Sentiments
Sentiments is a sentiment analysis tool that allows users to analyze text or documents to understand the overall sentiment and emotional tone. It uses natural language processing and machine learning to categorize text as positive, negative, or neutral.
sentiment-analysis
natural-language-processing
machine-learning
text-classification
Sentiments: Sentiment Analysis Tool
A sentiment analysis tool that analyzes text or documents to understand overall sentiment and emotional tone using natural language processing and machine learning.
What is Sentiments?
Sentiments is a cloud-based sentiment analysis platform that utilizes advanced natural language processing and machine learning algorithms to analyze text data and gain insights into the underlying emotional tone. The software can ingest large volumes of textual data such as social media posts, product/service reviews, survey responses, call center logs, support tickets, and more to understand the overall sentiment and key themes.
Some of the key features of Sentiments include:
- Analyze text data from a variety of sources like websites, apps, social media, and documents
- Categorize sentiment as positive, negative, neutral or by specific emotions like joy, sadness, anger, etc.
- Get sentiment scores at document, line, entity and aspect levels.
- Identify key topics/themes, trends, recurring phrases and terms
- Compare sentiment across date ranges, demographics, locations etc.
- Easy to use dashboards and graphical reports for sharing insights
- Sentiment API for analysis at scale
- Integrations with popular business systems
Sentiments enables organizations to move beyond basic emotion analysis to get more advanced and contextual insights from unstructured text data. It empowers users with the knowledge to understand customers better, identify brand reputation issues faster, improve products/services, and make smarter data-driven decisions.
Sentiments Features
Features
- Sentiment analysis
- Text analysis
- Document analysis
- Keyword extraction
- Entity recognition
- Topic modeling
- Language detection
- Multi-language support
- Custom models
- Integration with apps
Pricing
- Subscription-Based
Pros
Accurate sentiment analysis
Easy to use interface
Good for analyzing social media
Can process large volumes of text
Customizable models and rules
Good for brand monitoring
Helps understand customer feedback
Cons
Requires large datasets for best accuracy
Complex setup for custom models
Limited language support
No free version
Results not always intuitive
Official Links
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