Building Recommendation Service with Social Networks and Semantic Databases

Author(s):  
Sašo Karakatič ◽  
Vili Podgorelec ◽  
Marjan Heričko

In this chapter, it is shown how useful user services can be created through the integration of social networks and semantic databases. The authors developed a recommendation service in a form of a Web-based application, where a user's interests are imported from social network Facebook and linked with additional data from open semantic database Freebase. Based on a custom implementation of k-nearest neighbors algorithm, the developed method is able to find recommendations based on users’ interests enriched with semantic information. The resulting list of found recommendations is then shown to the user in some basic categories like movies, music, games, books, and others.

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 3994
Author(s):  
Yuxi Li ◽  
Fucai Zhou ◽  
Yue Ge ◽  
Zifeng Xu

Focusing on the diversified demands of location privacy in mobile social networks (MSNs), we propose a privacy-enhancing k-nearest neighbors search scheme over MSNs. First, we construct a dual-server architecture that incorporates location privacy and fine-grained access control. Under the above architecture, we design a lightweight location encryption algorithm to achieve a minimal cost to the user. We also propose a location re-encryption protocol and an encrypted location search protocol based on secure multi-party computation and homomorphic encryption mechanism, which achieve accurate and secure k-nearest friends retrieval. Moreover, to satisfy fine-grained access control requirements, we propose a dynamic friends management mechanism based on public-key broadcast encryption. It enables users to grant/revoke others’ search right without updating their friends’ keys, realizing constant-time authentication. Security analysis shows that the proposed scheme satisfies adaptive L-semantic security and revocation security under a random oracle model. In terms of performance, compared with the related works with single server architecture, the proposed scheme reduces the leakage of the location information, search pattern and the user–server communication cost. Our results show that a decentralized and end-to-end encrypted k-nearest neighbors search over MSNs is not only possible in theory, but also feasible in real-world MSNs collaboration deployment with resource-constrained mobile devices and highly iterative location update demands.


Author(s):  
Carson K.-S. Leung ◽  
Irish J. M. Medina ◽  
Syed K. Tanbeer

The emergence of Web-based communities and social networking sites has led to a vast volume of social media data, embedded in which are rich sets of meaningful knowledge about the social networks. Social media mining and social network analysis help to find a systematic method or process for examining social networks and for identifying, extracting, representing, and exploiting meaningful knowledge—such as interdependency relationships among social entities in the networks—from the social media. This chapter presents a system for analyzing the social networks to mine important groups of friends in the networks. Such a system uses a tree-based mining approach to discover important friend groups of each social entity and to discover friend groups that are important to social entities in the entire 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.


2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Katarzyna Musial ◽  
Piotr Bródka ◽  
Przemysław Kazienko ◽  
Jarosław Gaworecki

The data gathered in all kinds of web-based systems, which enable users to interact with each other, provides an opportunity to extract social networks that consist of people and relationships between them. The emerging structures are very complex due to the number and type of discovered connections. In web-based systems, the characteristic element of each interaction between users is that there is always an object that serves as a communication medium. This can be, for example, an e-mail sent from one user to another or post at the forum authored by one user and commented on by others. Based on these objects and activities that users perform towards them, different kinds of relationships can be identified and extracted. Additional challenge arises from the fact that hierarchies can exist between objects; for example, a forum consists of one or more groups of topics, and each of them contains topics that finally include posts. In this paper, we propose a new method for creation of multilayered social network based on the data about users activities towards different types of objects between which the hierarchy exists. Due to the flattening, preprocessing procedure of new layers and new relationships in the multilayered social network can be identified and analysed.


2021 ◽  
Vol 38 (5) ◽  
pp. 1413-1421
Author(s):  
Vallamchetty Sreenivasulu ◽  
Mohammed Abdul Wajeed

Spam emails based on images readily evade text-based spam email filters. More and more spammers are adopting the technology. The essence of email is necessary in order to recognize image content. Web-based social networking is a method of communication between the information owner and end users for online exchanges that use social network data in the form of images and text. Nowadays, information is passed on to users in shorter time using social networks, and the spread of fraudulent material on social networks has become a major issue. It is critical to assess and decide which features the filters require to combat spammers. Spammers also insert text into photographs, causing text filters to fail. The detection of visual garbage material has become a hotspot study on spam filters on the Internet. The suggested approach includes a supplementary detection engine that uses visuals as well as text input. This paper proposed a system for the assessment of information, the detection of information on fraud-based mails and the avoidance of distribution to end users for the purpose of enhancing data protection and preventing safety problems. The proposed model utilizes Machine Learning and Convolutional Neural Network (CNN) methods to recognize and prevent fraud information being transmitted to end users.


2020 ◽  
Author(s):  
Thomas Clavier ◽  
Benjamin Popoff ◽  
Jean Selim ◽  
Marion Beuzelin ◽  
Melanie Roussel ◽  
...  

BACKGROUND Critical care teams are on the front line of managing the COVID-19 pandemic, which is stressful for members of these teams. OBJECTIVE Our objective was to assess whether the use of social networks is associated with increased anxiety related to the COVID-19 pandemic among members of critical care teams. METHODS We distributed a web-based survey to physicians, residents, registered and auxiliary nurses, and nurse anesthetists providing critical care (anesthesiology, intensive care, or emergency medicine) in several French hospitals. The survey evaluated the respondents’ use of social networks, their sources of information on COVID-19, and their levels of anxiety and information regarding COVID-19 on analog scales from 0 to 10. RESULTS We included 641 respondents in the final analysis; 553 (86.3%) used social networks, spending a median time of 60 minutes (IQR 30-90) per day on these networks. COVID-19–related anxiety was higher in social network users than in health care workers who did not use these networks (median 6, IQR 5-8 vs median 5, IQR 3-7) in univariate (<i>P</i>=.02) and multivariate (<i>P</i>&lt;.001) analyses, with an average anxiety increase of 10% in social network users. Anxiety was higher among health care workers using social networks to obtain information on COVID-19 than among those using other sources (median 6, IQR 5-8 vs median 6, IQR 4-7; <i>P</i>=.04). Social network users considered that they were less informed about COVID-19 than those who did not use social networks (median 8, IQR 7-9 vs median 7, IQR 6-8; <i>P</i>&lt;.01). CONCLUSIONS Our results suggest that social networks contribute to increased anxiety in critical care teams. To protect their mental health, critical care professionals should consider limiting their use of these networks during the COVID-19 pandemic.


Author(s):  
Edeama O. Onwuchekwa

Social networking is a Web-based service that allows individuals to construct a public or semi-public profile within a bounded system, articulate a list of other users with whom they share a connection, and view and navigate their list of connections and those made by others within the system. No doubt, social media has great potential in taking library operations to the next level. It is in the light of this that this chapter examines the role of social media and social networking in information service provision in libraries. To achieve this objective, the chapter looks at social media as a tool in libraries, advantages of social media in libraries, social media and social networks, and practical examples on the use of social media and social network tools together with how libraries can forge ahead due to the use and application of social media and social networks to their daily operations. Conclusion and recommendations based on these highlights are provided.


2014 ◽  
Vol 94 ◽  
pp. 50-71 ◽  
Author(s):  
Lorena González-Manzano ◽  
Ana I. González-Tablas ◽  
José M. de Fuentes ◽  
Arturo Ribagorda

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.


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