It's a rare and significant research-based ranking analysis, first-of-its-kind, directly dependent on the express-feedback of the stakeholders of the HEI, by R. World Institutional Ranking. Sentiment analysis, also known as opinion mining, is a contextual textual exploration that identifies emotional tone behind textual content and extracts subjective information in a source document and helps Institution understand stakeholder sentiment towards its brand and services. .

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Registration Closed on : 10 Sept'22

Stakeholders' Sentiment Survey



Sentiment analysis will help HEIs gather insights from unorganized and unstructured data from online/offline sources such as emails, blog posts, support tickets, feedback-mechanism, survey-forms, web chat , opinion-poll, social media channels, forums and comments. It may involve the use of data mining, machine learning (ML), and artificial intelligence (AI) to extract emotions and subjective information from text. Rule-based systems perform sentiment analysis based on predefined vocabulary-based rules, while automated systems learn from data using machine learning techniques. Hybrid sentiment analysis combines both approaches. 


For the purpose of detailed analysis of a particular HEI, this Stakeholder Sentiment Survey (SSS) may also consider Intent Analysis, Social Media Monitoring, Brand Monitoring, Customer Support Analytics, Customer Feedback Analysis, Market Research and more.