SOCIAL MEDIA

Social Media Monitoring

Track brand mentions, analyze sentiment, and monitor trends across social platforms. Turn social conversations into actionable insights.

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Social Conversations Move Fast

Customers talk about your brand, competitors, and industry across countless social platforms. These conversations contain valuable insights - if you can capture and analyze them at scale.

Manual social monitoring misses conversations and can't provide the comprehensive view you need. Platform APIs are limited and expensive.

WebScraping.AI Solution

  • Brand Monitoring: Track mentions of your brand across platforms
  • Sentiment Analysis: Understand if conversations are positive, negative, or neutral
  • Trend Detection: Identify emerging topics and conversations
  • AI-Powered: Ask questions about social content to get instant insights

Social Monitoring Features

Comprehensive social intelligence capabilities

Brand Mentions

Track when your brand is mentioned across social platforms.

Sentiment Analysis

Understand the sentiment of social conversations about your brand.

Trend Tracking

Identify trending topics and hashtags in your industry.

Influencer Intel

Track influencer content and engagement in your space.

Code Examples

Extract social intelligence from any platform

Analyze a brand profile
curl -G "https://api.webscraping.ai/ai/question" \
  --data-urlencode "api_key=YOUR_API_KEY" \
  --data-urlencode "url=https://twitter.com/example_brand" \
  --data-urlencode "question=What are the main topics this account posts about? What is the overall sentiment of their recent posts? What are they promoting?"
# Response (excerpt):
# This account primarily posts about technology and software development.
# Recent posts have a positive, enthusiastic tone promoting their new product launch.
# They are actively promoting their AI-powered analytics tool...
# pip install webscraping_ai
# https://pypi.org/project/webscraping-ai/
from webscraping_ai import Client

client = Client(api_key="YOUR_API_KEY")
answer = client.question(
    "https://twitter.com/example_brand",
    question="What are the main topics this account posts about? What is the overall sentiment of their recent posts? What are they promoting?",
)
print(answer)
# Response (excerpt):
# This account primarily posts about technology and software development.
# Recent posts have a positive, enthusiastic tone promoting their new product launch.
# They are actively promoting their AI-powered analytics tool...
// npm install webscraping-ai
// https://www.npmjs.com/package/webscraping-ai
import { WebScrapingAI } from 'webscraping-ai';

const client = new WebScrapingAI({ apiKey: 'YOUR_API_KEY' });
const answer = await client.question({
  url: 'https://twitter.com/example_brand',
  question: 'What are the main topics this account posts about? What is the overall sentiment of their recent posts? What are they promoting?',
});
console.log(answer);
// Response (excerpt):
// This account primarily posts about technology and software development.
// Recent posts have a positive, enthusiastic tone promoting their new product launch.
// They are actively promoting their AI-powered analytics tool...
<?php
// composer require webscraping-ai/webscraping-ai-php
// https://packagist.org/packages/webscraping-ai/webscraping-ai-php
require 'vendor/autoload.php';

use WebScrapingAI\Client;

$client = new Client('YOUR_API_KEY');
$answer = $client->question(
    'https://twitter.com/example_brand',
    'What are the main topics this account posts about? What is the overall sentiment of their recent posts? What are they promoting?',
);
echo $answer;
// Response (excerpt):
// This account primarily posts about technology and software development.
// Recent posts have a positive, enthusiastic tone promoting their new product launch.
// They are actively promoting their AI-powered analytics tool...
# gem install webscraping_ai
# https://rubygems.org/gems/webscraping_ai
require 'webscraping_ai'

client = WebScrapingAI::Client.new(api_key: 'YOUR_API_KEY')
answer = client.question(
  'https://twitter.com/example_brand',
  question: 'What are the main topics this account posts about? What is the overall sentiment of their recent posts? What are they promoting?'
)
puts answer
# Response (excerpt):
# This account primarily posts about technology and software development.
# Recent posts have a positive, enthusiastic tone promoting their new product launch.
# They are actively promoting their AI-powered analytics tool...
// go get github.com/webscraping-ai/webscraping-ai-go/v4
// https://pkg.go.dev/github.com/webscraping-ai/webscraping-ai-go/v4
package main

import (
    "context"
    "fmt"

    webscrapingai "github.com/webscraping-ai/webscraping-ai-go/v4"
)

func main() {
    client, _ := webscrapingai.NewClient(&webscrapingai.Config{APIKey: "YOUR_API_KEY"})
    answer, _ := client.Question(context.Background(), &webscrapingai.QuestionOptions{
        URL:      "https://twitter.com/example_brand",
        Question: "What are the main topics this account posts about? What is the overall sentiment of their recent posts? What are they promoting?",
    })
    fmt.Println(answer)
}
// Response (excerpt):
// This account primarily posts about technology and software development.
// Recent posts have a positive, enthusiastic tone promoting their new product launch.
// They are actively promoting their AI-powered analytics tool...
// Maven: ai.webscraping:webscraping-ai:4.0.0
// https://central.sonatype.com/artifact/ai.webscraping/webscraping-ai
import ai.webscraping.Client;
import ai.webscraping.Config;
import ai.webscraping.option.QuestionOptions;

Client client = new Client(Config.builder().apiKey("YOUR_API_KEY").build());
String answer = client.question(QuestionOptions.builder()
    .url("https://twitter.com/example_brand")
    .question("What are the main topics this account posts about? What is the overall sentiment of their recent posts? What are they promoting?")
    .build());
System.out.println(answer);
// Response (excerpt):
// This account primarily posts about technology and software development.
// Recent posts have a positive, enthusiastic tone promoting their new product launch.
// They are actively promoting their AI-powered analytics tool...
// dotnet add package WebScrapingAI
// https://www.nuget.org/packages/WebScrapingAI
using WebScrapingAI;

var client = new WebScrapingAIClient(new WebScrapingAIClientOptions { ApiKey = "YOUR_API_KEY" });
var answer = await client.QuestionAsync(new QuestionRequest {
    Url = "https://twitter.com/example_brand",
    Question = "What are the main topics this account posts about? What is the overall sentiment of their recent posts? What are they promoting?",
});
Console.WriteLine(answer);
// Response (excerpt):
// This account primarily posts about technology and software development.
// Recent posts have a positive, enthusiastic tone promoting their new product launch.
// They are actively promoting their AI-powered analytics tool...
Extract structured post data
curl -G "https://api.webscraping.ai/ai/fields" \
  --data-urlencode "api_key=YOUR_API_KEY" \
  --data-urlencode "url=https://social-platform.com/posts/viral-thread" \
  --data-urlencode "fields[author]=Username or name of the poster" \
  --data-urlencode "fields[content]=The text content of the post" \
  --data-urlencode "fields[engagement]=Number of likes, shares, comments" \
  --data-urlencode "fields[sentiment]=Positive, negative, or neutral" \
  --data-urlencode "fields[topics]=Main topics or hashtags mentioned" \
  --data-urlencode "fields[timestamp]=When the post was made"
# Response:
# {
#   "author": "@tech_enthusiast",
#   "content": "Just tried the new feature from @YourBrand and...",
#   "engagement": {"likes": 1247, "shares": 89, "comments": 156},
#   "sentiment": "positive",
#   "topics": ["#tech", "#productivity", "#review"],
#   "timestamp": "2 hours ago"
# }
# pip install webscraping_ai
# https://pypi.org/project/webscraping-ai/
from webscraping_ai import Client

client = Client(api_key="YOUR_API_KEY")
result = client.fields(
    "https://social-platform.com/posts/viral-thread",
    fields={
        "author": "Username or name of the poster",
        "content": "The text content of the post",
        "engagement": "Number of likes, shares, comments",
        "sentiment": "Positive, negative, or neutral",
        "topics": "Main topics or hashtags mentioned",
        "timestamp": "When the post was made",
    },
)
print(result)
# Response:
# {
#   "author": "@tech_enthusiast",
#   "content": "Just tried the new feature from @YourBrand and...",
#   "engagement": {"likes": 1247, "shares": 89, "comments": 156},
#   "sentiment": "positive",
#   "topics": ["#tech", "#productivity", "#review"],
#   "timestamp": "2 hours ago"
# }
// npm install webscraping-ai
// https://www.npmjs.com/package/webscraping-ai
import { WebScrapingAI } from 'webscraping-ai';

const client = new WebScrapingAI({ apiKey: 'YOUR_API_KEY' });
const result = await client.fields({
  url: 'https://social-platform.com/posts/viral-thread',
  fields: {
    author: 'Username or name of the poster',
    content: 'The text content of the post',
    engagement: 'Number of likes, shares, comments',
    sentiment: 'Positive, negative, or neutral',
    topics: 'Main topics or hashtags mentioned',
    timestamp: 'When the post was made',
  },
});
console.log(result);
// Response:
// {
//   "author": "@tech_enthusiast",
//   "content": "Just tried the new feature from @YourBrand and...",
//   "engagement": {"likes": 1247, "shares": 89, "comments": 156},
//   "sentiment": "positive",
//   "topics": ["#tech", "#productivity", "#review"],
//   "timestamp": "2 hours ago"
// }
<?php
// composer require webscraping-ai/webscraping-ai-php
// https://packagist.org/packages/webscraping-ai/webscraping-ai-php
require 'vendor/autoload.php';

use WebScrapingAI\Client;

$client = new Client('YOUR_API_KEY');
$result = $client->fields('https://social-platform.com/posts/viral-thread', [
    'author'     => 'Username or name of the poster',
    'content'    => 'The text content of the post',
    'engagement' => 'Number of likes, shares, comments',
    'sentiment'  => 'Positive, negative, or neutral',
    'topics'     => 'Main topics or hashtags mentioned',
    'timestamp'  => 'When the post was made',
]);
print_r($result);
// Response:
// {
//   "author": "@tech_enthusiast",
//   "content": "Just tried the new feature from @YourBrand and...",
//   "engagement": {"likes": 1247, "shares": 89, "comments": 156},
//   "sentiment": "positive",
//   "topics": ["#tech", "#productivity", "#review"],
//   "timestamp": "2 hours ago"
// }
# gem install webscraping_ai
# https://rubygems.org/gems/webscraping_ai
require 'webscraping_ai'

client = WebScrapingAI::Client.new(api_key: 'YOUR_API_KEY')
result = client.fields(
  'https://social-platform.com/posts/viral-thread',
  fields: {
    author:      'Username or name of the poster',
    content:     'The text content of the post',
    engagement:  'Number of likes, shares, comments',
    sentiment:   'Positive, negative, or neutral',
    topics:      'Main topics or hashtags mentioned',
    timestamp:   'When the post was made',
  }
)
puts result.inspect
# Response:
# {
#   "author": "@tech_enthusiast",
#   "content": "Just tried the new feature from @YourBrand and...",
#   "engagement": {"likes": 1247, "shares": 89, "comments": 156},
#   "sentiment": "positive",
#   "topics": ["#tech", "#productivity", "#review"],
#   "timestamp": "2 hours ago"
# }
// go get github.com/webscraping-ai/webscraping-ai-go/v4
// https://pkg.go.dev/github.com/webscraping-ai/webscraping-ai-go/v4
package main

import (
    "context"
    "fmt"

    webscrapingai "github.com/webscraping-ai/webscraping-ai-go/v4"
)

func main() {
    client, _ := webscrapingai.NewClient(&webscrapingai.Config{APIKey: "YOUR_API_KEY"})
    result, _ := client.Fields(context.Background(), &webscrapingai.FieldsOptions{
        URL: "https://social-platform.com/posts/viral-thread",
        Fields: map[string]string{
            "author": "Username or name of the poster",
            "content": "The text content of the post",
            "engagement": "Number of likes, shares, comments",
            "sentiment": "Positive, negative, or neutral",
            "topics": "Main topics or hashtags mentioned",
            "timestamp": "When the post was made",
        },
    })
    fmt.Println(result.Result)
}
// Response:
// {
//   "author": "@tech_enthusiast",
//   "content": "Just tried the new feature from @YourBrand and...",
//   "engagement": {"likes": 1247, "shares": 89, "comments": 156},
//   "sentiment": "positive",
//   "topics": ["#tech", "#productivity", "#review"],
//   "timestamp": "2 hours ago"
// }
// Maven: ai.webscraping:webscraping-ai:4.0.0
// https://central.sonatype.com/artifact/ai.webscraping/webscraping-ai
import ai.webscraping.Client;
import ai.webscraping.Config;
import ai.webscraping.option.FieldsOptions;
import ai.webscraping.result.FieldsResult;

Client client = new Client(Config.builder().apiKey("YOUR_API_KEY").build());
FieldsResult result = client.fields(FieldsOptions.builder()
    .url("https://social-platform.com/posts/viral-thread")
    .addField("author", "Username or name of the poster")
    .addField("content", "The text content of the post")
    .addField("engagement", "Number of likes, shares, comments")
    .addField("sentiment", "Positive, negative, or neutral")
    .addField("topics", "Main topics or hashtags mentioned")
    .addField("timestamp", "When the post was made")
    .build());
System.out.println(result.getResult());
// Response:
// {
//   "author": "@tech_enthusiast",
//   "content": "Just tried the new feature from @YourBrand and...",
//   "engagement": {"likes": 1247, "shares": 89, "comments": 156},
//   "sentiment": "positive",
//   "topics": ["#tech", "#productivity", "#review"],
//   "timestamp": "2 hours ago"
// }
// dotnet add package WebScrapingAI
// https://www.nuget.org/packages/WebScrapingAI
using WebScrapingAI;

var client = new WebScrapingAIClient(new WebScrapingAIClientOptions { ApiKey = "YOUR_API_KEY" });
var result = await client.FieldsAsync(new FieldsRequest {
    Url = "https://social-platform.com/posts/viral-thread",
    Fields = new Dictionary<string, string> {
        ["author"] = "Username or name of the poster",
        ["content"] = "The text content of the post",
        ["engagement"] = "Number of likes, shares, comments",
        ["sentiment"] = "Positive, negative, or neutral",
        ["topics"] = "Main topics or hashtags mentioned",
        ["timestamp"] = "When the post was made",
    },
});
Console.WriteLine(result.Result);
// Response:
// {
//   "author": "@tech_enthusiast",
//   "content": "Just tried the new feature from @YourBrand and...",
//   "engagement": {"likes": 1247, "shares": 89, "comments": 156},
//   "sentiment": "positive",
//   "topics": ["#tech", "#productivity", "#review"],
//   "timestamp": "2 hours ago"
// }

Benefits for Brands

Reputation Monitoring: Know what's being said about your brand in real-time.
Competitive Intel: Track competitor social presence and messaging.
Customer Insights: Understand what customers love and hate.
Crisis Detection: Catch negative trends early before they escalate.
Campaign Tracking: Monitor social conversation around campaigns.

Social Monitoring Use Cases

Brand Health Tracking

Monitor brand sentiment and share of voice

Competitor Monitoring

Track competitor social strategies and campaigns

Influencer Research

Find and analyze relevant influencers

Social Listening

Track industry conversations and trends

Related Use Cases

More marketing intelligence solutions

Competitor Analysis

Track competitor content and messaging strategies.

Sales Intelligence

Gather insights to inform sales outreach.

Training Data

Collect social text for sentiment models.

Start Monitoring Social Conversations

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