User's Privacy in Recommendation Systems Applying Online Social Network Data, A Survey and Taxonomy

Recommender systems have become an integral part of many social networks and extract knowledge from a user's personal and sensitive data both explicitly, with the user's knowledge, and implicitly. This trend has created major privacy concerns as users are mostly unaware of what data and how much data is being used and how securely it is used. In this context, several works have been done to address privacy concerns for usage in online social network data and by recommender systems. This paper surveys the main privacy concerns, measurements and privacy-preserving techniques used in large-scale online social networks and recommender systems. It is based on historical works on security, privacy-preserving, statistical modeling, and datasets to provide an overview of the technical difficulties and problems associated with privacy preserving in online social networks.Comment: 26 pages, IET book chapter on big data recommender system

A qualitative study of stakeholders' perspectives on the social network service environment

Over two billion people are using the Internet at present, assisted by the mediating activities of software agents which deal with the diversity and complexity of information. There are, however, ethical issues due to the monitoring-and-surveillance, data mining and autonomous nature of software agents. Considering the context, this study aims to comprehend stakeholders' perspectives on the social network service environment in order to identify the main considerations for the design of software agents in social network services in the near future. Twenty-one stakeholders, belonging to three key stakeholder groups, were recruited using a purposive sampling strategy for unstandardised semi-structured e-mail interviews. The interview data were analysed using a qualitative content analysis method. It was possible to identify three main considerations for the design of software agents in social network services, which were classified into the following categories: comprehensive understanding of users' perception of privacy, user type recognition algorithms for software agent development and existing software agents enhancement

Social Navigation in a Location-Based Information System

Much of contextaware application research has dealt with the technical aspects of context capturing and how to interpret the context of a user. Little effort has been spent on the experience and usage of these systems. This thesis will present the general aspects of social awareness and present an example on how these concepts can be implemented into a location-based information system to help users navigate a potential information overload. This thesis also states that giving the users an experience of not being alone in the system increases the pleasure of using such a system. However this implies a decrease in privacy. To demonstrate these ideas I will describe a locationbased information system, GeoNotes, built by a group of researchers at SICS, the Swedish Institute of Computer Science. I will state a set of interaction requirements for how to extend the GeoNotes system with functionality for social awareness. Furthermore I will set up functional requirements for those interaction requirements to after implementation be able to conclude which interaction requirements I have been able to implement for. I will also give suggestions on how to position users in a WLAN. The deliverable from this project is a locationbased information system with functionality for social awareness. However, it was not within this project to test the system on true users. Therefore the statement that this functionality can help users to navigate a potential information overload is still just a hypothesis. To retrieve the position of a user in a W-LAN a packet is sent to all base stations in the network. In the first returning packet the mac address of contacting base station is extracted. Each base station is therefore a unique position. Triangulation was discarded due to its sensitivity to noise and weather circumstances, although a system that uses triangulation would have offered a much higher granularity

Personalisation and recommender systems in digital libraries

Widespread use of the Internet has resulted in digital libraries that are increasingly used by diverse communities of users for diverse purposes and in which sharing and collaboration have become important social elements. As such libraries become commonplace, as their contents and services become more varied, and as their patrons become more experienced with computer technology, users will expect more sophisticated services from these libraries. A simple search function, normally an integral part of any digital library, increasingly leads to user frustration as user needs become more complex and as the volume of managed information increases. Proactive digital libraries, where the library evolves from being passive and untailored, are seen as offering great potential for addressing and overcoming these issues and include techniques such as personalisation and recommender systems. In this paper, following on from the DELOS/NSF Working Group on Personalisation and Recommender Systems for Digital Libraries, which met and reported during 2003, we present some background material on the scope of personalisation and recommender systems in digital libraries. We then outline the working group’s vision for the evolution of digital libraries and the role that personalisation and recommender systems will play, and we present a series of research challenges and specific recommendations and research priorities for the field