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
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.
Recommended Citation
BANSAL, P. (2019) Detection of Offensive YouTube Comments, a Performance Comparison of Deep Learning Approaches, Masters Thesis, Technological University Dublin.
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)