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Authors:Qingzhu Ye Abstract: The purpose of this paper is to construct a digital collection and database of traditional clothing that is convenient for the digital dissemination and application of traditional clothing and provide resources for research on clothing fashion, traditional clothing techniques, clothing culture, history and clothing teaching. A real object analysis method was used in this paper, based on 15 core elements of the internationally common DC metadata standard, and with consideration to the characteristics of clothing products and clothing industry application specifications, the core elements of DC are expanded to facilitate the detailed record of the characteristic information of clothing, especially the implicit clothing culture. A code symbol compilation method was developed to give each piece of clothing a unique number, facilitating identification, classification and recording. At last, a metadata construction scheme for traditional clothing was developed. A traditional embroidered children's hat and Mamianqunt serve as examples to demonstrate the metadata elements. The clothing meta-database provides a main body of traditional clothing while also paying attention to the collection of cultural elements. It is composed of five layers of classified data, source data, characteristic data, connotation data and management data, as well as 28 data elements, providing ease of sharing and interoperation. This paper expands the subset of fashion metadata by describing traditional clothing metadata, especially the excavation of clothing cultural elements, and developing code compilation methods so that each clothing product can obtain a unique identification number, thereby building a traditional clothing metadata construction scheme consisting of five data layers and containing 28 data elements. This scheme records the information about each layer of traditional clothing in detail and provides shared data for discipline research and industry applications. Citation: The Electronic Library PubDate: 2023-05-25 DOI: 10.1108/EL-01-2023-0004 Issue No:Vol. ahead-of-print, No. ahead-of-print (2023)
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Authors:Irfan Ali, Nosheen Fatima Warraich Abstract: Although, smartphones have facilitated users to keep their personal information, nonetheless, less has been investigated about factors affecting personal information management (PIM) practices. Therefore, this study aims to investigate how personal innovativeness, perceived ease of use (PEOU) and mobile self-efficacy affect PIM (e.g. finding/re-finding, keeping, organizing and maintaining) practices. Quantitative research design was used in this study. The authors collected data from 222 students of information management from public sector universities using a questionnaire. PLS modeling technique was used to analyze data. The authors noted that personal innovativeness significantly impacts finding/refinding information, whereas it insignificantly affects keeping, organizing and maintaining information practices. In addition, smartphone PEOU significantly influences information finding and refinding, information keeping and organizing information, whereas insignificantly influences information maintaining. Moreover, mobile self-efficacy was noted to be significantly associated with finding and refinding information, information keeping, information organizing and information maintaining. This research is an important contribution to the body of existing literature, as it proposed an integrated model based on constructs extracted from Technology Acceptance Model (TAM), Social Cognitive Theory, personal innovativeness and PIM. This study also has practical significance because the findings of this study would be helpful for smartphone application developers and LIS school directors to design programs for information literacy. Citation: The Electronic Library PubDate: 2023-05-23 DOI: 10.1108/EL-12-2022-0262 Issue No:Vol. ahead-of-print, No. ahead-of-print (2023)
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Authors:Jie Meng Abstract: This paper aims to quantify the quality of peer reviews, evaluate them from different perspectives and develop a model to predict the review quality. In addition, this paper investigates effective features to distinguish the reviews' quality. First, a fine-grained data set including peer review data, citations and review conformity scores was constructed. Second, metrics were proposed to evaluate the quality of peer reviews from three aspects. Third, five categories of features were proposed in terms of reviews, submissions and responses using natural language processing (NLP) techniques. Finally, different machine learning models were applied to predict the review quality, and feature analysis was performed to understand effective features. The analysis results revealed that reviewers become more conservative and the review quality becomes worse over time in terms of these indicators. Among the three models, random forest model achieves the best performance on all three tasks. Sentiment polarity, review length, response length and readability are important factors that distinguish peer reviews’ quality, which can help meta-reviewers value more worthy reviews when making final decisions. This study provides a new perspective for assessing review quality. Another originality of the research lies in the proposal of a novelty task that predict review quality. To address this task, a novel model was proposed which incorporated various of feature sets, thereby deepening the understanding of peer reviews. Citation: The Electronic Library PubDate: 2023-05-19 DOI: 10.1108/EL-06-2022-0139 Issue No:Vol. ahead-of-print, No. ahead-of-print (2023)
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Authors:Saira Hanif Soroya, Liqaa Habeb Al-Obaydi, Mohsin Abdur Rehman Abstract: In the digital transformation race, the older generation, called digital immigrants (generation X), encounter various obstacles. This study aims to investigate the e-reading adoption and cross-cultural differences among generation X. This study collected survey-based data from generation X e-readers in Iraq and Pakistan (Pakistan, N = 235; Iraq, N = 251). Structural equation modeling and multigroup analysis (MGA) were used to arrive at a statistical decision regarding the hypotheses and the study’s primary objectives. Three hypotheses (H2, H3 and H8) were supported by both data sets. However, there is positive variance based on MGA for two hypotheses (H1 and H3) where the Pakistani sample’s path coefficients are greater than the Iraqi sample’s path coefficients. In contrast, there is negative variance based on MGA for two hypotheses (H7 and H9) where the Iraqi sample’s path coefficients are greater than the Pakistani sample’s path coefficients. Finally, these distinctions are examined, along with a few potential research topics Although there is a plethora of literature on digital immigrants and technology adoption in general, and specifically on e-reading uptake. Research on e-reading adoption in a global learning context is still lacking. Therefore, this study examines the e-reading behavior of digital immigrants from two developing countries (Iraq and Pakistan) and identifies significant cross-cultural differences in e-reading adoption. Citation: The Electronic Library PubDate: 2023-05-03 DOI: 10.1108/EL-09-2022-0217 Issue No:Vol. ahead-of-print, No. ahead-of-print (2023)
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Authors:Jiaxin Ye, Huixiang Xiong, Jinpeng Guo, Xuan Meng Abstract: The purpose of this study is to investigate how book group recommendations can be used as a meaningful way to suggest suitable books to users, given the increasing number of individuals engaging in sharing and discussing books on the web. The authors propose reviews fine-grained classification (CFGC) and its related models such as CFGC1 for book group recommendation. These models can categorize reviews successively by function and role. Constructing the BERT-BiLSTM model to classify the reviews by function. The frequency characteristics of the reviews are mined by word frequency analysis, and the relationship between reviews and total book score is mined by correlation analysis. Then, the reviews are classified into three roles: celebrity, general and passerby. Finally, the authors can form user groups, mine group features and combine group features with book fine-grained ratings to make book group recommendations. Overall, the best recommendations are made by Synopsis comments, with the accuracy, recall, F-value and Hellinger distance of 52.9%, 60.0%, 56.3% and 0.163, respectively. The F1 index of the recommendations based on the author and the writing comments is improved by 2.5% and 0.4%, respectively, compared to the Synopsis comments. Previous studies on book recommendation often recommend relevant books for users by mining the similarity between books, so the set of book recommendations recommended to users, especially to groups, always focuses on the few types. The proposed method can effectively ensure the diversity of recommendations by mining users’ tendency to different review attributes of books and recommending books for the groups. In addition, this study also investigates which types of reviews should be used to make book recommendations when targeting groups with specific tendencies. Citation: The Electronic Library PubDate: 2023-05-01 DOI: 10.1108/EL-11-2022-0252 Issue No:Vol. ahead-of-print, No. ahead-of-print (2023)
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Authors:Peilin Tian, Le Wang Abstract: This study aims to reveal the topic structure and evolutionary trends of health informatics research in library and information science. Using publications in Web of Science core collection, this study combines informetrics and content analysis to reveal the topic structure and evolutionary trends of health informatics research in library and information science. The analyses are conducted by Pajek, VOSviewer and Gephi. The health informatics research in library and information science can be divided into five subcommunities: health information needs and seeking behavior, application of bibliometrics in medicine, health information literacy, health information in social media and electronic health records. Research on health information literacy and health information in social media is the core of research. Most topics had a clear and continuous evolutionary venation. In the future, health information literacy and health information in social media will tend to be the mainstream. There is room for systematic development of research on health information needs and seeking behavior. To the best of the authors’ knowledge, this is the first study to analyze the topic structure and evolutionary trends of health informatics research based on the perspective of library and information science. This study helps identify the concerns and contributions of library and information science to health informatics research and provides compelling evidence for researchers to understand the current state of research. Citation: The Electronic Library PubDate: 2023-04-27 DOI: 10.1108/EL-01-2023-0010 Issue No:Vol. ahead-of-print, No. ahead-of-print (2023)
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Authors:Tae Hee Lee, Mina Jung, Youngseek Kim Abstract: This study aims to investigate the factors influencing the data sharing habits of psychologists with respect to academic reciprocity. A research model was developed based on Ostrom’s (2003) theory of collective action to map psychologists’ underlying motivations for data sharing. The model was validated by data from a survey of 427 psychologists, primarily from the psychological sciences and related disciplines. This study found that data sharing among psychologists is driven primarily by their perceptions of community benefits, academic reciprocity and the norms of data sharing. This study also found that academic reciprocity is significantly influenced by psychologists’ perceptions of community benefits, academic reputation and the norms of data sharing. Both academic reputation and academic reciprocity are affected by psychologists’ prior experiences with data reuse. Additionally, psychologists’ perceptions of community benefits and the norms of data sharing are significantly affected by the perception of their academic reputation. This study suggests that Ostrom’s (2003) theory of collective action can provide a new theoretical lens in understanding psychologists’ data sharing behaviours. This study suggests several practical implications for the design and promotion of data sharing in the research community of psychology. To the best of the authors’ knowledge, this is one of the initial studies that applied the theory of collective action to the mechanisms of reputation, community benefits, norms and reciprocity in psychologists’ data sharing behaviour. This research demonstrates that perceived community benefits, academic reputation and the norms of data sharing can all encourage academic reciprocity, and psychologists’ perceptions of community benefits, academic reciprocity and data sharing norms all facilitate their data sharing intentions. Citation: The Electronic Library PubDate: 2023-04-19 DOI: 10.1108/EL-10-2022-0232 Issue No:Vol. ahead-of-print, No. ahead-of-print (2023)
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Authors:Behzad Foroughi, Mohammad Iranmanesh, Mahaletchimi Kuppusamy, Yuvaraj Ganesan, Morteza Ghobakhloo, Madugoda Gunaratnege Senali Abstract: Gamification applications (apps) are gaining great attention in many contexts and have grown increasingly. Despite their significant role in many settings, prior research mainly focused on initial adoption, and there are limited studies on the post-adoption stage. This study aims to explore the factors influencing individuals’ continuance intention to use gamified task manager apps, drawing on the technology continuance theory (TCT) by integrating enjoyment, habit and social influence. Data were obtained from 318 Malaysian who had prior experience with task management gamified apps and analysed with the partial least squares approach. According to the results, confirmation, perceived usefulness (PU) and enjoyment positively influence satisfaction. PU, enjoyment, satisfaction and social influence affect attitude, while the result failed to confirm the association between perceived ease of use and attitude. Furthermore, PU, attitude and habit are strong determinants of users’ continuance intention. Moreover, continuance intention was not predicted by users’ satisfaction and social influence. The findings provide directions for developers and marketers of gamified task manager apps. Besides the technological and functional benefits of applications, they should also consider social, hedonic and individual factors in the designing and marketing stages. This study extends the literature by assessing the determinants of continuous intention to use gamified task manager apps; and extending the TCT in the context of gamification by incorporating three contextual factors, namely, perceived enjoyment, social influence and habit. Citation: The Electronic Library PubDate: 2023-04-11 DOI: 10.1108/EL-05-2022-0108 Issue No:Vol. ahead-of-print, No. ahead-of-print (2023)
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Authors:Chia-Ling Chang, Yen-Liang Chen, Jia-Shin Li Abstract: The purpose of this paper is to provide a cross-platform recommendation system that recommends the most suitable public Instagram accounts to Facebook users. We collect data from both Facebook and Instagram and then propose a similarity matching mechanism for recommending the most appropriate Instagram accounts to Facebook users. By removing the data disparity between the two heterogeneous platforms and integrating them, the system is able to make more accurate recommendations. The results show that the method proposed in this paper can recommend suitable public Instagram accounts to Facebook users with very high accuracy. To the best of the authors’ knowledge, this is the first study to propose a recommender system to recommend Instagram public accounts to Facebook users. Second, our proposed method can integrate heterogeneous data from two different platforms to generate collaborative recommendations. Furthermore, our cross-platform system reveals an innovative concept of how multiple platforms can promote their respective platforms in a unified, cooperative and collaborative manner. Citation: The Electronic Library PubDate: 2023-03-31 DOI: 10.1108/EL-09-2022-0210 Issue No:Vol. ahead-of-print, No. ahead-of-print (2023)
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Authors:Xin Feng, Xu Wang, Yufei Xue, Haochuan Yu Abstract: In the era of mobile internet, the social Q&A community has built a large-scale and complex knowledge label network through its internal knowledge units, and the scale and structure of the network have changed over time. By analysing the structural characteristics and evolution rules of knowledge label networks, the main purpose of this study is to understand the internal mechanisms of the replacement of old and new knowledge and the expansion of knowledge element boundaries, so as to explore the realization path of knowledge management in the new era from the perspective of complex networks. This paper uses distributed crawlers to capture 419,349 samples from the Zhihu platform. Each sample contains 33 characteristic dimensions, and the natural year is used as the sliding window to divide the whole. In this study, the global knowledge label network and 11 local knowledge label networks are first constructed. Then, the degree distribution analysis and central node exploration of the knowledge label network are carried out using the complex network method. Finally, the average shortest path and average clustering coefficient of the network are analysed by the time series method, and the ARIMA model is used to predict the evolution of the correlation coefficient. The research results show that the dissimilation degree of the degree distribution of the knowledge label network has gradually decreased from 2011 to 2021, and the attention of users in the knowledge community has shown a trend of distraction and diversification over time. With the expansion of the scale of the knowledge label network and the transformation to an information network, the network sparsity is becoming more and more obvious, and the knowledge granularity of the Q&A community is being refined and diversified. The prediction of the correlation coefficient of the knowledge label network by the ARIMA model shows that the connection between the labels is lacking diversity and the opinion strengthening phenomenon tends to strengthen, which is more likely to form the “echo chamber effect”, resulting in mutual isolation and even opposition between different circles. The Q&A community is about to enter a mature stage, and the corresponding status of each label has been finalized. The future development trend of label networks will be reflected in the substitution between labels, and the specific structure will not change significantly. The Q&A community model is the trend in Web 2.0 community development. This study proves the effectiveness of complex networks and time series prediction methods in knowledge label network mining in the Q&A community. Citation: The Electronic Library PubDate: 2023-03-07 DOI: 10.1108/EL-10-2022-0241 Issue No:Vol. ahead-of-print, No. ahead-of-print (2023)
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Authors:Shu-Hsien Liao, Retno Widowati, Wei-Can Lin Abstract: As of December 2021, WeChat had more than 1.2 billion active users worldwide, making it the most active online social media in mainland China. The term social commerce is used to describe new online sales through a mix of social networks and/or peer-to-peer communication or marketing strategies in terms of allowing consumers to satisfy their shopping behaviour through online social media. Thus, given the numerous active users, the development of online social media and social commerce on WeChat is a critical issue of internet research. This empirical study takes WeChat as the online social media research object. Questionnaires for WeChat users in China were designed and distributed. All items are designed as nominal and ordinal scales (not Likert scale). The obtained data was put into a relational database (N = 2,342), and different meaningful patterns and rules were examined through data mining analytics, including clustering analysis and association rules, to explore the role of WeChat in the development of online social media and social commerce. Practical implications are presented according to the research findings of meaningful patterns and rules. In addition, alternatives to WeChat in terms of further development are also proposed according to the investigation findings of WeChat users’ behaviour and preferences in China. This study concludes that online social media, such as WeChat, will be able to transcend the current development pattern of most online social media and make good use of investigating users’ behaviour and preferences, not only to stimulate the interaction of users in the social network, but also to create social commerce value in social sciences. Citation: The Electronic Library PubDate: 2023-02-16 DOI: 10.1108/EL-10-2022-0229 Issue No:Vol. ahead-of-print, No. ahead-of-print (2023)
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Authors:Xin Chen, Yingxi Liu Abstract: This study aims to explore the switching behaviour of short video (SV) users and its influencing factors and promote the sustainable development of SV platforms (SVPs) and the marketing strategy formulation of library and information institutions. Using the qualitative research method of semi-structured interviews and grounded theory, this study conducts an exploratory study on the user switching phenomenon of an SVP. The authors encoded the interview text at three levels, extracted the factors influencing user switching behaviour on an SVP and constructed the corresponding theoretical model. This study identifies the following major internal and external factors influencing user switching behaviour of SVP: platform quality, social environment, individual characteristics and use needs. It also elaborates on the impact of these internal and external factors on user switching behaviour. This study explored the factors influencing SV user switching behaviour and constructed corresponding theoretical models, enriching research in information technology and social media switching. In practice, this study helped the existing SVPs and library and information institutions establish a corresponding early warning mechanism to prevent the loss of existing users and attract new users. Citation: The Electronic Library PubDate: 2023-02-08 DOI: 10.1108/EL-09-2022-0207 Issue No:Vol. ahead-of-print, No. ahead-of-print (2023)
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