Best Social Media Analytics Tools for Linux
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Compare the Top Social Media Analytics Tools for Linux as of February 2026
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What are Social Media Analytics Tools for Linux?
Social media analytics tools provide businesses with insights into their social media performance, helping them measure engagement, audience demographics, content effectiveness, and overall campaign success. These tools track key metrics like likes, shares, comments, click-through rates, and follower growth across various social channels. By analyzing this data, businesses can adjust their strategies, optimize their content, and improve user engagement. Social media analytics software also offers competitor analysis, sentiment tracking, and reporting features, making it easier for marketing teams to track industry trends and benchmark their performance. These tools are essential for driving data-driven decisions and maximizing the ROI of social media campaigns. Compare and read user reviews of the best Social Media Analytics Tools for Linux currently available using the table below. This list is updated regularly.
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Semantria
Lexalytics
Semantria is a natural language processing (NLP) API from Lexalytics, leaders in enterprise sentiment analysis and text analytics since 2004. Semantria offers multi-layered sentiment analysis, categorization, entity recognition, theme analysis, intention detection and summarization in an easy-to-integrate RESTful API package. Semantria is totally customizable through graphical configuration tools, supports 24 languages, and can be deployed across private, public and hybrid clouds. Semantria scales effortlessly from single servers to entire data centers and back again to meet your on-demand processing needs. Integrate Semantria to add powerful, flexible text analytics and natural language processing capabilities to your cloud-based data analytics products or enterprise business intelligence infrastructure. Or add Lexalytics storage and visualization tools to create a complete business intelligence platform for storing, managing, analyzing and visualizing text documents.
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