# Reddit CrosspostNet--Studying Reddit Communities with Large-Scale Crosposst Graph Networks
## 3 Dataset and Network Creation  
As noted, the aim of this work is to propose a new approach to analyzing the structure of and relations between, subreddits using graph network algorithms applied to represent the crosspost perspective. In this context, we first introduce the dataset used in the reported work. In the first step, all crossposts, from all subreddits with over 10,000 subscribers, have been collected for the period 1 January 2022-31 December 2022. The crossposts have been then filtered to remove insignificant content. Specifically, crossposts with a score (Reddit's \"appreciation\" mechanism [11]) of less than 2 were removed. Note that, by default, all posts obtain a score of 1 when posted. Therefore, it was assumed that posts with \"no appreciation\" can be seen as \"inconsequential\" from the perspective of Reddit as a medium of information exchange. For similar reasons, all posts with 0 comments were also removed. Again, it was assumed that \"nobody cares\" about posts when they have no comments. Obviously, these values are arbitrary. It could have been decided to keep crossposts with more user involvement (e.g., a minimum score of 5 and a minimum of 5 comments). In this way, only the \"most influential\" crossposts could be kept and used in further analysis. However, it has been assumed that, in this contribution, the focus will be on a complete picture of the information structure of Reddit. Studying the effects of including only the most influential crossposts is left to future work. Finally, all crossposts with the topic \"[deleted]\"or \"[removed]\" were also pruned, as these were either deleted by the author or removed by Reddit's moderation. Completion of the pruning process resulted in a dataset consisting of 7,643,447 crossposts from 131,477 subreddits. Here, due to the recent restrictions imposed by Reddit, we have decided to not post the dataset publicly online. However, it may be provided to academic researchers (only), upon contacting the lead author. In the second step, a graph network was formed, with subreddits as nodes and crossposts capturing the directional relationship between them. The edges were weighted by the number of crossposts. The pseudocode of the graph network building algorithm is as follows: in the Algorithm 1. ```
crossposts \(\leftarrow\) all available crossposts after cleaning (a crosspost is a dictionary with values \"from subreddit\" and \"to subreddit\") \(V\leftarrow\{\}\) (empty set of vertices; it will become a set of values) \(E\leftarrow\{\}\) (empty set of edges; it will become a set of ordered pairs (node1, node2) with an additional value indicating weight) while\(|\textit{crossposts}|>0\)do  test crossposts \(\leftarrow\) crossposts\([0]\) (take the first element) \(i\gets i-1\) if\(\textit{crossposts}[\textit{\"from subreddit\"}]\
ot\in V\)then \(V\gets V+\textit{crosspost}[\textit{\"from subreddit\"}]\) endif if\(\textit{crossposts}[\textit{\"to subreddit\"}]\
ot\in V\)then \(V\gets V+\textit{crosspost}[\textit{\"from subreddit\"}]\) endif \(\textit{new\_edge}\leftarrow(\textit{crossposts}[\textit{\"from subreddit\"}],\textit{ crossposts}[\textit{\"to subreddit\"}])\) if\(\textit{new\_edge}\
ot\in E\)then \(E\gets E+\textit{new\_edge}\) endif \(\textit{new\_edge\_weight}\leftarrow\textit{new\_edge\ weight}+1\) crossposts \(\leftarrow\) crossposts\(\backslash\) crosspost endwhile
```  
**Algorithm 1** The algorithm of constructing the CrosspostNet  
As a result, the set \(V\) becomes the set of vertices (labeled with subreddit names) and the set \(E\) is the set of directed edges, weighted by the number of crossposts between the subreddits. For example, there were 2083 crossposts from r/Unexpected to r/HolUp and 33 crossposts from r/HolUp to r/Unexpected. So, the node representing r/Unexpected is connected to r/HolUp with an edge of weight 2083, while r/HolUp is connected to r/Unexpected with an edge of weight 33.