Cross-tagging for personalized open social networking

Abstract

The Social Web is successfully established and poised for continued growth. Web 2.0 applications such as blogs, bookmarking, music, photo and video sharing systems are among the most popular; and all of them incorporate a social aspect, i.e., users can easily share information with other users. But due to the diversity of these applications -serving different aims -the Social Web is ironically divided. Blog users who write about music for example, could possibly benefit from other users registered in other social systems operating within the same domain, such as a social radio station. Although these sites are two different and disconnected systems, offering distinct services to the users, the fact that domains are compatible could benefit users from both systems with interesting and multi-faceted information. In this paper we propose to automatically establish social links between distinct social systems through cross-tagging, i.e., enriching a social system with the tags of other similar social system(s). Since tags are known for increasing the prediction quality of recommender systems (RS), we propose to quantitatively evaluate the extent to which users can benefit from cross-tagging by measuring the impact of different cross-tagging approaches on tag-aware RS for personalized resource recommendations. We conduct experiments in real world data sets and empirically show the effectiveness of our approaches.

Recommendation of similar users, resources and social networks in a Social Internetworking Scenario

“…This approach adopts also tag alignment techniques. In [41] the authors propose a cross-tagging approach which aims at enriching each social system by exploiting the tags used in the other ones. This activity has a twofold effect: it first allows the automatic annotation of resources which were not originally labelled and, then, enriches user profiles in such a way that user similarities can be computed in a more precise fashion.…”

“…This idea is also present in our approach because we examine the whole set of actions carried out by users in different social networks to compute similarity values. A further analogy regards the ''multi-dimensional'' structure used to represent information involved; specifically, our approach uses a hypergraph whose edges indicate the existence of suitable actions, whereas, for instance, the approach of [41] uses a tensor to represent resources, users and their interactions.…”

Linkage, aggregation, alignment and enrichment of public user profiles with Mypes

“…In [12], Szomszor et al present an approach to combine profiles generated in two different tagging platforms to obtain richer interest profiles; Stewart et al demonstrate the benefits of combining blogging data and tag assignments from Last.fm to improve the quality of music recommendations [11]. In this paper we present a solution that goes beyond linkage of tag-based user profiles, which we moreover enrich with Wordnet facets, as we consider also explicitly provided profiles coming from different social networking and social media services.…”

Escaping the Big Brother: An empirical study on factors influencing identification and information leakage on the Web

“…Examples are the suggestion of people with similar interests, the recommendation of resources [2] and the support to content annotation by tag suggestion [3]. Personal data are also used for security-related services, such as automatic filtering of unintended friends [4] and trust predictions in social networks [5].…”

“…It is a subject of interest for different communities, which often use similar techniques. It is relevant for user profiling in the community of adaptive and personalized systems [2,3], in that one of criminal identification [8] and furthermore in that one of privacy protection [6,11,12].…”