feat(stat): add conversation concentration metric

Remove old `initiator_ratio` metric which wasn't working due every event having a `reply_to` value.

This metric was suggested by AI, and is a surprisingly interesting one that gave interesting insights.

server/analysis/interactional.py

@@ -63,11 +63,25 @@ class InteractionAnalysis:
         pairs.sort(key=lambda x: x[1], reverse=True)
         return pairs[:top_n]
     
-    def initiator_ratio(self, df: pd.DataFrame):
-        starters = df["reply_to"].isna().sum()
-        total = len(df)
+    def conversation_concentration(self, df: pd.DataFrame) -> dict:
+        if "type" not in df.columns:
+            return {}
 
-        if total == 0:
-            return 0
+        comments = df[df["type"] == "comment"]
+        if comments.empty:
+            return {}
 
-        return round(starters / total, 2)
+        author_counts = comments["author"].value_counts()
+        total_comments = len(comments)
+        total_authors = len(author_counts)
+
+        top_10_pct_n = max(1, int(total_authors * 0.1))
+        top_10_pct_share = round(author_counts.head(top_10_pct_n).sum() / total_comments, 4)
+
+        return {
+            "total_commenting_authors": total_authors,
+            "top_10pct_author_count": top_10_pct_n,
+            "top_10pct_comment_share": float(top_10_pct_share),
+            "single_comment_authors": int((author_counts == 1).sum()),
+            "single_comment_author_ratio": float(round((author_counts == 1).sum() / total_authors, 4)),
+        }