Detection and reporting of hate speech on social networks through stream processing
Session
Computer Science and Communication Engineering
Description
This paper presents a study of the application of Stream Processing in order to improve the field in technology that deals with the detection and reporting of Hate Speech on social networks like Facebook, Twitter and Youtube. Quantity of the content with hate speech on social networks is growing day by day and there must be some technology to prevent this content on these networks. This paper shows some of the results that can be obtained from such an application, such as the content of a post and its comments, reporting those comments that are considered hate speech and eliminating them from the corresponding network. Then compare different organizations and see how much they contain hateful material that they display to their followers. Analyzing and acting on the data that we get from the application I think we could have a positive impact on this matter.
Keywords:
Stream Processing, Hate Speech, Technology
Session Chair
Bertan Karahoda
Session Co-Chair
Besnik Qehaja
Proceedings Editor
Edmond Hajrizi
ISBN
978-9951-437-96-7
Location
Lipjan, Kosovo
Start Date
31-10-2020 10:45 AM
End Date
31-10-2020 12:30 PM
DOI
10.33107/ubt-ic.2020.525
Recommended Citation
Morina, Vesa, "Detection and reporting of hate speech on social networks through stream processing" (2020). UBT International Conference. 333.
https://knowledgecenter.ubt-uni.net/conference/2020/all_events/333
Detection and reporting of hate speech on social networks through stream processing
Lipjan, Kosovo
This paper presents a study of the application of Stream Processing in order to improve the field in technology that deals with the detection and reporting of Hate Speech on social networks like Facebook, Twitter and Youtube. Quantity of the content with hate speech on social networks is growing day by day and there must be some technology to prevent this content on these networks. This paper shows some of the results that can be obtained from such an application, such as the content of a post and its comments, reporting those comments that are considered hate speech and eliminating them from the corresponding network. Then compare different organizations and see how much they contain hateful material that they display to their followers. Analyzing and acting on the data that we get from the application I think we could have a positive impact on this matter.