The role of network topological structure and semantic features in creating verbal aggression

IF 2.2 4区 数学 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Meghdad Abarghouei Nejad;Salman Abarghouei Nejad;Azizollah Memariani;Masoud Asadpour;Javad Hatami;Mohammad Mahdi Kashani
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Abstract

In this article, we studied the role of the topological structure of semantic networking in creating verbal aggression. It is shown that centralities such as degree, betweenness and closeness play an important role in the activation of verbal aggression in the network. We have also shown that aggressive labelled nodes with spectral clustering in different spectra are often divided into two groups, with the larger group activating more aggressive labelled nodes. In addition, the parameter of eccentric distribution from the origin is introduced to study the dispersion of aggressive nodes around the specific nodes. Hence, studying two networks with different contexts shows that the dispersion of nodes with aggressive labelling around the network's hub, as the centre of the network with political context, is much more than artistic context. In addition, different clusters of verbal aggression in the political and artistic context have the same pattern of frequency. In addition, we investigated semantic features in creating verbal aggression, showing that non-aggressive words are prone to create verbal aggression as much as aggressive words.
网络拓扑结构和语义特征在言语攻击产生中的作用
在本文中,我们研究了语义网络拓扑结构在言语攻击产生中的作用。研究表明,程度、中间性和亲密性等中心性在网络言语攻击的激活中起着重要作用。我们还表明,在不同光谱中具有光谱聚类的主动标记节点通常分为两组,较大的组激活更积极的标记节点。此外,引入原点偏心分布参数,研究侵彻节点在特定节点周围的分散情况。因此,研究两个具有不同背景的网络表明,作为具有政治背景的网络中心,具有侵略性标签的节点在网络中心周围的分散程度远远超过艺术背景。此外,在政治语境和艺术语境中,不同类型的言语攻击具有相同的频率模式。此外,我们还研究了产生言语攻击的语义特征,发现非攻击性词汇和攻击性词汇同样容易产生言语攻击。
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来源期刊
Journal of complex networks
Journal of complex networks MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-
CiteScore
4.20
自引率
9.50%
发文量
40
期刊介绍: Journal of Complex Networks publishes original articles and reviews with a significant contribution to the analysis and understanding of complex networks and its applications in diverse fields. Complex networks are loosely defined as networks with nontrivial topology and dynamics, which appear as the skeletons of complex systems in the real-world. The journal covers everything from the basic mathematical, physical and computational principles needed for studying complex networks to their applications leading to predictive models in molecular, biological, ecological, informational, engineering, social, technological and other systems. It includes, but is not limited to, the following topics: - Mathematical and numerical analysis of networks - Network theory and computer sciences - Structural analysis of networks - Dynamics on networks - Physical models on networks - Networks and epidemiology - Social, socio-economic and political networks - Ecological networks - Technological and infrastructural networks - Brain and tissue networks - Biological and molecular networks - Spatial networks - Techno-social networks i.e. online social networks, social networking sites, social media - Other applications of networks - Evolving networks - Multilayer networks - Game theory on networks - Biomedicine related networks - Animal social networks - Climate networks - Cognitive, language and informational network
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