3.2.1

To capture overall thematic organization during the event period, we constructed a post similarity network using TF-IDF vectorization and cosine similarity between Reddit post titles. Each node represents a post, and edges connect pairs with similarity scores above a threshold of 0.5. This method captures lexical overlap and repeated phrase structures common in meme-driven discourse.

The resulting network, built from all 53,187 GameStop-related posts, reveals a structure composed of both dense and sparse regions. It contains 5,307 connected components, with a strikingly dominant component comprising 47,790 posts—nearly 90% of the dataset. In contrast, 5,276 components are singletons, accounting for 99.42% of all components but only a small fraction of the total posts.

This structure reflects a heavily repeated core of thematically consistent posts, likely sustained by meme reuse and narrative convergence (e.g., “hold the line”, “GME to the moon”). Surrounding this core is a periphery of outlier posts with little lexical overlap. Figure2visualizes this pattern, showing a densely connected center surrounded by a fringe of disconnected or loosely connected nodes.

Visualization of the title similarity network using TF-IDF cosine similarity (threshold = 0.5) on a randomly sampled 2,500-post subset.

Sample Post Titles from the Largest Component and Their Relevance

3.2.2

To further interpret the structure of the dominant component in the similarity network, we examined a sample of high-degree nodes—posts that were most thematically connected to others. As suggested by the network topology in Figure2, this cluster forms the semantic core of the community’s discourse during the peak of the GameStop event.

The titles in this cluster frequently reuse a narrow set of slogans, memes, and emotionally expressive phrases. Common expressions include“GME YOLO,” “AMC to the moon,”and“Let’s get em bois,”which contribute to high lexical overlap and dense connectivity in the similarity graph.

Table1shows a sample of ten representative post titles from this cluster, annotated with relevance and thematic notes. These posts reflect the community’s collective voice: blending performative conviction in meme stocks like GME, AMC, and SPCE with anger at institutional actors and platforms such as Robinhood.

To reinforce these qualitative findings, we generated a word cloud (Figure3) from the titles in the largest TF-IDF component. Prominent words includeGME,Robinhood,AMC,buy,hold, andmoon—terms that are not only frequent but also culturally significant within the r/WallStreetBets community. Their repetition reflects an emotionally charged, meme-driven discourse that goes beyond simple lexical similarity. The prevalence of slang, slogans, and emojis underscores that thematic cohesion in this period was shaped not just by word overlap, but by collective cultural identity and shared narrative framing.

Word cloud generated from post titles in the largest TF-IDF component. Common stopwords were removed.

Together, these results support the interpretation that the central cluster represents a thematically consistent narrative, reinforced by repeated slogans and community rituals.

3.3.1

To examine discourse evolution during the GameStop event (January 28–August 16), we constructed daily title similarity networks. Four metrics—number of connected components, largest component size, component size entropy, and average clustering coefficient—were computed for each. Figures4and5show these metrics revealing a pronounced fragmentation spike during the peak event window (January 25–28), followed by partial thematic consolidation.

Timeline of structural fragmentation metrics for GameStop-related Reddit posts. Red dashed lines mark key events: GameStop’s peak stock price on Jan 29, trading halts on Jan 28, and the start of post volume decline on Feb 2. Entropy (blue bars) reflects thematic diversity, while the number of components and largest component size capture shifts in network cohesion.

Long-term structural fragmentation metrics for GameStop-related Reddit posts (January–August 2021). Blue bars indicate the entropy of component size distributions, while green and orange lines represent the number of components and largest component size, respectively. Entropy remains elevated even after post volume declines, suggesting persistent thematic disorganization.

Entropy (blue bars, Figure4), measuring cluster size distribution in the daily similarity network, peaks with high discourse fragmentation—i.e., when many similarly sized clusters exist and no dominant theme emerges. Entropy rose sharply around the GameStop event’s peak, then gradually declined with discussion consolidation.

Unlike metrics sensitive only to component quantity, entropy reflects the relative balance of cluster sizes. For instance, 100 components, mostly singletons with few large ones, can yield lower entropy than 100 equally sized clusters. Thus, entropy can remain high even with fewer components if thematic diversity persists.

Average clustering coefficient of daily post similarity networks.

The average clustering coefficient of daily title similarity networks (Figure6) spiked sharply around January 27–28, coinciding with the GameStop event’s peak. This suggests abundant, mutually reinforcing, and tightly interconnected clusters of thematically similar posts during peak collective attention. Post-peak, the coefficient declined rapidly, remaining near zero subsequently. This drop indicates sparser, more fragmented post similarity, with few tight clusters persisting beyond the initial coordinated discourse. Sustained low clustering through spring and summer reflects a long-tail phase of weakened thematic cohesion and diversified community attention.

3.3.2

A striking observation is the dramatic drop in the largest connected component’s size on January 29, 2021 (Figure4). On January 28, the network showed high semantic cohesion, with the largest component including most GameStop-related posts. This cohesion collapsed after Robinhood and other brokerages announced restrictions on GME share purchases.

The largest component size plummeted while disconnected components surged, suggesting sudden thematic divergence. Discourse previously aligned by coordinated memes and slogans (e.g., “hold the line”) fragmented into varied reactions like outrage, legal speculation, technical confusion, and emotional venting. This fragmentation is mirrored by the entropy metric, which spiked with the component count, indicating no single dominant theme.

Actual Reddit posts corroborate this shift, like one titledRH allowing limited buying of GME ”(discussing Robinhood’s reversal) and another,GME YOLO update — Jan 28, 2021 ”(users posting massive losses or defiant gains). These examples show how the external trading halt fractured a unified semantic field into competing narratives, structurally captured by the drop in network cohesion.