or infomediated).
Infomediation, according to Smynrios “is defined as the set of socio-technical mechanisms such as software, services, and infrastructures that provide internet users with all types of information online and connect them with other users.” (Smyrnaios, 2018). In this sense, the graph on “DoctorWho_BBCA” could be considered a less bad form of infomediation than what Smynrios speaks about. The number one influencer in every group of this particular network is @doctorwho_bbca, which means that every group is being broadcasted the same information from the start. Now, what that specific group does with it after may differ from one to another.
This contrasts with the first graph “Comic_Con” because each group is not getting its information from the exact same source. The fact that the groups in the network are all focused on different parts of Comic-Con make the information being mediated from one source almost impossible.
Smyrnaios, N. (2018). The Privatisation of the Internet. In Internet Oligopoly: The Corporate Takeover of Our Digital World. Emerald Publishing Limited.