## 5 Results
### Linguistic Usage Patterns
#### 5.2.2 Linguistic Differences Across User Groups  
We also investigated linguistic differences among the three user groups (general, comment-heavy, and post-heavy). We conducted a one-way ANOVA for each dimension, followed by post hoc [PERSON]'s HSD tests whenever the ANOVA indicated significant differences. To emphasize the differences in heavy groups, we reported only the corresponding p-values in the _p (post hoc)_ column in Figure 4. The results show that these heavy groups differ significantly in most dimensions. Through these findings, we confirmed that there are substantial differences in language usage patterns between the post-heavy group and the comment-heavy group within both posting and commenting contexts. Representative examples of posts and comments from post-heavy and comment-heavy users are shown in Figure 5 and Figure 6, respectively. **Analytic** : Post-heavy users tended to produce more structured and formal text, indicated by higher Analytic scores in LIWC. Their writing often included well-organized sentences and collective pronouns (for example, \"we\" or \"let's\"), suggesting official announcements or group-focused statements. In contrast, comment-heavy users exhibited a more casual style, occasionally ignoring conventional grammar (for example, \"I looooooove you\") and engaging in rapid, conversational exchanges. **Clout**: LIWC defines Clout as an index of social dominance or leadership in communication. Comment-heavy users displayed higher Clout when writing public posts, often by initiating conversations or making bold statements (for example, \"I love you!\"). In contrast, post-heavy users generally showed higher Clout in comment sections, frequently directing discussions with calls to action (for example, \"Why don't we...\", \"Let's vote...\"). **Authentic**: Although posts in general appeared more Authentic than comments across the entire user base, post-heavy users' own posts were somewhat lower in Authentic scores. This may occur because many of their posts resembled official announcements rather than spontaneous personal expressions. On the other hand, comment-heavy users' posts included more informal, candid language, which correlated with higher Authentic scores. **Tone**: Comment-heavy users showed a significantly higher Tone score than general and post-heavy users, although the difference between comment-heavy and post-heavy users was not significant. This likely occurred because comment-heavy users frequently employed more positive or affectionate language (for example, \"miss you\", \"love you\"). **Personal pronoun**: Analysis of personal pronoun usage showed that comment-heavy users used more instances of \"you\", whereas post-heavy users used more instances of \"we\", especially in their posts. This finding suggests a more interpersonal communication style among comment-heavy users, while post-heavy users tend to emphasize collective goals or a group identity. Figure 5: Examples of posts from a post-heavy user (**left**) and a comment-heavy user (**right**). Figure 6: Examples of comments from a post-heavy user (**left**) and a comment-heavy user (**right**). **Drives**: Post-heavy users exhibited higher Drives scores, suggesting a stronger focus on goals, leadership, or group motivation. Their posts often contained group-oriented language (\"we\", \"let's\") or directives. In contrast, comment-heavy users demonstrated a more informal communication style, characterized by frequent use of \"you\", more affective expressions, and a greater inclination to express empathy or affection. **Affect**: Further distinctions emerged in Affect, where post-heavy users demonstrated markedly lower emotional expression overall, particularly in their comments. Compared to the other groups, which used more varied emotional terms or friendly gestures (for example, \"love you\", emojis), post-heavy users maintained a more reserved tone in both posts and comments. **Social**: Post-heavy users showed significantly lower Social scores than comment-heavy users when posting.