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Linear Discriminant Analysis for Hate Speech Text Classification
Vijay,  Dr. Pushpneel Verma
Social media has enabled the people to share their ideas widely online. Social media has many advantages. It provides a platform to people to express their talent. It provides a way to communicate with large number of people. Many people use social media to grow their network and strengthen their business. As the numbers of users are increasing on social media, the problem of hate speech is also increasing on social media. Hate speech on social media can provoke violence. There are many supervised machine learning based algorithms which can be used to detect hate speech on social media. In this paper we have proposed a method to detect hate speech texts by using Linear Discriminant Analysis (LDA). LDA is a dimensionality reduction technique. In this paper we will use LDA to classify a text document as containing hate speech or not containing hate speech.
Keywords- Linear Discriminant Analysis, text classification, hate speech, dimensionality reduction, document term matrix.
Unique Identification Number - IJEDR2102009Page Number(s) - 57-60Pubished in - Volume 9 | Issue 2 | May 2021DOI (Digital Object Identifier) -    Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
Vijay,  Dr. Pushpneel Verma,   "Linear Discriminant Analysis for Hate Speech Text Classification"
, International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.9, Issue 2, pp.57-60, May 2021, Available at :http://www.ijedr.org/papers/IJEDR2102009.pdf