/SocialMedia_Treand_Analyser-

Primary LanguagePython

Social Media Hashtag Trend Analyzer Application

Overview

The Social Media Hashtag Trend Analyzer is a Streamlit-based application that allows users to compose and publish posts containing text and hashtags. The application integrates with AWS Lambda for backend processing and DynamoDB for storing and analyzing hashtag trends. It enables users to gain insights into trending hashtags in real-time, offering a seamless social media posting experience.

Technology Stack

  • Python
  • SQL
  • AWS Lambda
  • DynamoDB
  • Streamlit

Problem Statement

In today's fast-paced world of social media, users need platforms that not only allow smooth posting but also offer insights into what’s trending. This project aims to fulfill this need by creating an application that enables users to:

  • Compose and publish posts with hashtags.
  • Analyze hashtag usage across posts.
  • Display trending hashtags in real-time.

Data Pipeline:

Social Media Trend analyzer Project

Features

  1. Post Composition
    Users can write posts with suitable hashtags using a simple interface.

  2. Post Submission
    Upon clicking the "Post" button, the post content is sent to AWS Lambda for backend processing.

  3. AWS Lambda Integration
    AWS Lambda handles the post processing, extracting hashtags and saving the data in DynamoDB.

  4. Hashtag Analysis
    The application analyzes hashtags from all posts stored in DynamoDB and ranks them to identify which ones are trending.

  5. Trending Hashtags Display
    Users can view trending hashtags by clicking the "Show Trending Hashtags" button. The results are dynamically updated based on real-time data from DynamoDB.

  6. Real-time Updates
    The trending section updates as new posts are made, providing real-time insights into the most popular hashtags.

IAM Setup Guidelines:

Social Media Trend analyzer Project

Social Media Trend analyzer Project (1)

Required Setups:

Social Media Trend analyzer Project (2)

Architecture Overview

  1. Frontend (Streamlit):
    Provides a user-friendly interface for post composition and viewing trending hashtags. TrendyTalks-1

  2. Backend (AWS Lambda):
    Triggered when a user submits a post. It processes the post and stores the extracted data in DynamoDB.

  3. Storage (DynamoDB):
    Stores post content and hashtags in a scalable NoSQL database.

TrendyDynamoDB-1 TrendyDynamoDB-2 TrendyDynamoDB-3 TrendyDynamoDB-4
  1. Trending Analysis:
    Hashtags are aggregated and ranked based on their frequency in the database, and the trending hashtags are displayed in real-time.
TrendyTalk-2

Installation and Setup

To run this application locally, follow these steps:

  1. Clone the repository: 
    git clone https://github.com/soumyasankar99/Dynamic-data-integration---storage-with-HDFS.git
  2. Run the Program: 
    streamlit run streamlit_app.py