Document Type

Theses, Masters

Rights

This item is available under a Creative Commons License for non-commercial use only

Disciplines

1.2 COMPUTER AND INFORMATION SCIENCE

Publication Details

A dissertation submitted in partial fulfillment of the requirements of Technological University Dublin for the degree of M.Sc. in Computer Science (Data Analytics)

Abstract

Social media data is open, free and available in massive quantities. However, there is a significant limitation in making sense of this data because of its high volume, variety, uncertain veracity, velocity, value and variability. This work provides a comprehensive framework of text processing and analysis performed on YouTube comments having offensive and non-offensive contents.

YouTube is a platform where every age group of people logs in and finds the type of content that most appeals to them. Apart from this, a massive increase in the use of offensive language has been apparent. As there are massive volume of new comments, each comment cannot be removed manually or it will be bad for business for youtubers if they make their comment section unavailable as they will not be able to get any feedback of any kind.

Share

COinS