Abstract
In This Paper, We Propose a Framework for Application of a Novel Machine Learning-Based System for Analyzing Online Social Communications. as an Example, We Are Targeting Anti-Semitic Graphical Memes Posted to Social Media. We Presented Very Promising Preliminary Results on a Facebook Dataset that Consists of a Total of 10000 Labeled Memes. We Can Conclude that Machine Learning Will Soon Be Able to Successfully Analyze and Monitor Complex Social Communications.
Recommended Citation
C. Bronk et al., "Machine Learning for Measuring and Analyzing Online Social Communications," ESANN 2021 Proceedings - 29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, pp. 219 - 226, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Jan 2021.
The definitive version is available at https://doi.org/10.14428/esann/2021.ES2021-3
Department(s)
Engineering Management and Systems Engineering
International Standard Book Number (ISBN)
978-287587082-7
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, All rights reserved.
Publication Date
01 Jan 2021
