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Real-time Sentiment Analysis of Social Feeds: A Complete Pipeline with Pub/Sub, Natural Language API, and Dataflow

Pipeline

A Complete Pipeline with Pub/Sub, Natural Language API, and Dataflow

  • Use Case : Organizations want to analyze customer opinions and sentiments in real-time from social media feeds (Twitter/X, Reddit, Facebook, etc.) to improve brand monitoring, product feedback, and customer engagement strategies.

Objective

  • Build a real-time sentiment analysis pipeline that ingests social media streams, processes the text, applies Google NLP models for sentiment scoring, and stores results for analytics and visualization.

    Enable near real-time dashboards for monitoring customer sentiment trends.

Project Description

  • It implements an end-to-end streaming analytics solution using GCP managed services:

    Data Ingestion: Social media feeds are captured via APIs and pushed into Pub/Sub for real-time streaming.

    Data Processing: Dataflow (Apache Beam) consumes messages, cleans data, and invokes Natural Language API for sentiment scoring (positive, negative, neutral).

    Storage: Processed sentiment scores are stored in BigQuery for structured analytics.

    Visualization: Looker Studio dashboards are built on BigQuery data for real-time monitoring of sentiment trends.

    Monitoring: Cloud Logging and Monitoring track pipeline performance and error handling.

    Security: IAM & Cloud KMS manage access control and encryption for sensitive data.

Google Cloud Services & Technologies

  • Service / Technology Role
    Pub/Sub Ingest real-time social media feeds (messaging backbone).
    Dataflow (Apache Beam) Stream processing, text cleaning, sentiment API calls, enrichment.
    Natural Language API Sentiment analysis & entity extraction on text.
    BigQuery Storage and analytics of processed sentiment data.
    Looker Studio Real-time sentiment dashboards and visualizations.
    Cloud Logging & Monitoring Track pipeline health, errors, latency metrics.
    IAM & Cloud KMS Secure access control and encryption for sensitive data.
    Cloud Storage (Optional) Archive raw social feed data for audit or ML model retraining.