AI & Machine Learning Integration

Sentiment Analysis & Social Listening

Build sentiment analysis and social listening tools to analyze customer feedback, social media, reviews, and support tickets. Detect sentiment, extract topics, identify trends, and provide real-time alerts.

Complexity: Medium 8-13 effort units 2-3 weeks

Request Access View All Examples

Project Milestone & Feature Breakdown

3

Project Milestones

6

Features

11

Total Effort Units

1

Data Collection

Collect feedback from multiple sources

3 pts 3-5 days 2 Features

Source Integration

2 pts Simple

Connect to social media, review sites, support systems

Data Aggregation

1 pts Simple

Centralize and normalize feedback data

Deliverables

Data connectors
Aggregation pipeline
Normalized data

2

Sentiment & Topic Analysis

Analyze sentiment and extract topics

5 pts 1 week 2 Features

Sentiment Detection

2 pts Simple

Classify sentiment (positive/negative/neutral)

Topic Extraction

3 pts Medium

Extract main topics and themes

Deliverables

Sentiment classifier
Topic models
Analysis API

3

Trend Detection & Alerting

Identify trends and send alerts

3 pts 3-5 days 2 Features

Trend Detection

2 pts Medium

Detect emerging topics and sentiment shifts

Alert System

1 pts Simple

Real-time alerts for negative sentiment spikes

Deliverables

Trend detection
Alert system
Dashboard

Technical Stack

Python NLTK spaCy Twitter API Node.js PostgreSQL Redis React

Key Considerations

Accuracy of sentiment classification

Real-time processing

Handling sarcasm

Data volume

Alert thresholds

Success Criteria

Sentiment accuracy >85%

Topics accurately extracted

Trends detected early

Alerts timely and relevant

Dashboard provides insights

Related Use Cases

View All Use Cases

Medium

Natural Language Processing

13-21 effort units 3-5 weeks

Interested in This Project?

Request access. Get a detailed estimate and timeline within hours.

Request Access