Personal preferences analysis of user interaction based on social networks

Author(s):  
Cheng-Hung Tsai ◽  
Han-Wen Liu ◽  
Tsun Ku ◽  
Wu-Fan Chien
Author(s):  
Márcio J. Mantau ◽  
Marcos H. Kimura ◽  
Isabela Gasparini ◽  
Carla D. M. Berkenbrock ◽  
Avanilde Kemczinski

The issue of privacy in social networks is a hot topic today, because of the growing amount of information shared among users, who are connected to social media every moment and by different devices and displays. This chapter presents a usability evaluation of the privacy features of Facebook's social network. The authors carry out an evaluation composed by three approaches, executed in three stages: first by the analysis and inspection of system's features related to privacy, available for both systems (Web-based systems and mobile-based systems, e.g. app). The second step is a heuristic evaluation led by three experts, and finally, the third step is a questionnaire with 605 users to compare the results between specialists and real users. This chapter aims to present the problems associated with these privacy settings, and it also wants to contribute for improving the user interaction with this social network.


2021 ◽  
Vol 45 (1) ◽  
Author(s):  
V. A. Savchenko ◽  
◽  
V. M. Akhramovych ◽  
T. M. Dzyuba ◽  
S. O. Laptіev ◽  
...  

The elements of user interaction in social networks are considered: it is shown that the method of analysis of user interactions is based on assumptions when the magnitude of the influence depends on the centrality of users in the social network; the greater the consonance, the higher the nature of the influence, the interaction is a nonlinear function; it is indicated that interaction is a process that has a time interval, the linear model of protection of the information protection system from user interaction is considered; the obtained equations of protection are the equation of a harmonic oscillator with damping amplitude, the iteration of oscillations of the protection system in the pre-resonant, resonant and post-resonant zones is shown.


2020 ◽  
Author(s):  
Haiming Wu ◽  
Ruigang Wang ◽  
Lixia Jia ◽  
Likui Feng ◽  
Xu Zhou

Abstract Social network has gradually become the mainstream way for people to obtain and interact with information. The study on the law of information dissemination in social networks is of great significance to enterprise marketing, public opinion control and social recommendation. This paper puts forward a method that use multi-dimensional node influence and epidemic model to illustrate the causes and rules of information dissemination in social networks. Firstly, based on the multiple linear regression model, a measurement method of node influence is proposed from three dimensions: topology, user interaction behavior and information content. Then, taking the node influence as the cause of state transition, the information dissemination model based on the epidemic model is constructed, and the multidimensional factors affecting the information dissemination are analyzed. Meanwhile, the information dissemination trend in social networks is described.


2021 ◽  
Vol 38 (1) ◽  
pp. 1-11
Author(s):  
Hafzullah İş ◽  
Taner Tuncer

It is highly important to detect malicious account interaction in social networks with regard to political, social and economic aspects. This paper analyzed the profile structure of social media users using their data interactions. A total of 10 parameters including diameter, density, reciprocity, centrality and modularity were used to comprehensively characterize the interactions of Twitter users. Moreover, a new data set was formed by visualizing the data obtained with these parameters. User profiles were classified using Convolutional Neural Network models with deep learning. Users were divided into active, passive and malicious classes. Success rates for the algorithms used in the classification were estimated based on the hyper parameters and application platforms. The best model had a success rate of 98.67%. The methodology demonstrated that Twitter user profiles can be classified successfully through user interaction-based parameters. It is expected that this paper will contribute to published literature in terms of behavioral analysis and the determination of malicious accounts in social networks.


Author(s):  
Graham Cormode ◽  
Balachander Krishnamurthy

Web 2.0 is a buzzword introduced in 2003-04 which is commonly used to encompass various novel phenomena on the World Wide Web. Although largely a marketing term, some of the key attributes associated with Web 2.0 include the growth of social networks, bi-directional communication, various 'glue' technologies, and significant diversity in content types. We are not aware of a technical comparison between Web 1.0 and 2.0. While most of Web 2.0 runs on the same substrate as 1.0, there are some key differences. We capture those differences and their implications for technical work in this paper. Our goal is to identify the primary differences leading to the properties of interest in 2.0 to be characterized. We identify novel challenges due to the different structures of Web 2.0 sites, richer methods of user interaction, new technologies, and fundamentally different philosophy. Although a significant amount of past work can be reapplied, some critical thinking is needed for the networking community to analyze the challenges of this new and rapidly evolving environment.


2021 ◽  
Author(s):  
Vijayalakshmi Kakulapati

The explosion of affluent social networks, online communities, and jointly generated information resources has accelerated the convergence of technological and social networks producing environments that reveal both the framework of the underlying information arrangements and the collective formation of their members. In studying the consequences of these developments, we face the opportunity to analyze the POD repository at unprecedented scale levels and extract useful information from query log data. This chapter aim is to improve the performance of a POD repository from a different point of view. Firstly, we propose a novel query recommender system to help users shorten their query sessions. The idea is to find shortcuts to speed up the user interaction with the open data repository and decrease the number of queries submitted. The proposed model, based on pseudo-relevance feedback, formalizes exploiting the knowledge mined from query logs to help users rapidly satisfy their information need.


2019 ◽  
pp. 1270-1294
Author(s):  
Márcio J. Mantau ◽  
Marcos H. Kimura ◽  
Isabela Gasparini ◽  
Carla D. M. Berkenbrock ◽  
Avanilde Kemczinski

The issue of privacy in social networks is a hot topic today, because of the growing amount of information shared among users, who are connected to social media every moment and by different devices and displays. This chapter presents a usability evaluation of the privacy features of Facebook's social network. The authors carry out an evaluation composed by three approaches, executed in three stages: first by the analysis and inspection of system's features related to privacy, available for both systems (Web-based systems and mobile-based systems, e.g. app). The second step is a heuristic evaluation led by three experts, and finally, the third step is a questionnaire with 605 users to compare the results between specialists and real users. This chapter aims to present the problems associated with these privacy settings, and it also wants to contribute for improving the user interaction with this social network.


Author(s):  
Márcio J. Mantau ◽  
Marcos H. Kimura ◽  
Isabela Gasparini ◽  
Carla D. M. Berkenbrock ◽  
Avanilde Kemczinski

The issue of privacy in social networks is a hot topic today, because of the growing amount of information shared among users, who are connected to social media every moment and by different devices and displays. This chapter presents a usability evaluation of the privacy features of Facebook's social network. The authors carry out an evaluation composed by three approaches, executed in three stages: first by the analysis and inspection of system's features related to privacy, available for both systems (Web-based systems and mobile-based systems, e.g. app). The second step is a heuristic evaluation led by three experts, and finally, the third step is a questionnaire with 605 users to compare the results between specialists and real users. This chapter aims to present the problems associated with these privacy settings, and it also wants to contribute for improving the user interaction with this social network.


Sign in / Sign up

Export Citation Format

Share Document