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alexchilton
Initial deployment: Sentiment & Topic Analysis Dashboard
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metadata 
title: Topic Analysis
emoji: 📊
colorFrom: green
colorTo: blue
sdk: docker
pinned: false
app_port: 7860

📊 Sentiment & Topic Analysis Dashboard

Upload CSV, JSON, or Excel files containing customer feedback, support tickets, or reviews — get instant multilingual sentiment analysis, topic clustering, anomaly detection, and interactive visualizations.

Features

  • Multilingual sentiment analysis using cardiffnlp/twitter-xlm-roberta-base-sentiment
  • Dynamic topic clustering with BERTopic (HDBSCAN + UMAP)
  • Interactive force-directed topic cluster graph
  • Sentiment trend charts with confidence intervals
  • Data quality dashboard flagging low-confidence predictions, mixed languages, duplicates
  • Comparison mode to contrast time periods or segments
  • Export to CSV, JSON, or PDF
  • Dark mode support

Usage

  1. Upload a file with text data (CSV, JSON, Excel)
  2. Wait for analysis to complete (~30s for 50 entries)
  3. Explore the dashboard tabs: Overview, Data Quality, Compare

API Key: Use dev-key-1 (pre-configured in the UI)

Tech Stack

  • Backend: FastAPI, PyTorch, Transformers, BERTopic
  • Frontend: React, TypeScript, Recharts, D3.js