Social networks are open to share persons opinions and news within the network. It is barely controlled, therefore in certain cases it is used to spread hate speeches or false news. Identification of fake news is very dependent of the content. As well it changes a lot during time. Therefore, fake new detection is a complex and resource exhausting task.<\/p>\n\n\n\n
This challenge aims to generate new ideas how social networks could be monitored automatically by automated robots. The gathered data should be analysed, taking into account the post, its authors profile and connections, its relation to other more trusted sources. Generating the ideas, consider the possibilities to use big data and reinforcement learning methods to achieve accurate and up to date fake news identification solutions for real-time social network posts.<\/p>\n","protected":false},"excerpt":{"rendered":"
This challenge aims to generate new ideas how social networks could be monitored automatically by automated robots. The gathered data should be analysed, taking into account the post, its authors profile and connections, its relation to other more trusted sources.<\/p>\n","protected":false},"featured_media":710,"template":"","meta":{"_monsterinsights_skip_tracking":false},"categories":[12,23,21],"tags":[17,19,18],"class_list":["post-638","proposed-challenges","type-proposed-challenges","status-publish","has-post-thumbnail","hentry","category-ai","category-cs","category-ict","tag-ai","tag-cybersecurity","tag-ict"],"yoast_head":"\n