Semantically Modeling Cyber Influence Campaigns (CICs): Ontology Model and Case Studies

Survey of Generative Methods for Social Media Analysis

“…The creation of social media platforms generated an immense volume and diversity of content produced and exchanged by users. According to [126], Facebook, Twitter, and Instagram boast over two billion monthly active users, and as such, their ability to directly and indirectly connect the world's population has never been easier or more far reaching. Also, according to a Pew Research study [44], 56% of US adults online use more than one social media platform.…”

Ubi-Flex-Cloud: ubiquitous flexible cloud computing: status quo and research imperatives

“…Modern societies depend on reliable secure cloud computing for a wide range of critical functions, including education through virtual learning environments [3][4][5] and health care [6][7][8], both for classical health care topics, such as heart health [9], as well as newly emerging diseases, such as Covid-19 [10][11][12][13]. Moreover, the influence that social media exert on people in conjunction with advanced cloud computing models enable sophisticated cyber influence campaigns for a wide range of purposes, ranging from public health awareness to military conflicts [14][15][16][17][18]. Also, the ongoing roll-out of fifth generation wireless systems (5G) will enable a new range of use cases that require low-latency communication and compute processing [19,20], e.g.…”

Determination of Subjects’ Significance Rate and Optimal Information Control in Social Networks

“…In the late 90s of the last century, there was a massive collapse of the socalled dot-com (.com) companies and this phenomenon, sensitive for the Internet technology industry, has contributed immensely to the revision of the basic laws of social networks, which were considered almost immutable: asymptotic laws about the value of social networks -Sarnoff's, Metcalfe's, and Reed's Laws (for instance, see Kovarik, 2015;Simeonov, 2006;Reed, 1999Reed, , 2001Farris, Pfeifer, & Johnson, 2009); information field formation laws (for instance, see Bukharin, Kovalev, & Malkov, 2009;Bukharin & Malkov, 2010;Chernets, Bazlova, & Ivanova, 2010;Gubanov, 2020;Malkov, 2016;Gubanov et al, 2010); laws of formation, dynamics and influence of opinions (Nguyen, Xiao, Xu, Wu, & Xia, 2020;Galam, 2012;Xiong & Liu, 2014;Gubanov, Novikov, & Chkhartishvili, 2009;Grabich & Rusinowska, 2010;Rusinowska & Swart, 2007; see also relatively old work Hoede & Bakker, 1982, which is important in terms of its subsequent influences); etc. As a result, there have appeared other laws and regulations, methods and approaches, and even qualitatively new concepts (for more information on these methods and concepts see fundamental monographs Jackson, 2008;Gubanov et al, 2010;Fowler & Christakis, 2011;Amati, Lomi, & Mira, 2018;Razis, Anagnostopoulos, & Zeadally, 2020;Johnson, Turnbull, Maher, & Reisslein, 2021; see also the voluminous article Gubanov et al, 2009). Due to the aforementioned revision, mathematical models of various levels have been constructed and studied (many of them only partially) to describe and understand various aspects of sustainable existence, functioning, safety and reliability, development, value, influence, danger and regulation of social networks.…”