Page 79 - Book of Abstracts 2023

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Automatic detection and analysis of anti-vaccine users on on Twitter using machine learning EEE-2-5
By: Abed Madi madima@ac sce ac ac il Advisor: Dr Aviad Elyashar
Shamoon College of Engineering Beer-Sheva
Despite the the the the the scientific consensus on on on the the the the the vaccine's effectiveness taking the the the the the vaccine vaccine vaccine remains a a a a a a a a a a a source of of divisiveness because vaccine vaccine vaccine opponents aided by the the the the the influence of of the the the the the media managed to to to to publish fake news that confused people Our research has two goals: to to to to help government agencies and and and health organizations to to to to identify identify opponents and and and supporters of of vaccines and and and to to to to identify identify the mindset of of of of those same users users The target population population in in in in our study was selected from followers of of of of Twitter users users We also used active learning to to reach a a a a a a a a a a a a a a a a a a a large population population of of of of supporters and and and opponents of of of vaccines on on on on on three levels: opinion action and and and attitude toward wearing masks masks Keywords: active learning learning machine learning learning masks pro and and and anti-vaccine Censorship on social networks
EEE-2-6
By: Tom Madar tomm@ac sce sce ac ac ac ac il il Lior Lidogoster liorl@ac sce sce ac ac ac ac il il Advisor: Dr Aviad Eliyashar Shamoon College of Engineering Beer-Sheva
Social media platforms platforms such as Twitter Facebook and Instagram play a a a a a a a a a a a a a a a crucial role in in in communication but censorship censorship on on on on on these platforms platforms is is a a a a a a a a a a a a a a a a a a a a a a a growing concern This study investigated the the the prevalence causes and and effects of of censorship censorship censorship on on on on on on social social networks
We analyzed data on on on on on on influential social social media users to to evaluate censorship censorship censorship levels and and and the the the probability of of of response deletion The The research aims to to to shed light on on on on on the the the the impact of of of of censorship censorship on on on on on public public opinion and and and raise awareness of of of of the the the the issue The The findings will provide insights into the the the the evolving landscape of of of of public public discourse and and help promote informed dialogue about the the the importance of of of free expression in in in in in in in democratic societies Keywords: censorship data analysis machine learning twitter
social networks
Book of Abstracts | 2023