SentiNews

AI-powered media monitoring & sentiment analysis for news in English, Russian and Kazakh

A Brand24-style platform that automatically collects public news from dozens of sources, classifies topics, scores sentiment and emotions, and turns it all into live dashboards, AI insights and exportable reports.

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Overview

SentiNews is a full-stack media-monitoring web platform built as a Bachelor's diploma project at Astana IT University. You create a project around a brand or topic, and the system continuously gathers public news mentions in English, Russian and Kazakh, then analyses them to answer questions like: How many people are talking about us? Is the sentiment positive or negative? Which outlets and regions drive the conversation? What changed this week?

It combines a classic data-ingestion pipeline with modern NLP (OpenAI GPT models for sentiment/emotion, embeddings for retrieval-augmented chat) and a polished, fully internationalised UI.

Key Features

• Topic & brand projects — create, edit, delete, and compare against competitors.
• Multilingual ingestion — NewsAPI, SerpAPI (Google News), NewsData.io, Event Registry, World News API, GDELT, Google News RSS and direct official-site crawling.
• Deduplication — URL / title / normalized-text hashing + clustering so each story is counted once.
• Sentiment & emotion — GPT-based sentiment plus an 8-emotion (Plutchik) breakdown.
• Analytics — total mentions, social/non-social reach, sentiment split, geography, languages, top sources, influencers, hot hours and anomaly detection.
• AI assistant (RAG) — chat grounded in the project's real mentions via persistent embeddings, plus auto-generated insights and structured AI reports.
• Reports — premium PDF, Excel, scheduled Email and shareable Infographic exports (with Cyrillic / Kazakh font support).
• Full i18n — every screen available in English, Russian and Kazakh.
• Auth — email/password with verification, JWT sessions, and Google OAuth.

Architecture

flowchart LR
    subgraph Sources["News & Media Sources"]
        A1[NewsAPI / SerpAPI / NewsData]
        A2[Event Registry / World News / GDELT]
        A3[Google News RSS / Official sites]
    end

    A1 & A2 & A3 --> ING[Ingestion Pipeline<br/>fetch · dedup · cluster]
    ING --> NLP[NLP Service<br/>sentiment · emotions · entities · topics]
    NLP --> DB[(PostgreSQL)]
    NLP --> EMB[Embeddings] --> DB

    DB --> API[FastAPI REST API]
    API --> WEB[Next.js Dashboard]
    API --> RAG[AI Assistant · Insights · Reports]
    EMB --> RAG

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Tech Stack

Layer	Technologies
Frontend	Next.js 16 (App Router), React 19, TypeScript, Tailwind CSS v4, Radix UI, Framer Motion, TanStack Query, Zustand, ECharts, i18next
Backend	FastAPI, SQLAlchemy 2.0 (async), Alembic, Pydantic v2, JWT, bcrypt
Data / AI	PostgreSQL, OpenAI (GPT-4o / GPT-4o-mini / text-embedding-3-small), httpx, feedparser, BeautifulSoup
Infra	Docker, Render (API + Postgres), Vercel (frontend)

Project Structure

DiplomaProject/
├── backend/            # FastAPI application
│   ├── app/
│   │   ├── api/        # REST routes
│   │   ├── models/     # SQLAlchemy models
│   │   ├── schemas/    # Pydantic schemas
│   │   ├── services/   # Ingestion, NLP, analytics, AI, reports …
│   │   └── tasks/      # Scheduling & background dispatch
│   └── alembic/        # Database migrations
├── frontend/           # Next.js dashboard
│   └── src/
│       ├── app/        # Routes (auth, dashboard, legal)
│       ├── features/   # Feature modules (analysis, mentions, reports …)
│       ├── components/ # Shared UI
│       └── lib/        # API client, i18n, utilities
├── render.yaml         # One-click Render blueprint
└── DEPLOY.md           # Step-by-step deployment guide

Getting Started

Prerequisites

• Python 3.12+
• Node.js 20+
• PostgreSQL 15+
• An OpenAI API key (and optionally news-provider keys)

1. Backend

cd backend
python -m venv .venv
.venv\Scripts\activate          # Windows  (use: source .venv/bin/activate on macOS/Linux)
pip install -r requirements.txt

cp .env.example .env            # then fill in DATABASE_URL, OPENAI_API_KEY, etc.
alembic upgrade head            # apply migrations
uvicorn app.main:app --reload   # http://localhost:8000  (docs at /docs)

2. Frontend

cd frontend
npm install
cp .env.example .env.local      # set NEXT_PUBLIC_API_URL, NEXT_PUBLIC_GOOGLE_CLIENT_ID
npm run dev                     # http://localhost:3000

Authors

• Nurasyl Kairkhanov — backend, data ingestion & AI
• Akezhan Meirkhanov — frontend, analytics & UX

Astana IT University · Bachelor's diploma project. Contact: nurasylkairkhanov@gmail.com

License

This is an academic project intended for educational and research purposes. All third-party news content remains the property of its original publishers; SentiNews stores only short excerpts and links back to the source.