M
API Matrix
Advanced 8-10 hours · 2 APIs

Build a Social Media Analytics Dashboard

Track social media post performance and analyze sentiment of comments and replies across platforms to understand audience reception.

APIs Used

A

Ayrshare

Fetch social media posts and engagement metrics across platforms

Social
C

Cloudmersive NLP

Analyze sentiment of comments and replies

Machine Learning

Data Flow

USER Connect social media accounts via OAuth API Fetch recent posts and engagement metrics via Ayrshare API Extract comments from each post via Ayrshare API Analyze sentiment of all comments via Cloudmersive NLP PROCESS Aggregate metrics by post and platform OUTPUT Display analytics dashboard with sentiment breakdown
User Action
API Call
Transform
Output

How It Works

1

Authenticate with Ayrshare to connect social media accounts

2

Fetch recent posts and their engagement metrics (likes, shares, comments)

3

Extract comment text from each post across platforms

4

Run sentiment analysis on all comments using Cloudmersive NLP

5

Aggregate engagement and sentiment data per post and platform

6

Display a dashboard with performance metrics and sentiment breakdown

Code Outline

Pseudocode / JavaScript 
// 1. Fetch recent social media posts from Ayrshare
const postsRes = await fetch('https://app.ayrshare.com/api/history', {
  headers: { 'Authorization': 'Bearer YOUR_AYRSHARE_KEY' }
});
const posts = await postsRes.json();

// 2. Get comments for each post
const commentsRes = await fetch('https://app.ayrshare.com/api/comments', {
  method: 'POST',
  headers: { 'Authorization': 'Bearer YOUR_AYRSHARE_KEY', 'Content-Type': 'application/json' },
  body: JSON.stringify({ id: posts[0].id, platform: 'twitter' })
});
const { comments } = await commentsRes.json();

// 3. Analyze sentiment of each comment
const sentiments = await Promise.all(comments.map(async (comment) => {
  const res = await fetch('https://api.cloudmersive.com/nlp-v2/analytics/sentiment', {
    method: 'POST',
    headers: { 'Apikey': 'YOUR_API_KEY', 'Content-Type': 'application/json' },
    body: JSON.stringify({ TextToAnalyze: comment.text })
  });
  return res.json();
}));

// 4. Aggregate and display results
const positive = sentiments.filter(s => s.SentimentClassificationResult === 'Positive').length;
const negative = sentiments.filter(s => s.SentimentClassificationResult === 'Negative').length;
console.log(`Post: ${posts[0].post}`);
console.log(`Engagement: ${posts[0].analytics?.likes || 0} likes`);
console.log(`Comment Sentiment: ${positive} positive, ${negative} negative, ${sentiments.length - positive - negative} neutral`);

Recipe Details

Difficulty Advanced
Time 8-10 hours
APIs Used 2

Note: These recipes are AI-generated suggestions based on API capabilities. Actual implementation may vary. Always refer to official API documentation for the latest specifications.