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feat(api): add cultural analysis endpoint with identity markers

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Dylan De Faoite
2026-02-24 14:25:53 +00:00
parent 257eb80de7
commit ccba6a5262
3 changed files with 47 additions and 47 deletions
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11
server/stat_gen.py
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@@ -8,6 +8,7 @@ from server.analysis.temporal import TemporalAnalysis
from server.analysis.emotional import EmotionalAnalysis
from server.analysis.interactional import InteractionAnalysis
from server.analysis.linguistic import LinguisticAnalysis
from server.analysis.cultural import CulturalAnalysis
DOMAIN_STOPWORDS = {
"www", "https", "http",
@@ -46,6 +47,7 @@ class StatGen:
self.emotional_analysis = EmotionalAnalysis(self.df)
self.interaction_analysis = InteractionAnalysis(self.df, EXCLUDE_WORDS)
self.linguistic_analysis = LinguisticAnalysis(self.df, EXCLUDE_WORDS)
self.cultural_analysis = CulturalAnalysis(self.df)
self.original_df = self.df.copy(deep=True)
@@ -87,24 +89,23 @@ class StatGen:
def get_user_analysis(self) -> dict:
return {
"top_users": self.interaction_analysis.top_users(),
"users": self.interaction_analysis.per_user_analysis(),
"interaction_graph": self.interaction_analysis.interaction_graph()
"users": self.interaction_analysis.per_user_analysis()
}
# average / max thread depth
# high engagment threads based on volume
def get_interactional_analysis(self) -> dict:
return {
"average_thread_depth": self.interaction_analysis.average_thread_depth(),
"average_thread_length_by_emotion": self.interaction_analysis.average_thread_length_by_emotion()
"average_thread_length_by_emotion": self.interaction_analysis.average_thread_length_by_emotion(),
"interaction_graph": self.interaction_analysis.interaction_graph()
}
# detect community jargon
# in-group and out-group linguistic markers
def get_cultural_analysis(self) -> dict:
return {
"identity_markers": self.linguistic_analysis.identity_markers()
"identity_markers": self.cultural_analysis.get_identity_markers()
}
def summary(self) -> dict: