A hybrid approach for the detection and monitoring of people having personality disorders on social networks [0.03%]
一种在社交网络上检测和监控患有个性障碍人群的混合方法
Mourad Ellouze,Lamia Hadrich Belguith
Mourad Ellouze
Research in the medical field does not stop evolving. This evolution obliges doctors to be up-to-date in order to well manage every situation that may occur with their patients. However, the medical field is very sensitive and requires a gr...
Public reactions towards Covid-19 vaccination through twitter before and after second wave in India [0.03%]
印度第二波新冠疫情前后-twitter上的新冠疫苗接种公众反应
Siddhi Mishra,Abhigya Verma,Kavita Meena et al.
Siddhi Mishra et al.
Social media have a significant impact on opinion building in public. Vaccination in India started in January 2021. We have seen many opinions towards vaccination of the people, as vaccination is one of the most crucial steps toward the fig...
Samiha Fadloun,Yacine Morakeb,Erick Cuenca et al.
Samiha Fadloun et al.
Social networks are a dominant data source for sharing, participation, and exchanging information. For example, Twitter is a microblogging site that enables users to express opinions by transmitting brief messages (i.e., Tweets). Tweets can...
Novel approaches to fake news and fake account detection in OSNs: user social engagement and visual content centric model [0.03%]
面向社交网络的新型谣言和水军检测方法：以用户社会参与度及视觉内容为中心模型
Santosh Kumar Uppada,K Manasa,B Vidhathri et al.
Santosh Kumar Uppada et al.
With an increase in the number of active users on OSNs (Online Social Networks), the propagation of fake news became obvious. OSNs provide a platform for users to interact with others by expressing their opinions, resharing content into dif...
Understanding social engagements: A comparative analysis of user and text features in Twitter [0.03%]
理解社会参与行为：基于Twitter的用户特征和文本特征的比较分析
Cagri Toraman,Furkan Şahinuç,Eyup Halit Yilmaz et al.
Cagri Toraman et al.
Information is spread as individuals engage with other users in the underlying social network. Analysis of social engagements can therefore provide insights to understand the motivation behind how and why users engage with others in differe...
Ridge count thresholding to uncover coordinated networks during onset of the Covid-19 pandemic [0.03%]
基于新冠大流行初期的ridge计数阈值法揭示协调网络
Spencer Lee Kirn,Mark K Hinders
Spencer Lee Kirn
In order to combat information operations (IO) and disinformation campaigns, one must look at the behaviors of the accounts pushing specific narratives and stories through social media, not at the content itself. In this work, we present a ...
DeeProBot: a hybrid deep neural network model for social bot detection based on user profile data [0.03%]
基于用户资料数据的社交机器人检测的混合深度神经网络模型DeeProBot
Kadhim Hayawi,Sujith Mathew,Neethu Venugopal et al.
Kadhim Hayawi et al.
Use of online social networks (OSNs) undoubtedly brings the world closer. OSNs like Twitter provide a space for expressing one's opinions in a public platform. This great potential is misused by the creation of bot accounts, which spread fa...
Marco Mameli,Marina Paolanti,Christian Morbidoni et al.
Marco Mameli et al.
Social networks are increasingly used for discussing all kinds of topics, including those related to politics, serving as a virtual arena. Consequently, analysing online conversations, for example, to predict election outcomes, is becoming ...
Abeer Aldayel,Walid Magdy
Abeer Aldayel
There is a rising concern with social bots that imitate humans and manipulate opinions on social media. Current studies on assessing the overall effect of bots on social media users mainly focus on evaluating the diffusion of discussions on...
Oscar Fontanelli,Demian Hernández,Ricardo Mansilla
Oscar Fontanelli
In this work we introduce a simple mathematical model, based on master equations, to describe the time evolution of the popularity of hashtags on the Twitter social network. Specifically, we model the total number of times a certain hashtag...