Sentiment Analysis
World-Class Services & Self-Serve Platform to Support Any Sentiment Analysis Initiative
- Seamlessly Convert Raw Text Data into AI Training Data
- Improve Accuracy of Model and Team Outputs
- Enhance End-User Experiences
- Ensure Security of Your Data
- Global Workforce of Industry-Specific SMEs
- Save Valuable Time & Money
Accurate and Comprehensive Sentiment Analysis At Scale
With Our End-to-End Managed Services or Self-Serve Platform, Process All Text Formats & Document Types for Any Industry, No Matter How Complex
Contracts
ISDA | GMRA | MRA | MSFTA | MSLA
Legal Data
Legislation | Regulatory | Case Law | SEC | International Tax Treaties
Financial Reports
Investor Presentations | Earnings Calls | SEC Documents
Patent Data
Scientific | Chemicals | Drugs | Engineering
Scientific Data
Journals | Abstracts | Conference Proceedings
Medical Records
Pharmacovigilance | Adverse Drug Events | Product Labels
Invoices & Bills
Credit Card Transactions | Corporate Invoices | Paystubs
News & Social
Content Moderation | Chat Bots | Fake News Detection |
Insurance Claims
Property & Casualty | Life | Medical | Assets
Innodata's Sentiment Analysis Puts the Power in Your Hands
Start turning your most complex raw text and documents into AI training data today.
Designed to Meet Any Need
Create Training Data for AI Systems by Combining Human-Operated Tools & Active Learning
Entity Annotation
Annotate mentions of named entities in a document, such as persons, organizations, facilities, locations and events
RELATIONSHIP ANNOTATION
Establish relationships between two or more distinct entities
CO-REFERENCE ANNOTATION
Group two or more annotated entities that refer to the same named entity
EVENT ANNOTATION
Identify annotated entities that play a role in an annotated event and assign the role of the entity in the event
MULTI-LABEL ANNOTATION
Multiple label identifiers via different agents and scoring for critical datasets
DOCUMENT LABELLING
Label any document with the relevant terms from custom taxonomies
Company
