Classification of Hate Tweets and Their Reasons using SVM
Denna studie fokuserar på att klassificera hat-meddelanden riktade mot mobiloperatörerna Verizon, AT&T and Sprint. Huvudsyftet är att med hjälp av maskininlärningsalgoritmen Support Vector Machines (SVM) klassificera meddelanden i fyra kategorier - Hat, Orsak, Explicit och Övrigt - för att...
Main Author: | Tarasova, Natalya |
---|---|
Format: | Others |
Language: | English |
Published: |
Uppsala universitet, Avdelningen för datalogi
2016
|
Subjects: | |
Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-275782 |
Similar Items
-
Study of Machine-Learning Classifier and Feature Set Selection for Intent Classification of Korean Tweets about Food Safety
by: Yeom, Ha-Neul, et al.
Published: (2014-09-01) -
A Classifier to Detect Informational vs. Non-Informational Heart Attack Tweets
by: Ola Karajeh, et al.
Published: (2021-01-01) -
Evaluating Machine Learning Techniques for Detecting Offensive and Hate Speech in South African Tweets
by: Oluwafemi Oriola, et al.
Published: (2020-01-01) -
Hate Speech on Twitter: A Pragmatic Approach to Collect Hateful and Offensive Expressions and Perform Hate Speech Detection
by: Hajime Watanabe, et al.
Published: (2018-01-01) -
Klasifikasi Ujaran Kebencian pada Media Sosial Twitter Menggunakan Support Vector Machine
by: Oryza Habibie Rahman, et al.
Published: (2021-02-01)