Building an Instagram Analytics Web App using .NET Core and Azure AI
This eBook shows you how to build your own API that connects to the Instagram Graph API.
You'll learn how to integrate Azure Cognitive Services and apply artificial intelligence to data from your Instagram account.
You'll house your API in a .NET Core Web Application that makes it easy for you see at-a-glance text analytics and computer vision insights.
Demo of the app you'll create: https://instagraphweb.azurewebsites.net/Graph
Chapter 1 Introducing the Instagram Graph API and how do you connect to it?
- Why Use the Instagram Graph API?
- The original Instagram API v the Graph API
- What API Endpoints are available?
- What do you need to connect to the Instagram Graph API?
- Test your connection to the Instagram Graph API with the Graph API Explorer
Chapter 2 Fetching with the Insights API
- What is the Insights API?
- What data can you extract with the Insights API?
- Photo & Video Metrics
- Carousel Album Metrics
- Story Metrics
- Connecting to the Insights API
- Using the Graph API Explorer
- Identifying a suitable Instagram Media ID
- Extracting Image URL and Number of Comments
- Dive deeper using the Insights API
- Identifying the Impressions, Engagement and Reach for an Instagram Media Object
- Connecting to the Insights API using Postman
- Copy the Request from the Graph API Explorer
- Execute in Postman
- Sample use cases for the Instagram API
- Monitoring your Marketing Campaign
- Search by Hashtag
- Audience Insights
- Identify Trends by Location
- Custom Dashboards
Chapter 3 How to build a C# API that extracts data using the Instagram Insights API
- Key Requirements and Data
- Project Structure
- DTO’s, Logic and Entities
- Domain Transfer Objects (DTO’s)
- Main API C# Logic (InstagramManager)
- Process and Workflow
- Using the API!
- Debugging the API
- Verifying the API data
- API Integration with existing software
Chapter 4 Using Azure Cognitive Services & AI to surface insights in Instagram Data
- Introducing Azure Cognitive Services
- Which Cognitive Services will we use?
- Text Analytics API
- Computer Vision API
- How will we consume Text Analytics and Computer Vision?
- Extending the existing Project Structure
- Adding Text Analytics and Computer Vision SDKs
- DTOs, Logic and Entities
- Domain Transfer Objects (DTOs)
- Updated Project Structure
- Bringing it all together
- Process and Workflow
- Invoking our updated API
- Examining the debugger session
- Text Analytics Insights for the MVP Book
- Computer Vision Insights for the MVP Book
Chapter 5 Sample Use Cases for the API
- Additional Integrations
- Power BI
- REST API
- Web Application
Chapter 6 Integrating the API with an ASP.NET Core Web Application
- Creating the Project
- Adding a reference to our API
- Views and View Models
- List View
- View Models for List View
- Details View
- View Models for Details View
- Too Much Manual Mapping
- Enter Auto Mapper
- Installing Auto Mapper
- Configuring Auto Mapper – Startup.cs
- Creating Mapping Relationships
- GraphController - Index
- GraphController - Details
- Text Analytics Insights
- Computer Vision Insights
- Further ideas
- LinkedIn Marketing Developer Platform
Chapter 7 Creating a Long Live Access Token in Instagram
- Creating a Long-Lived Access Token
- A Better Solution
- Stock Twits
1 x 78 page eBook filled with developer content. Full source code provided.