## 4 Results
### Annotation Consistency and Discrepancies  
Our data annotation process revealed significant trends in inter-annotator agreement. Our findings, which are illustrated in Contingency Table 6, showed both concordance and discordance between the two annotators across four key mental health root cause categories. Notably, the \"trauma and stress\" category exhibited substantial concordance, with both annotators achieving a 92.5 percent agreement rate, which is considered high. This category comprises a diverse range of factors, including domestic violence, relationship issues, financial strain, work-related stress, and feelings of loneliness. For instance, posts P4-P6 in Table 4 clearly indicate that the \"trauma and stress\" label can be attributed to expressions of financial hardship, social isolation, and relational dissolution. Conversely, distinguishing between the \"personality\" and \"trauma and stress\" categories presented challenges, leading to noticeable discrepancies. Differentiating posts regarding \"early life\" factors also showed some inconsistencies, while the \"drug and alcohol\" category displayed the least disagreement, indicating more distinct criteria for classification in this area. The post in Table 7 presents a case where the subjective nature of mental health narratives can lead to initial disagreements among annotators. Annotator 2 perceived the post as indicative of \"trauma and stress\", due to the mention of the loss of loved ones, a classification typically associated with impactful events causing significant emotional distress. However, Annotator 1 identified the enduring nature of the poster's grief, tracing its origin to adverse experiences in childhood, thus categorizing it under \"early life\" factors. The distinction here lies in the recognition that the user has carried the stress from childhood into adulthood, an interpretation that aligns with the \"early life\" label, which encompasses formative experiences that have a lasting influence on an individual's mental health. This is in contrast to \"trauma and stress\", which often focuses on more recent events and their immediate impact. Such disagreements were systematically resolved by engaging in a consensus-based discussion or, when necessary, consulting with a domain expert. Through these resolution mechanisms, the team was able to reconcile different interpretations and achieve a unified understanding, ensuring the reliability and consistency of the dataset's categorization. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & & & & \multicolumn{3}{c}{**Annotator 1**} \\ \hline \multirow{3}{*}{**Label**} & \multirow{2}{*}{**Personality**} & \multirow{2}{*}{**Trauma and Stress**} & \multirow{2}{*}{**Early Life**} & \multirow{2}{*}{**Drug and Alcohol**} & \multirow{2}{*}{**Total**} \\  & & & & & & \\ \cline{1-1} \cline{5-8}  & Personality & 157 & 23 & 16 & 4 & 200 \\ \cline{1-1} \cline{5-8}  & Trauma and stress & 15 & 185 & 0 & 0 & 200 \\ \cline{1-1} \cline{5-8}  & Early life & 0 & 15 & 185 & 0 & 200 \\ \cline{1-1} \cline{2-8}  & Drug and alcohol & 0 & 5 & 0 & 195 & 200 \\ \cline{1-1} \cline{5-8}  & Total & 172 & 228 & 201 & 199 & 800 \\ \hline \end{tabular} Source: authors’ creation, detailing concordance and discordance between the two annotators across four key mental health root cause categories. This table serves to quantify inter-annot agreement, as part of the data validation process.  
\end{table} 
Table 6: Inter-annotator agreement (IAA) contingency table.