Want to gain a deeper understanding of how communities evolve and respond to external pressures? Below, we present the ultimate way to study cultural groups undergoing significant changes, e.g., the richness and diversity of their interactions and the outcomes of conversations.
This study analyzed core and peripheral conversations related to technological innovation, such as remote work conversations before, during, and after the COVID-19 pandemic. Core conversations typically revolved around essential topics such as visa issues, remote work strategies, and digital nomad lifestyle challenges. These discussions were central to the community’s identity and often involved practical advice and shared experiences. Conversely, peripheral conversations included multiple “how-to” recommendations, novel cultural experiences, and personal anecdotes.
Mixed Method Approach
To classify the conversations, we performed content analysis, where we qualitatively coded and reviewed a sample of posts in each period to identify recurring themes and topics. Then, we used Stochastic Block Modeling, which treats a collection of texts (posts from a subreddit) as a network. This network is called a bipartite network, which means it has two types of nodes:
- Text Nodes represent individual texts or documents (e.g., posts).
- Word Nodes: These represent words from the texts.
To make an analogy, imagine being at an after-work gathering with many people talking about different things, and you want to get an overview of the discussions in the room. The algorithm groups people based on the issues they’re talking about, and it can show us how these groups are related to each other. This helps to understand what people discuss and how their conversations are connected.
We looked at how people in the digital nomad community on Reddit talked about different topics over time, especially before and during the COVID-19 pandemic. Before the pandemic, the community had a balanced mix of primary and side conversations, and people regularly interacted with each other. When lockdowns started, the community talked more about visa issues because travel was restricted. This was a temporary change. As countries opened their borders again around May 2021, there was a considerable increase in interactions. This disrupted the community’s identity more significantly than before. We saw two main changes:
- Constant Interaction Anomalies: People started interacting in unusual ways.
- New Community Issues: Conversations shifted to questions like being a digital nomad, sharing resources, and dealing with restrictions.
Figure 2. (A) Heat map of monthly interaction counts across topics. (B) Tree map depicting topic interaction ratios in the three identified sub-periods (pre-pandemic, lockdown, and vaccinated).
Many new people joined the community, which might have caused conflicts in social norms. This changed how digital nomads saw themselves, which was still happening by the end of 2021.
Conversations shifted to questions about how to become a digital nomad and proper definitions of this lifestyle.
Identifying shifts in core and peripheral topics can help predict how a community might evolve in response to disruptions. This approach can be applied to other online communities or cultural groups undergoing significant changes. For instance, in analyzing core and peripheral conversations in forums related to emerging technologies like AI or blockchain, core conversations might focus on technical developments and applications. In contrast, peripheral discussions could involve speculative future scenarios. Analyzing these conversations could help predict how the community adapts to technological advancements. Such Insights can inform strategic decisions about workforce development, technology adoption, and organizational culture.
Real Life Applications
By tracking changes in these core and peripheral conversations, people analytics teams can predict how the workforce might evolve in response to disruptions, such as technological changes or organizational restructuring.
