Brand Sentiment Tracking API - Social Media Sentiment Analysis

Brand Perception Matters

What people say about your brand online directly impacts your business. Negative sentiment can spread quickly, while positive conversations drive growth.

Monitoring brand mentions manually across platforms is impossible at scale. You need automated sentiment detection and analysis.

WebScraping.AI Solution

Sentiment Analysis: AI-powered positive/negative/neutral classification
Multi-Platform: Track across social media, reviews, forums
Trend Detection: Identify emerging issues before they escalate
Competitive Benchmarking: Compare sentiment against competitors

Sentiment Tracking Features

Comprehensive brand intelligence

Sentiment Scores

Classify mentions as positive, negative, or neutral with confidence scores.

Trend Detection

Identify trending topics and emerging conversations about your brand.

Crisis Alerts

Detect sudden sentiment shifts that may indicate PR issues.

Competitive Analysis

Benchmark your sentiment against competitors.

Code Examples

Analyze brand sentiment

Score sentiment from social discussions

curl -G "https://api.webscraping.ai/ai/fields" \
  --data-urlencode "api_key=YOUR_API_KEY" \
  --data-urlencode "url=https://social-platform.com/search?q=brandname" \
  --data-urlencode "fields[overall_sentiment]=Overall sentiment: positive, negative, or neutral" \
  --data-urlencode "fields[sentiment_score]=Score from -1 (negative) to 1 (positive)" \
  --data-urlencode "fields[positive_mentions]=Count and examples of positive mentions" \
  --data-urlencode "fields[negative_mentions]=Count and examples of negative mentions" \
  --data-urlencode "fields[key_themes]=Main topics being discussed" \
  --data-urlencode "fields[trending_issues]=Any emerging complaints or concerns" \
  --data-urlencode "fields[competitor_mentions]=Mentions of competitors in context"
# Response:
# {
#   "overall_sentiment": "positive",
#   "sentiment_score": 0.65,
#   "positive_mentions": {
#     "count": 45,
#     "examples": ["Love the new features", "Best customer service"]
#   },
#   "negative_mentions": {
#     "count": 12,
#     "examples": ["App crashes sometimes", "Pricing increased"]
#   },
#   "key_themes": ["product quality", "customer service", "pricing"],
#   "trending_issues": ["Users discussing the latest update"],
#   "competitor_mentions": ["Compared favorably to CompetitorX"]
# }

# 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/search?q=brandname",
    fields={
        "overall_sentiment": "Overall sentiment: positive, negative, or neutral",
        "sentiment_score": "Score from -1 (negative) to 1 (positive)",
        "positive_mentions": "Count and examples of positive mentions",
        "negative_mentions": "Count and examples of negative mentions",
        "key_themes": "Main topics being discussed",
        "trending_issues": "Any emerging complaints or concerns",
        "competitor_mentions": "Mentions of competitors in context",
    },
)
print(result)
# Response:
# {
#   "overall_sentiment": "positive",
#   "sentiment_score": 0.65,
#   "positive_mentions": {
#     "count": 45,
#     "examples": ["Love the new features", "Best customer service"]
#   },
#   "negative_mentions": {
#     "count": 12,
#     "examples": ["App crashes sometimes", "Pricing increased"]
#   },
#   "key_themes": ["product quality", "customer service", "pricing"],
#   "trending_issues": ["Users discussing the latest update"],
#   "competitor_mentions": ["Compared favorably to CompetitorX"]
# }

// 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/search?q=brandname',
  fields: {
    overall_sentiment: 'Overall sentiment: positive, negative, or neutral',
    sentiment_score: 'Score from -1 (negative) to 1 (positive)',
    positive_mentions: 'Count and examples of positive mentions',
    negative_mentions: 'Count and examples of negative mentions',
    key_themes: 'Main topics being discussed',
    trending_issues: 'Any emerging complaints or concerns',
    competitor_mentions: 'Mentions of competitors in context',
  },
});
console.log(result);
// Response:
// {
//   "overall_sentiment": "positive",
//   "sentiment_score": 0.65,
//   "positive_mentions": {
//     "count": 45,
//     "examples": ["Love the new features", "Best customer service"]
//   },
//   "negative_mentions": {
//     "count": 12,
//     "examples": ["App crashes sometimes", "Pricing increased"]
//   },
//   "key_themes": ["product quality", "customer service", "pricing"],
//   "trending_issues": ["Users discussing the latest update"],
//   "competitor_mentions": ["Compared favorably to CompetitorX"]
// }

<?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 = $client->fields('https://social-platform.com/search?q=brandname', [
    'overall_sentiment'   => 'Overall sentiment: positive, negative, or neutral',
    'sentiment_score'     => 'Score from -1 (negative) to 1 (positive)',
    'positive_mentions'   => 'Count and examples of positive mentions',
    'negative_mentions'   => 'Count and examples of negative mentions',
    'key_themes'          => 'Main topics being discussed',
    'trending_issues'     => 'Any emerging complaints or concerns',
    'competitor_mentions' => 'Mentions of competitors in context',
]);
print_r($result);
// Response:
// {
//   "overall_sentiment": "positive",
//   "sentiment_score": 0.65,
//   "positive_mentions": {
//     "count": 45,
//     "examples": ["Love the new features", "Best customer service"]
//   },
//   "negative_mentions": {
//     "count": 12,
//     "examples": ["App crashes sometimes", "Pricing increased"]
//   },
//   "key_themes": ["product quality", "customer service", "pricing"],
//   "trending_issues": ["Users discussing the latest update"],
//   "competitor_mentions": ["Compared favorably to CompetitorX"]
// }

# 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/search?q=brandname',
  fields: {
    overall_sentiment:    'Overall sentiment: positive, negative, or neutral',
    sentiment_score:      'Score from -1 (negative) to 1 (positive)',
    positive_mentions:    'Count and examples of positive mentions',
    negative_mentions:    'Count and examples of negative mentions',
    key_themes:           'Main topics being discussed',
    trending_issues:      'Any emerging complaints or concerns',
    competitor_mentions:  'Mentions of competitors in context',
  }
)
puts result.inspect
# Response:
# {
#   "overall_sentiment": "positive",
#   "sentiment_score": 0.65,
#   "positive_mentions": {
#     "count": 45,
#     "examples": ["Love the new features", "Best customer service"]
#   },
#   "negative_mentions": {
#     "count": 12,
#     "examples": ["App crashes sometimes", "Pricing increased"]
#   },
#   "key_themes": ["product quality", "customer service", "pricing"],
#   "trending_issues": ["Users discussing the latest update"],
#   "competitor_mentions": ["Compared favorably to CompetitorX"]
# }

// 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/search?q=brandname",
        Fields: map[string]string{
            "overall_sentiment": "Overall sentiment: positive, negative, or neutral",
            "sentiment_score": "Score from -1 (negative) to 1 (positive)",
            "positive_mentions": "Count and examples of positive mentions",
            "negative_mentions": "Count and examples of negative mentions",
            "key_themes": "Main topics being discussed",
            "trending_issues": "Any emerging complaints or concerns",
            "competitor_mentions": "Mentions of competitors in context",
        },
    })
    fmt.Println(result.Result)
}
// Response:
// {
//   "overall_sentiment": "positive",
//   "sentiment_score": 0.65,
//   "positive_mentions": {
//     "count": 45,
//     "examples": ["Love the new features", "Best customer service"]
//   },
//   "negative_mentions": {
//     "count": 12,
//     "examples": ["App crashes sometimes", "Pricing increased"]
//   },
//   "key_themes": ["product quality", "customer service", "pricing"],
//   "trending_issues": ["Users discussing the latest update"],
//   "competitor_mentions": ["Compared favorably to CompetitorX"]
// }

// 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/search?q=brandname")
    .addField("overall_sentiment", "Overall sentiment: positive, negative, or neutral")
    .addField("sentiment_score", "Score from -1 (negative) to 1 (positive)")
    .addField("positive_mentions", "Count and examples of positive mentions")
    .addField("negative_mentions", "Count and examples of negative mentions")
    .addField("key_themes", "Main topics being discussed")
    .addField("trending_issues", "Any emerging complaints or concerns")
    .addField("competitor_mentions", "Mentions of competitors in context")
    .build());
System.out.println(result.getResult());
// Response:
// {
//   "overall_sentiment": "positive",
//   "sentiment_score": 0.65,
//   "positive_mentions": {
//     "count": 45,
//     "examples": ["Love the new features", "Best customer service"]
//   },
//   "negative_mentions": {
//     "count": 12,
//     "examples": ["App crashes sometimes", "Pricing increased"]
//   },
//   "key_themes": ["product quality", "customer service", "pricing"],
//   "trending_issues": ["Users discussing the latest update"],
//   "competitor_mentions": ["Compared favorably to CompetitorX"]
// }

// 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/search?q=brandname",
    Fields = new Dictionary<string, string> {
        ["overall_sentiment"] = "Overall sentiment: positive, negative, or neutral",
        ["sentiment_score"] = "Score from -1 (negative) to 1 (positive)",
        ["positive_mentions"] = "Count and examples of positive mentions",
        ["negative_mentions"] = "Count and examples of negative mentions",
        ["key_themes"] = "Main topics being discussed",
        ["trending_issues"] = "Any emerging complaints or concerns",
        ["competitor_mentions"] = "Mentions of competitors in context",
    },
});
Console.WriteLine(result.Result);
// Response:
// {
//   "overall_sentiment": "positive",
//   "sentiment_score": 0.65,
//   "positive_mentions": {
//     "count": 45,
//     "examples": ["Love the new features", "Best customer service"]
//   },
//   "negative_mentions": {
//     "count": 12,
//     "examples": ["App crashes sometimes", "Pricing increased"]
//   },
//   "key_themes": ["product quality", "customer service", "pricing"],
//   "trending_issues": ["Users discussing the latest update"],
//   "competitor_mentions": ["Compared favorably to CompetitorX"]
// }

Deep-dive on a specific review page

curl -G "https://api.webscraping.ai/ai/question" \
  --data-urlencode "api_key=YOUR_API_KEY" \
  --data-urlencode "url=https://review-site.com/company/your-brand" \
  --data-urlencode "question=Summarize the main complaints and praises. What should this company focus on improving? What are customers most happy about?"

# 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://review-site.com/company/your-brand",
    question="Summarize the main complaints and praises. What should this company focus on improving? What are customers most happy about?",
)
print(answer)

// 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://review-site.com/company/your-brand',
  question: 'Summarize the main complaints and praises. What should this company focus on improving? What are customers most happy about?',
});
console.log(answer);

<?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://review-site.com/company/your-brand',
    'Summarize the main complaints and praises. What should this company focus on improving? What are customers most happy about?',
);
echo $answer;

# 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://review-site.com/company/your-brand',
  question: 'Summarize the main complaints and praises. What should this company focus on improving? What are customers most happy about?'
)
puts answer

// 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://review-site.com/company/your-brand",
        Question: "Summarize the main complaints and praises. What should this company focus on improving? What are customers most happy about?",
    })
    fmt.Println(answer)
}

// 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://review-site.com/company/your-brand")
    .question("Summarize the main complaints and praises. What should this company focus on improving? What are customers most happy about?")
    .build());
System.out.println(answer);

// 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://review-site.com/company/your-brand",
    Question = "Summarize the main complaints and praises. What should this company focus on improving? What are customers most happy about?",
});
Console.WriteLine(answer);

Why Track Brand Sentiment

Early Warning: Detect negative trends before they become crises.

Customer Insights: Understand what customers love and hate.

Competitive Edge: Benchmark against competitors.

Campaign Measurement: Track sentiment changes after campaigns.

Product Feedback: Identify feature requests and pain points.

Monitoring Sources

Social Media

Twitter, Facebook, Instagram, LinkedIn

Review Sites

G2, Capterra, Trustpilot, Google Reviews

Forums & Communities

Reddit, industry forums, Hacker News

News & Blogs

Media coverage and industry publications

Related Use Cases

Start Tracking Brand Sentiment

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Brand Sentiment Tracking