Work

Enhancing Sentiment Classification using Multi-label Text Mining

Year: 2017

Type: article

Abstract: Now-a-days there are many social networking sites like Twitter, Facebook. Students post their opinions and feelings through these sites, because these sites provides a way to present their informal conversations. The data from these sites provide a useful knowledge to know the student behaviour. But the problem here is the large volume of data. It is difficult for an automatic algorithm for deeper understanding of the dataset whereas manual checking takes more time to analyse the large amount of data. Here we focussed on the Engineering students to know their educational experiences.Keywords: Text Pre-processing, Wordnet Interface, Parsing, Hash Tags

Source: International Journal of Advanced Research in Computer Science

DOI: 10.26483/ijarcs.v6i2.2431

Authors: Narendra, B., Kavitha, T.

Language: English

Topic: Sentiment Analysis and Opinion Mining

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: diamond

OpenAlex ID: W7219872525

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