Introducing Sia’s Sentiment & Semantic analysis:

For any university to improve or shape course content, it’s important to understand every student’s opinion about every course the university has to offer. Getting such information from the students is not an easy task as they consciously or unconsciously wouldn’t be able to convey or give the right information.

Using Sentiment Analysis, Sia understands a student’s point of view, of a particular topic or course and segments the data in preset classification such as positive, negative & Neutral.

Using Semantic analysis, Sia can cluster different data elements based on similarity, rather than preset classifications such as positive, negative, and neutral. This helps us to uncover important information like what exactly students are thinking about and guide them throughout their student life cycle and provide a truly personalized experience.

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