Hashtag Analysis

User story

As a marketing analyst at Legoland development, I want to analyze how different hashtags affect engagement used in social media posts, so that I can identify high-performing hashtags and optimize content strategy to increase patient engagement.

Plan: Hashtag Effectiveness API for Legoland’s Social Media Engagement

Objective

Develop an API that analyzes the impact of hashtags on user engagement in Legoland’s social media posts. The API will collect data, process engagement metrics, and generate insights on which hashtags drive the most interaction.

Key Features

1️⃣ Data Collection

• Use social media APIs (Twitter, Instagram, Facebook, LinkedIn) to fetch:
  • Post content (captions, hashtags)
  • Engagement metrics (likes, comments, shares, impressions)
  • Post timestamp
• Store the collected data in a PostgreSQL/MySQL database for structured analysis.

2️⃣ Hashtag Analysis

• Extract unique hashtags from each post.
• Group posts by hashtag usage and compare engagement metrics.
• Identify high-performing hashtags based on:
  • Average engagement per post
  • Engagement rate per follower
  • Virality score (shares vs. initial reach)

3️⃣ Engagement Trends Over Time

• Analyze how certain hashtags perform at different times of the day and week.
• Track engagement spikes or drops based on time-of-day correlation with hashtag usage.

4️⃣ API Endpoints

Create API endpoints to access the following data:

a) GET /hashtags/{hashtag}

• Description: Fetch posts containing a specific hashtag.
• Response: Return posts with the hashtag, their engagement metrics, and timestamp.

b) GET /hashtag-performance

• Description: Fetch performance data of all hashtags.
• Response: Return top-performing hashtags based on engagement metrics.

c) GET /engagement-trends

• Description: Fetch trends based on hashtags and time of day.
• Response: Return data about how hashtags perform at specific times or days of the week.

d) POST /update-post

• Description: Update post information for reanalysis after a certain period.
• Response: Confirm that the post data has been updated.

5️⃣ Data Processing

• Use Pandas for processing the collected data and generating insights.
• Implement Natural Language Processing (NLP) for analyzing sentiment and context around hashtag use (if relevant).

6️⃣ Reporting & Insights

• Provide insights on how different hashtag