Social Tagging Services Research Articles

Ranking on heterogeneous manifolds for tag recommendation in social tagging services

Abstract Nowadays, most social Websites allow users to annotate resources (such as Web pages and images) with keywords, i.e. tags. Collaborative tagging data reflects the semantic perception of users, thus providing valuable information for the related recommendation problems, e.g. tag recommendation, resource recommendation. In this paper, we tackle the problem of personalized tag recommendation in social tagging services by generalizing the traditional manifold ranking idea. Specifically, we model the complex relationships in tagging data as a heterogeneous graph and propose a novel ranking algorithmic framework for heterogeneous manifolds, named GRoMO (Graph-based Ranking of Multi-type interrelated Objects). In our system both the resource to be tagged (accounting for relevance) and the user׳s historical tags (accounting for personalization) are treated as query inputs. Then tags are ranked according to the output of GRoMO and the top tags are recommended to that user. We also explore adapting GRoMO for resource recommendation. For experiments we crawled a tagging dataset from the well-known tagging service, Del.icio.us. Experimental results indicate (1) the proposed method is effective and significantly outperforms baseline methods; (2) the iterative form solutions of GRoMO converge very fast and can be used when the dataset is large; (3) GRoMO can also be used for resource recommendation.

Security techniques for prevention of rank manipulation in social tagging services including robotic domains.

With smartphone distribution becoming common and robotic applications on the rise, social tagging services for various applications including robotic domains have advanced significantly. Though social tagging plays an important role when users are finding the exact information through web search, reliability and semantic relation between web contents and tags are not considered. Spams are making ill use of this aspect and put irrelevant tags deliberately on contents and induce users to advertise contents when they click items of search results. Therefore, this study proposes a detection method for tag-ranking manipulation to solve the problem of the existing methods which cannot guarantee the reliability of tagging. Similarity is measured for ranking the grade of registered tag on the contents, and weighted values of each tag are measured by means of synonym relevance, frequency, and semantic distances between tags. Lastly, experimental evaluation results are provided and its efficiency and accuracy are verified through them.

Web 2.0 applications in government web sites

PurposeThe purpose of this paper is to investigate the extent to which Web 2.0 applications are prevalent in government web sites, the ways in which Web 2.0 applications have been used in government web sites, as well as whether the presence of Web 2.0 applications correlates with the perceived quality of government web sites.Design/methodology/approachDivided equally between developing and advanced economies, a total of 200 government web sites were analysed using content analysis and multiple regression analysis.FindingsThe prevalence of seven Web 2.0 applications in descending order was: RSS, multimedia sharing services, blogs, forums, social tagging services, social networking services and wikis. More web sites in advanced countries include Web 2.0 applications than those in developing countries. The presence of Web 2.0 applications was found to have a correlation with the overall web site quality, and in particular, service quality.Research limitations/implicationsThis paper only covers government web sites in English. Emerging genres of Web 2.0 applications such as mashups and virtual worlds have not been included. Moreover the data were drawn solely from the public domain.Practical implicationsDecision makers and e‐government web developers may benchmark their own efforts in deploying Web 2.0 applications against this study. The numerous exemplars cited here serve as a springboard to generate more ideas on how Web 2.0 applications could be used and harnessed to improve the overall quality of government web sites.Originality/valueThis paper unites two research interests: Web 2.0 and web site quality. It also extends previous studies by investigating the suite of Web 2.0 applications found in government web sites around the world.

Social search

PurposeThe purpose of this paper is to introduce the notion of social search as a new concept, drawing upon the patterns of web search behaviour. It aims to: define social search; present a taxonomy of social search; and propose a user‐centred social search method.Design/methodology/approachA mixed method approach was adopted to investigate and conceptualise the notion of social search. A review of literature on social search was carried out to identify the key trends and topics. A model of online collaboration was adopted to delineate the types and categories of social search. Four use case scenarios were developed to provide a more pragmatic approach to the understanding of social search.FindingsThe developed taxonomy of social search reveals important similarities and differences between many social search systems. This analysis reveals a gap in social search approaches. A practical method was identified that allows users to directly leverage social search without special features built into search engines.Research limitations/implicationsFor feasibility reasons, Google was used as an example of a search system that can be used for carrying out social searches.Practical implicationsThe paper provides several practical implications for web searchers as well as web designers. In particular, some recommendations are provided for the design of search engines, digital libraries and browser add‐ons.Social implicationsThe study demonstrates the value and power of “collective intelligence” in web search. It shows how general web searches can be enhanced through using socially enhanced web‐based tools such as social bookmarking systems, social tagging services and social media sites.Originality/valueThis is the first study that provides a granular analysis of the notion of social search and puts forward a taxonomy of social search. The use cases developed and reported are created based on real search topics, and show the value and validity of the approach taken.