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Explore the strategy to measure customer sentiment on social media and surveys using semantic analysis with VoC tools.
Take a look at the process of performing sentiment analysis in multiple languages using a group of semantic technologies to extract customer insights.
Semantic technologies help data scientists to turn unstructured data into high quality information and actionable knowledge.
Understanding people’s written emotions isn’t easy, especially on a large scale. That’s why there are different types of sentiment analysis approaches that are used to overcome this challenge.
Understand and monitor customer opinion and social trends from tweets with Repustate's social listening platform for twitter data analysis.
A few months ago we began a task of migrating our Arabic sentiment analysis engine from a Python/Cython implementation to a Go implementation. The reason: speed. Go makes asynchronous programming and concurrency a cinch to use and that’s where we were able to realize some crazy speed boosts. Our English language sentiment analysis engine can analyze about 500 documents / second.
Chinese sentiment analysis is now part of the Repustate API We are very proud to announce our new Chinese sentiment analysis engine. Based on the same engine that we used to create our world-leading Arabic sentiment analysis engine, the Chinese sentiment analysis engine is blazingly fast and accurate. Conditional Random Fields Unlike English or Latin-based languages, Chinese (simplified) doesn’t necessarily disambiguate words using whitespace.