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The purpose of this paper is to explore different tagging behaviours between Chinese and Americans by analysing the movie tags, and explore the feasibility of applying cultural differences to tag recommendations.

This paper introduced hypotheses based on several well-established psychological theories and tested them with social tags for the same movies generated by Chinese and Americans. And to prove the utility of the cultural factor consideration, this paper conducted a cross-cultural tag recommendation experiment.

The results show that compared with Americans, Chinese users tend to add more tags about movies’ background information (e.g. release year) and global contextual characteristics (e.g. genre); they also prefer to add tags about production countries and factual tags, and cultural factors can be applied for recommending more accurate tags.

Other reasons for tagging differences beyond cultural factors have not be explored. Tags for some sample movies in MovieLens might be unstable, as they had been tagged by a small scale of users; as a result, the tags’ type distribution might be influenced.

The results and conclusion of this study will be beneficial for the cross-cultural applications of social tags and mining users’ interests based on tags.

This paper provided a deeper investigation of the cross-cultural effect in people’s social tagging behaviours from cognitive perspective, and an empirical analysis has been performed to explore proper approaches of incorporating cultural differences for tag recommendation.

Based on the study of overall situation of the tagging function in the provincial public libraries and library of major colleges and universities, this paper aims to examine the difference of tagging behaviour of its users in library and social community sites. The authors also want to understand the causes of a variety of annotation behavior in social community sites and libraries.

The authors collected all system log data of tags, comments and ratings users added in Wuhan University library, and then found the tags, comments and rating of corresponding books in Douban. Then, the authors did questionnaire survey to the Wuhan University students.

The authors found that the annotation service in the library is not perfect as that in social community site. Enthusiasm of users annotating books in the library is far less high than that on the social community sites. Lack of understanding of the annotation service is the main reason why users are not concerned or do not use the tagging service. But users have the needs of the organization of personal information in the library using tags.

This paper investigated the library users’ behavior in the using library OPAC course and compared the difference of annotation behavior between library and social community site.

The purpose of this paper is to analyse the personalised and social characteristics of open knowledge management in higher education based on social tagging in the Web 2.0 environment.

Through the function of annotation in social tagging, the paper analyses its personalised characteristics of recognising the preferences of participants, and its personalised‐social characteristics of enriching content from all kinds of aspects; through the function of association of social tagging, it analyses its social characteristics of social networking, and its social‐personalised characteristics of collaborative acquisition or recommendation.

In the process of online information and open knowledge organisation and acquisition based on the annotation function of social tagging in the Web 2.0 environment, the personalised participation of individuals will lead to social results for everyone; however, in the process of online information and open knowledge creation and sharing based on the association function of social tagging, social and collaborative sharing among participants will help with personalised knowledge allocation.

In open knowledge management in higher education, the characteristics of personalisation and sociability based on social tagging will help to personalise the organisation and acquisition of knowledge, and help with social creation and sharing of knowledge.

This is an attempt to introduce proactive changes when creating and providing intellectual access in order to convince catalogers to become more social catalogers then they have ever been in the past.

Through a brief review and analysis of relevant literature a definition of social cataloging and social cataloger is given.

User contributed content to library catalogs affords informational professionals the opportunity to see directly the users’ perceptions of the usefulness and about-ness of information resources. This is a form of social cataloging especially from the perspective of the information professional seeking to organize information to support knowledge discovery and access.

The user and the cataloger exercise their voice as to what the information resources are about, which in essence is interpreting the intentions of the creator of the resources, how the resource is related to other resources, and perhaps even how the resources can be, or have been, used. Depending on the type of library and information environment, the weight of the work may or may not fall equally on both user and cataloger.

New definitions of social cataloging and social cataloguing are offered and are linked back to Jesse Shera’s idea of social epistemology.

Social library systems are Web 2.0 sites where users discover interesting books, movies, and music, etc., collect these resources to their personal libraries, and share their collections with others. The purpose of this study is to identify the information seeking modes adopted by users in this context as well as to reveal the characteristics of the users who are dominated by each mode.

An online survey was conducted to capture the background and behavior data of regular users from Douban, the most influential Chinese‐language social library system. The “friend‐of‐a‐friend” recruitment technique resulted in a total of 129 responses, 112 of which were valid and analyzed to generate both descriptive and inferential statistics.

Searching, browsing, encountering, and monitoring are the four major information seeking modes adopted by social library system users. The majority of the users tend to combine two or more modes, but each user has a dominating one that helps define him/her as a searcher, browser, encounterer, or monitor. While searching is the most widely adopted mode, browsers are the most prevalent type of information seekers. Different information seekers do not demonstrate significantly different characteristics by and large, however with some exceptions.

This study is one of the first to investigate how users look for resources in social library systems, a problem neglected by previous studies mostly focusing on how users organize and tag resources. The research findings enrich our understanding of social library systems as diverse and dynamic information seeking environments. This in turn will provide useful implications for their interface design to more effectively address the needs and expectations of special types of information seekers.

In the era of social media, users all over the world annotate books with social tags to express their preferences and interests. The purpose of this paper is to explore different tagging behaviours by analysing the book tags in different languages.

This investigation collected nearly 56,000 tags of 1,200 books from one Chinese and two English online bookmarking systems; it combined content analysis and machine-processing methods to evaluate the similarities and differences between different tagging systems from a cross-lingual perspective. Jaccard’s coefficient was adopted to evaluate the similarity level.

The results show that the similarity between mono-lingual tags of the same books is higher than that of cross-lingual tags in different systems and the similarity between tags of books written for specialties is higher than that of books written for the general public.

Those who have more in common annotate books with more similar tags. The similarity between users in tagging systems determines the similarity of the tag sets.

The results and conclusion of this study will benefit users’ cross-lingual information retrieval and cross-lingual book recommendation for online bookmarking systems.

This study may be one of the first to compare cross-lingual tags. Its methodology can be applied to tag comparison between any two languages. The insights of this study will help develop cross-lingual tagging systems and improve information retrieval.

With the continuous increase of users, resources and tags, social tagging systems gradually present the characteristics of “big data” such as large number, fast growth, complexity and unreliable quality, which greatly increases the complexity of recommendation. The contradiction between the efficiency and effectiveness of recommendation service in social tagging is increasingly becoming prominent. The purpose of this study is to incorporate topic optimization into collaborative filtering to enhance both the effectiveness and the efficiency of personalized recommendations for social tagging.

Combining the idea of optimization before service, this paper presents an approach that incorporates topic optimization into collaborative recommendations for social tagging. In the proposed approach, the recommendation process is divided into two phases of offline topic optimization and online recommendation service to achieve high-quality and efficient personalized recommendation services. In the offline phase, the tags' topic model is constructed and then used to optimize the latent preference of users and the latent affiliation of resources on topics.

Experimental evaluation shows that the proposed approach improves both precision and recall of recommendations, as well as enhances the efficiency of online recommendations compared with the three baseline approaches. The proposed topic optimization–incorporated collaborative recommendation approach can achieve the improvement of both effectiveness and efficiency for the recommendation in social tagging.

With the support of the proposed approach, personalized recommendation in social tagging with high quality and efficiency can be achieved.

Most studies pertaining to social tagging focus on one platform or platform type, thus limiting the scope of their findings. The purpose of this paper is to explore social tagging practices across four platforms in relation to cultural products associated with the book Casino Royale, by Ian Fleming.

A layered and nested case study approach was used to analyse data from four online platforms: Goodreads, Last.fm, WordPress, and public library social discovery platforms. The top-level case study focuses on the book Casino Royale, by Ian Fleming and its derivative products. The analysis of tagging practices in each of the four online platforms is nested within the top-level case study. Casino Royale was conceptualized as a cultural product (the book), its derived products (e.g. movies, theme songs), as well as a keyword in blogs. A qualitative, inductive, and context-specific approach was chosen to identify commonalities in tagging practices across platforms whilst taking into account the uniqueness of each platform.

The four platforms comprise different communities of users, each platform with its own cultural norms and tagging practices. Traditional access points in the library catalogues focused on the subject, location, and fictitious characters of the book. User-generated content across the four platforms emphasized historical events and periods related to the book, and highlighted more subjective access points, such as recommendations, tone, mood, reaction, and reading experience. Revealing shifts occur in the tags between the original book and its cultural derivatives: Goodreads and library catalogues focus almost exclusively on the book, while Last.fm and WordPress make in addition cross-references to a wider range of different cultural products, including books, movies, and music. The analyses also yield apparent similarities in certain platforms, such as recurring terms, phrasing and composite or multifaceted tags, as well as a strong presence of genre-related terms for the book and music.

The layered and nested case study approach presents a more comprehensive theoretical viewpoint and methodological framework by which to explore the study of user-generated metadata pertaining to a range of related cultural products across a variety of online platforms.

Online question-and-answer (Q&A) communities serve as important channels for knowledge diffusion. The purpose of this study is to investigate the dynamic development process of online knowledge systems and explore the final or progressive state of system development. By measuring the nonlinear characteristics of knowledge systems from the perspective of complexity science, the authors aim to enrich the perspective and method of the research on the dynamics of knowledge systems, and to deeply understand the behavior rules of knowledge systems.

The authors collected data from the programming-related Q&A site Stack Overflow for a ten-year period (2008–2017) and included 48,373 tags in the analyses. The number of tags is taken as the time series, the correlation dimension and the maximum Lyapunov index are used to examine the chaos of the system and the Volterra series multistep forecast method is used to predict the system state.

There are strange attractors in the system, the whole system is complex but bounded and its evolution is bound to approach a relatively stable range. Empirical analyses indicate that chaos exists in the process of knowledge sharing in this social labeling system, and the period of change over time is about one week.

This study contributes to revealing the evolutionary cycle of knowledge stock in online knowledge systems and further indicates how this dynamic evolution can help in the setting of platform mechanics and resource inputs.

The purpose of this study is to examine the growth patterns of tag vocabulary in collaborative tagging systems to verify the sustainability and stabilization of tag distributions. Both sustainability and stabilization are essential to the mining and categorization of information driven by tagging behaviors.

The study was based on time series data of CiteULike from November 2004 to April 2010. Power law distributions were detected to reveal statistical regularities and tagging patterns. Logistic regression analysis with time‐dependent covariates was conducted to identify the factors affecting the growth of distinct tags for articles. The significance of the effects and the time taken for a given article to reach its tagging maturity were also explored.

Time series plots and trend analysis illustrated the continuous growth of the tagging system. Exploratory analysis of power law distribution fittings indicated a sign of system stability known as scale invariance. Logistic regression results demonstrated that for a particular article, the number of users who tagged the article, the initial date when the article was tagged, and the life span of the article are statistically significant to the ratio of the distinct tag number to the total tag number for a given article. These results confirmed that the distinct tag ratio of an article gives rise to a stable pattern.

Though extensive work has been done on the patterns of tag vocabulary, it is not clear how the growth of distinctive tags behaves in relation to the total number of tag applications, considering time‐dependent covariates such as the number of users, and the longevity of an article. This paper sets to complement the literature on the existing methodology and investigate this property in detail.