Graphs are structured data that models complex relations between real-world entities.
Heterophilic graphs, where linked nodes are prone to be with different labels or dissimilar …

Graph Neural Networks (GNNs) are commonly used and have shown promising
performance in recommendation systems. A major branch, Heterogeneous GNNs, models …

Malicious social bots achieve their malicious purposes by spreading misinformation and
inciting social public opinion, seriously endangering social security, making their detection a …

Bot accounts on microblogging platforms significantly impact information reliability and
cyberspace security. Accurately identifying these bots is essential for effective community …

Information spreads faster through social media platforms than traditional media, thus
becoming an ideal medium to spread misinformation. Meanwhile, automated accounts …

With the rise and prevalence of social bots, their negative impacts on society are gradually
recognized, prompting research attention to effective detection and countermeasures …

X bot detection aims to automatically identify malicious X bots on the X platform, playing a
crucial role in protecting information and maintaining platform stability. Recently, mixture …

Currently, due to the significant negative impact of social bots, there has been widespread
interest among researchers in automating the detection of social bots. And Graph Neural …

The paper describes the problems of analyzing and processing large volumes of
heterogeneous texts in natural language in the task of identifying bots in social networks …

У роботі розглядаються різні аспекти розробки інтелектуальної системи аналізу та
обробки великих обсягів неоднорідних текстів природною мовою для завдання …