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This paper aims to study the characteristics and evolution rules of tagging knowledge network for users with different activity levels in question-and-answer (Q&A) community represented by Zhihu.

A random sample of issue tag data generated by topics in the Zhihu network environment is selected. By defining user quality and selecting the top 20% and bottom 20% of users to focus on, i.e. top users and bot users, the authors apply time slicing for both types of data to construct label knowledge networks, use Q-Q diagrams and ARIMA models to analyze network indicators and introduce the theory and methods of network motif.

This study shows that when the power index of degree distribution is less than or equal to 3.1, the ARIMA model with rank index of label network has a higher fitting degree. With the development of the community, the correlation between tags in the tagging knowledge network is very weak.

It is not comprehensive and sufficient to classify users only according to their activity levels. And traditional statistical analysis is not applicable to large data sets. In the follow-up work, the authors will further explore the characteristics of the network at a larger scale and longer timescale and consider adding more node features, including some edge features. Then, users are statistically classified according to the attributes of nodes and edges to construct complex networks, and algorithms such as machine learning and deep learning are used to calculate large-scale data sets to deeply study the evolution of knowledge networks.

This paper uses the real data of the Zhihu community to divide users according to user activity and combines the theoretical methods of statistical testing, time series and network motifs to carry out the time series evolution of the knowledge network of the Q&A community. And these research methods provide other network problems with some new ideas. Research has found that user activity has a certain impact on the evolution of the tagging network. The tagging network followed by users with high activity level tends to be stable, and the tagging network followed by users with low activity level gradually fluctuates.

Research has found that user activity has a certain impact on the evolution of the tagging network. The tagging network followed by users with high activity level tends to be stable, and the tagging network followed by users with low activity level gradually fluctuates. For the community, understanding the formation mechanism of its network structure and key nodes in the network is conducive to improving the knowledge system of the content, finding user behavior preferences and improving user experience. Future research work will focus on identifying outbreak points from a large number of topics, predicting topical trends and conducting timely public opinion guidance and control.

In terms of data selection, the user quality is defined; the Zhihu tags are divided into two categories for time slicing; and network indicators and network motifs are compared and analyzed. In addition, statistical tests, time series analysis and network modality theory are used to analyze the tags.

This paper aims to explore the characteristics of the co-occurrence network of online tags and propose new approaches of applying social network analysis by utilising social tagging in order to organise data.

The authors collected online resources labelled “tag” from 7 November 2004 to 31 October 2011 from the CiteULike website, comprising 684 papers and their URLs, titles and data on tagging (users, times, and tags). They examined the co-occurrence network of online tags by using the analyses of social networks, including the analysis of coherence, the analysis of centricity and core to periphery categorical analysis.

Some features of the co-occurrence of online tags are as follows: the internet is subject to the “small world” phenomenon, as well as being “scale-free”. The structure of the internet reflects stable areas of core knowledge. In addition to five possible applications of social network analysis, social tagging has the greatest significance in organising online resources.

This research finds that co-occurrence of tags online is an effective way to organise and index data. Some suggestions are provided on the organisation of online resources.

The purpose of this paper is to identify the radio frequency identification (RFID) strategic value attributes (RFIDSVAs) mechanism selections preferences and also integration of RFID tags with technology coordination tools (IRTWTCTs) alternatives ranking performance decisions in supply chain management (SCM). RFID-enabled techno-economic feasibility decisions are enhancing the SC visibility in apparel supply chains (ASCs). The RFIDSVAs mechanism selections have performed significant agility to strategic competitive advantages, namely, inventory visibility, multi-tags ownership transfer within trusted third party, etc.

Fuzzy analytical hierarchy process (FAHP) and FAHP-fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) approaches have been used to evaluate the quantitative assessment of RFIDSVA mechanisms selection decision based on weight priority orders and IRTWTCTs alternatives selection in ASC networks. The comparison of FAHP and FAHP-FTOPSIS approaches to evaluate the integrated framework develop in RFIDSVAs mechanisms and IRTWTCTs alternatives selection decisions in Indian multi-tier ASC networks.

The result found that the FAHP-FTOPSIS approaches have used to prioritizing the RFIDSVA mechanism selection weights and also identify the IRTWTCTs alternatives ranking preferences order in apparel SCM. The comparison between the FAHP and FAHP-FTOPSIS approach to quantitative assessments from RFIDSVA mechanisms and IRTWTCTs alternatives selection decisions, which enable them SC agility potential across multi-tier visibility in ASC networks. ASC stakeholders can be benefited by techno-economic feasibility decisions, RFID-enabled shop floor activities, multi-tags ownerships transfer in SCs and knowledge-based cryptography tags/items separation in SCs.

The research work has considered only five RFIDSVA mechanisms and also three integration of RFIDTWTCTs alternatives in multi-tier ASC. The strategic competitive advantages are achieved by RFID-enabled break-even tags price decisions and also techno-economic feasibility decision by contractual design multi-tier SC stakeholder’s involvements.

The pilot project study explores that the quantitative assessment decision has based on RFID-enable techno-economic feasibility in ASCs. Stakeholders can be benefited by inventory control of the financial losses, reducing the inventory inaccuracies and multi-tags ownership transfer within trusted third-party traceability in ASC networks.

This study explores the RFID-enabled apparel SC process and activities visibility (natural fibre’s fibre producer, fibre dyeing producer, yarn spinning producer, knitting and finishing producer).

This article describes the third part of a three-stage study investigating the information behaviour of fans and fan communities, the first stage of which is described in the study by Price and Robinson (2017).

Using tag analysis as a method, a comparative case study was undertaken to explore three aspects of fan information behaviour: information gatekeeping; classifying and tagging and entrepreneurship and economic activity. The case studies took place on three sites used by fans–Tumblr, Archive of Our Own (AO3) and Etsy. Supplementary semi-structured interviews with site users were used to augment the findings with qualitative data.

These showed that fans used tags in a variety of ways quite apart from classification purposes. These included tags being used on Tumblr as meta-commentary and a means of dialogue between users, as well as expressors of emotion and affect towards posts. On AO3 in particular, fans had developed a practice called “tag wrangling” to mitigate the inherent “messiness” of tagging. Evidence was also found of a “hybrid market economy” on Etsy fan stores. From the study findings, a taxonomy of fan-related tags was developed.

Findings are limited to the tagging practices on only three sites used by fans during Spring 2016, and further research on other similar sites are recommended. Longitudinal studies of these sites would be beneficial in understanding how or whether tagging practices change over time. Testing of the fan-tag taxonomy developed in this paper is also recommended.

This research develops a method for using tag analysis to describe information behaviour. It also develops a fan-tag taxonomy, which may be used in future research on the tagging practices of fans, which heretofore have been a little-studied section of serious leisure information users.

The purpose of this paper is to define a methodology to analyze links between programming topics and libraries starting from GitHub data.

This paper developed an analysis over machine learning repositories on GitHub, finding communities of repositories and studying the anatomy of collaboration around a popular topic such as machine learning.

This analysis indicates the significant importance of programming languages and technologies such as Python and Jupyter Notebook. It also shows the rise of deep learning and of specific libraries such as Tensorflow from Google.

There exists no survey or analysis based on how developers influence each other for specific topics. Other researchers focused their analysis on the collaborative structure and social impact instead of topic impact. Using this methodology to analyze programming topics is important not just for machine learning but also for other topics.

The main purpose of this study is to present an overview of the state of the art of the RFID technology in terms of data storage approaches in construction cases, and to identify the factors that require different approaches to data storage (e.g. on tags or on a remote database) in RFID applications in the construction industry.

A literature survey was conducted and the contexts of 37 construction industry cases were investigated to determine the factors that affect the decision of data storage approach and the types of information groups that were stored in each case. Additionally, 79 cases were reviewed from other industries to provide insights.

The literature review showed that, many cases in the construction industry preferred storing additional data on RFID tags such as identification, technical and historical information. The factors affecting the selection of data storage approach in RFID applications were identified: application environment, cost efficiency, multiple number of parties, need for monitoring up‐to‐date progress data, collecting environmental conditions, in situ (on‐board) data storage, industry‐related specifications, and reading range requirement.

The high proportion of cases which stored data on tags demonstrate that there is a need for tags/storage media that are specially designed for the construction industry because most tags currently have either minimum or limited memories.

The analysis of the investigated cases and the factors that were identified to be affecting the data storage approach decision making can assist construction practitioners and owners in selecting an appropriate data storage approach for their projects.

The research on social media-based academic communication has made great progress with the development of the mobile Internet era, and while a large number of research results have emerged, clarifying the topology of the knowledge label network (KLN) in this field and showing the development of its knowledge labels and related concepts is one of the issues that must be faced. This study aims to discuss the aforementioned issue.

From a bibliometric perspective, 5,217 research papers in this field from CNKI from 2011 to 2021 are selected, and the title and abstract of each paper are subjected to subword processing and topic model analysis, and the extended labels are obtained by taking the merged set with the original keywords, so as to construct a conceptually expanded KLN. At the same time, appropriate time window slicing is performed to observe the temporal evolution of the network topology. Specifically, the basic network topological parameters and the complex modal structure are analyzed empirically to explore the evolution pattern and inner mechanism of the KLN in this domain. In addition, the ARIMA time series prediction model is used to further predict and compare the changing trend of network structure among different disciplines, so as to compare the differences among different disciplines.

The results show that the degree sequence distribution of the KLN is power-law distributed during the growth process, and it performs better in the mature stage of network development, and the network shows more stable scale-free characteristics. At the same time, the network has the characteristics of “short path and high clustering” throughout the time series, which is a typical small-world network. The KLN consists of a small number of hub nodes occupying the core position of the network, while a large number of label nodes are distributed at the periphery of the network and formed around these hub nodes, and its knowledge expansion pattern has a certain retrospective nature. More knowledge label nodes expand from the center to the periphery and have a gradual and stable trend. In addition, there are certain differences between different disciplines, and the research direction or topic of library and information science (LIS) is more refined and deeper than that of journalism and media and computer science. The LIS discipline has shown better development momentum in this field.

KLN is constructed by using extended labels and empirically analyzed by using network frontier conceptual motifs, which reflects the innovation of the study to a certain extent. In future research, the influence of larger-scale network motifs on the structural features and evolutionary mechanisms of KLNs will be further explored.

The purpose of this paper is to investigate the linking of a folksonomy (user vocabulary) and LCSH (controlled vocabulary) on the basis of word matching, for the potential use of LCSH in bringing order to folksonomies.

A selected sample of a folksonomy from a popular collaborative tagging system, Delicious, was word‐matched with LCSH. LCSH was transformed into a tree structure called an LCSH tree for the matching. A close examination was conducted on the characteristics of folksonomies, the overlap of folksonomies with LCSH, and the distribution of folksonomies over the LCSH tree.

The experimental results showed that the total proportion of tags being matched with LC subject headings constituted approximately two‐thirds of all tags involved, with an additional 10 percent of the remaining tags having potential matches. A number of barriers for the linking as well as two areas in need of improving the matching are identified and described. Three important tag distribution patterns over the LCSH tree were identified and supported: skewedness, multifacet, and Zipfian‐pattern.

The results of the study can be adopted for the development of innovative methods of mapping between folksonomy and LCSH, which directly contributes to effective access and retrieval of tagged web resources and to the integration of multiple information repositories based on the two vocabularies.

The linking of controlled vocabularies can be applicable to enhance information retrieval capability within collaborative tagging systems as well as across various tagging system information depositories and bibliographic databases.

This is among frontier works that examines the potential of linking a folksonomy, extracted from a collaborative tagging system, to an authority‐maintained subject heading system. It provides exploratory data to support further advanced mapping methods for linking the two vocabularies.

The purpose of this paper is to provide awareness of various copyright concerns that may arise by the usage of web 2.0 technology and some answers to possible concerns.

The paper looks at web 2.0 technology which is currently used in libraries against a backdrop of the US Copyright statute, CONTU guidelines, and copyright concerns mentioned in library literature and law reviews.

For libraries to build a community of users, they will need to make their services more interactive. Interactive services increase the chance of patrons violating copyright law. Copyright guidelines need to be developed to assist the patron in avoiding copyright infringement.

This paper looks at library services, such as RSS feeds, wikis, social networking, tagging, and patron reviews, and explores the legal ramifications to making these services more interactive.

The study aims to investigate the level of awareness and use of Web 2.0 tools by librarians in university libraries in Nigeria.

A questionnaire was used to collect data from 176 librarians in 49 university libraries in Nigeria.

It emerged that the librarians were more familiar with social networking sites, instant messaging, media sharing sites, blogs and wikis. The popularity of these Web 2.0 tools made them the most frequently used by the librarians. Web 2.0 tools like Flickr, RSS feeds, podcasts, social bookmarking, were among the least used. The study revealed that librarians use Web 2.0 tools mostly for reference services online, library news/events, training resources, and image and video sharing. Lack of facilities such as computers with internet access, lack of skills, and lack of time were indicated as some of the barriers in the use of Web 2.0 tools by librarians in university libraries in Nigeria.

These research results can be consulted by interested librarians as they plan to implement Web 2.0 applications in their libraries.

This study draws an overall picture of Web 2.0 applications in Nigerian university libraries and attempts to provide helpful information to better understand how librarians elsewhere are utilizing Web 2.0 technologies in rendering library services.