The following guide provides a practical demonstration for collecting Reddit data and constructing networks, using VOSON Lab’s interactive R/Shiny app VOSONDash. Reddit – a social news aggregation, content rating, and discussion website – provides the opportunity for researchers to access a wide range of themed-based online discussion data, and to understand the dynamics of these conversations.
SNA approach to studying online networks
VOSONDash (and vosonSML) method for network construction is based on Ackland and Zhu (2015) approach, whereby edges in Reddit networks represent implicitly directed ties, i.e. reflecting exchange of opinion between users rather than an explicit social relationship. Conversations threads can be analysed as networks and VOSONDash provides two approaches to constructing Reddit networks:
Actor networks – where nodes represent users who have posted original posts and comments, and edges are the comment interactions between users.
Activity networks – where nodes are comments or initial thread posts and edges represent either replies to the original post, or replies to comments.
Methodology
In this example, we will collect data from a Reddit post relating to the COVID-19 lockdown in Sydney, Australia, and proceed to use VOSONDash features to demonstrate the data outputs and a quick overview of analysis tools.
The post titled Sydney Lockdown extended until the end of September was created on 20 August 2021, and by the time of data collection (23 September 2021) it had attracted 557 comments.
The GitHub page provides instructions to install and run VOSONDash. More information on features can be accessed in the VOSONDash Userguide(Borquez et al. 2020).
Collecting Reddit data
Reddit collection does not require API authentication. Simply go to the Reddit view, enter the URL, and click on Collect Threads. The output of the collection is presented in the right pane (Figure 1). In this example, 494 comments were collected. At this stage, the data can be saved as .rds dataframe.
Creating Reddit Activity networks with VOSONDash
Activity networks represent the three-like structure of conversations, with nodes being comments or the initial post, and edges being replies to comments or replies to initial post. In this example, we selected the Add text option, so the .graphml file contains text data.
The console displays the output of the activity network (Figure 2). The Activity network has 495 nodes (including the initial post), and 494 edges (comments). The network can be saved ad .graphml, if you prefer to use a different tool for analysis.
Creating Reddit Actor networks with VOSONDash
In a similar workflow, we can use the data we just collected to create Actor networks, to observe Reddit users interactions. As mentioned earlier, in Actor networks, nodes are users who have commented, or who have created initial thread posts, and edges represent either replies to the original post, or replies to comments. Again, the Add text option was selected, for the .graphml file to contain text data.
The console displays the output of the activity network once the network is created. The Activity network has 302 nodes, and 495 edges.
VOSONDash provides three approaches to analyse networks: Network graph, Network metrics (SNA), and Text analysis. These tools are presented in more detail in the post Analysing networks with VOSONDash.
We hope this guide has been useful and easy to follow. In the next post, we will cover Twitter data collection with VOSONDash.