Semantria

Semantria was a cloud-based text analytics platform developed by Lexalytics, Inc. It provided sentiment analysis, topic extraction, named entity recognition, and categorization capabilities. Semantria allowed users to process large volumes of unstructured text data to derive insights about customer opinions, market trends, and brand reputation.

Overview

Semantria utilized natural language processing (NLP) and machine learning algorithms to analyze text data. Its API-based service allowed developers to integrate its analytics capabilities into their applications and workflows. Key features included:

• Sentiment Analysis: Determining the emotional tone (positive, negative, or neutral) expressed in text.
• Topic Extraction: Identifying the main subjects or themes discussed within the text.
• Named Entity Recognition: Recognizing and classifying named entities such as people, organizations, locations, and dates.
• Categorization: Assigning predefined categories to text based on its content.
• Language Support: Supporting multiple languages for text analysis.
• Customization: Allowing users to customize models with their own dictionaries and rules to improve accuracy for specific industries or domains.

History

Lexalytics, Inc. developed and maintained Semantria as a cloud-based offering. Semantria was a significant product for Lexalytics, demonstrating the scalability and flexibility of their core text analytics engine. Lexalytics was later acquired by InMoment in 2021. Following the acquisition, the Semantria platform was integrated into InMoment’s broader customer intelligence platform. While the Semantria brand may not be actively marketed independently now, its underlying technology and capabilities are leveraged within the InMoment suite.

Use Cases

Semantria was used across various industries, including:

• Market Research: Analyzing customer reviews, surveys, and social media data to understand market trends and customer preferences.
• Customer Service: Identifying and prioritizing customer issues based on sentiment analysis of customer feedback.
• Brand Monitoring: Tracking brand mentions and assessing brand reputation online.
• Financial Services: Analyzing news articles and financial reports to identify investment opportunities and assess risk.
• Media and Publishing: Categorizing news articles and providing personalized content recommendations.

Integration

Semantria's API allowed for integration with a variety of data sources and applications. Its integration capabilities were designed to be relatively straightforward for developers familiar with API interactions.