# Reddit CrosspostNet--Studying Reddit Communities with Large-Scale Crosposst Graph Networks
## 4 Characterizing CrosspostNet
### Node Degree Analysis  
We start the analysis of CrosspostNet by discussing the node degrees. Figures 3 and 4 depict the top nodes, sorted on the basis of their in- and out-degrees, respectively. Figure 1: CrosspostNet illustrative visualization (simplified). Figure 2: CrosspostNet illustrative visualization (simplified and zoomed). The first thing to notice is the Power Law nature of both distributions. This is a common phenomenon in social networks. The exponent of the degree distribution of a scale-free network (\(\gamma\)) of the distribution usually lies between 2 and 3 [12]. As established in similar studies of Reddit social networks [1], the Power Law should materialize also here. After simple calculations, it was found that for the CrospostNet, the resulting values for the degree distribution (Figures 3 and 4) are \(\gamma=2.83\) (in-degree) and \(\gamma=2.35\) (out-degree). Therefore, as expected, CrospostNet is a scale-free network (see, also [12]). We now focus attention on the top in- and out-crosposposing subreddits. It is clearly visible that r/HolUp (acronym from \"hold up!\"--a phrase used on the Internet when something unexpected happens) is the major subreddit, to which crossposts are posted. It is the main receiver of crossposts in the whole of Reddit. On the other hand, r/interestingasfuck, r/Unexpected and r/damnthatsinteresting produce most posts, which are then crossposted to other subreddits. They are the main senders (producers) on the platform. Interestingly, R/HolUp and r/Unexpected consist of mostly pictures or GIFs that show a situation with an unusual \"twist\" (the so-called \"holup!\" moment). R/interestingasfuck and r/damnthatsinteresting, as their names suggest, display pictures that are interesting to users, mostly trivia, unintuitive facts, and other random pieces of knowledge. Note that all these subreddits do not focus on a particular topic, but rather a feeling that the user  
Figure 3: Top 50 subreddits (nodes) by in-degree. experiences when browsing them. This means that there is no particular topic that attracts sharing and crossposting, rather a general and/or unspecified content. In the following analysis, the \"in-\" and \"out-\" prefixes refer to the direction of the edges (hence the degree). The in-degree refers to the in-going edges, which model the incoming crossposts (posts that were crossposted to the subreddit). The out-degree refers to the out-going edges, which model the out-going crossposts (posts that were crossposted from one subreddit to another). The top subreddits in both rankings (the in-degree and the out-degree) consist of subreddits with very broad topics, such as r/nextfuckinglevel (pictures and videos of skillfully performed activities), r/funny (funny pictures and videos), etc. However, there are several subreddits that are more narrow topic-wise. At the top of subreddits with the highest in-degree (subreddits that receive the most crossposts), there is r/pikabu, a Russian subreddit which consists of various content in Russian and r/antiwork, a subreddit about getting \"the most out of a work-free life\". In the top of subreddits with the highest out-degree (subreddits that produce posts that are then crossposted) there is also r/soccer. Figure 4: Top 50 subreddits (nodes) by out-degree. have crossposts themselves. On the other hand, practically all subreddits exchange (in- and out-degree) crossposts with subreddits of similar out-going crossposts (out-degree). While the uniform distribution of out-degrees does not indicate any outstanding subreddits, the power-like distributions are worth taking a closer look at. The top of both in- and out-neighbors contains the following subreddits: r/therewasanattempt, r/196 and r/instantkarma, r/TheRandomest, r/PeopleFuckingDying. All of them contain various types of memes in an image, or video format that have no particular topic. The content of r/therewasanattempt is finishing the titular sentence with a (usually funny) comment about a given image or video.