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The Electronic Library
Journal Prestige (SJR): 0.44
Citation Impact (citeScore): 1
Number of Followers: 1294  
 
Hybrid Journal Hybrid journal   * Containing 2 Open Access Open Access article(s) in this issue *
ISSN (Print) 0264-0473 - ISSN (Online) 1758-616X
Published by Emerald Homepage  [362 journals]
  • A study of non-users of digital libraries: the case of the Capes digital
           library in Brazil

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      Authors: Wesley Rodrigo Fernandes, Beatriz Valadares Cendón
      Abstract: The purpose of this paper is to understand the reasons that hinder the use of digital libraries. This study analyzed data obtained through a web survey sent to 14,763 faculty members in Brazilian universities. Of the 6,689 respondents, 1,075 (16.1%) reported not using the Capes digital library and 1,017 answered the questionnaire for non-users. Results showed that the main reasons for non-use are lack of knowledge of the existence of the Capes digital library, use of other resources, preference for printed journals and difficulty of access. Eight factors of non-use were elicited: insufficient dissemination, inadequacies in contents, in infrastructure, in access policy, in training and in the interface, personal constraints and personal attitude. The reasons and factors for non-use were categorized as intrinsic and extrinsic to the digital library. Intrinsic reasons relate to characteristics of the Capes digital library. Extrinsic factors are influenced by user characteristics. The chi-square test demonstrated that the variables: area of knowledge, age, hours dedicated to research and computer skills influence non-use. This study has contributed to research about non-users of digital libraries, differing from previous research by surveying a large-scale population and by investigating in a single work the reasons for non-use, other electronic sources used by non-users, advantages of using the digital library and intention of non-users to become users if barriers were removed. Qualitative data complemented the quantitative data collected which allowed a more complete picture of the respondent’s positions.
      Citation: The Electronic Library
      PubDate: 2021-07-01
      DOI: 10.1108/EL-10-2020-0277
      Issue No: Vol. ahead-of-print, No. ahead-of-print (2021)
       
  • Trust mechanisms underlying the self-efficacy-rumour use relationship

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      Authors: Ping Wang, Yixia Hu, Qiao Li, Hanqin Yang
      Abstract: Journalism students, a special user group with the dual perspective of both social media general users and online journalists, and their trust in rumours is a valued but understudied topic in relation to preparing rational information users and professionals for rumour control. To reveal these trust mechanisms, this paper aims to identify salient psychological and behavioural factors related to journalism students’ different levels of trust. Using structural equation modelling to analyse the survey data of 234 journalism students, this paper tested a theoretical model that considers self-efficacy and the expressive and consumptive use of social media rumours as the antecedents and consequences of trust belief and trust action, respectively. Self-efficacy has a positive effect on trust belief but a negative effect on trust action. Trust belief positively affects expressive use of rumours, whereas trust action negatively affects consumptive use. This study contributes to the cultivation of future online news gatekeepers. This paper distinguishes journalism students’ trust mechanisms from those of general users and online journalists. The integration of dual process theories provides insights into trust-building processes related to rumours and advances the understanding of the anchoring and adjustment effects of self-efficacy on trust.
      Citation: The Electronic Library
      PubDate: 2021-06-19
      DOI: 10.1108/EL-12-2020-0332
      Issue No: Vol. ahead-of-print, No. ahead-of-print (2021)
       
  • Mobile vs desktop user search behaviours of the 1300K site, a Korean
           shopping search engine

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      Authors: Soyeon Park, Kihun Cho
      Abstract: This study aims to investigate and compare mobile and desktop user search behaviours of the 1300K site, a Korean shopping search engine, by using transaction log analysis. Transaction logs of 1300K site were collected over a three months’ period, from 1 January to 31 March 2018. The data set of this study consists of 1,149,690 desktop queries, 2,346,938 mobile queries, 2,481,747 desktop browsing activities and 2,550,309 mobile browsing activities. This study quantitatively analyses transaction log of 1300K site. The results of this study show that mobile usage is higher than desktop usage: there are more mobile sessions than desktop sessions and the number of mobile queries is more than double of desktop queries. Overall, mobile query search behaviours are more simple, targeted and focused than desktop query search behaviours. Also, mobile browsing behaviours are more simple and passive than desktop browsing behaviours. However, mobile click behaviours are more active than desktop click behaviours. To the best of the authors’ knowledge, this study appears to be the first of its type in Korea that compared search behaviours of a large number of users on desktop computers and mobile phones. To identify various characteristics of user search behaviours, this study analyses users’ directory browsing behaviour and click behaviour as well as query search behaviour. The results of this study can be implemented to address the effective improvement and development of search services and interfaces for different devices.
      Citation: The Electronic Library
      PubDate: 2021-06-15
      DOI: 10.1108/EL-09-2020-0261
      Issue No: Vol. ahead-of-print, No. ahead-of-print (2021)
       
  • A comparative analysis on digital libraries and academic search engines
           from the dual-route perspective

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      Authors: Fenfang Cao, Jinchao Zhang, Xianjin Zha, Kunfeng Liu, Haijuan Yang
      Abstract: Digital libraries and academic search engines have developed as two important online scholarly information sources with different features. The purpose of this study is to compare digital libraries and academic search engines from the perspective of the dual-route model. Research hypotheses were developed. Potential participants were recruited to answer an online survey distributing at Chinese social media out of which 251 responses were deemed to be valid and used for data analysis. The paired samples t-test was used to compare the means. Both information quality (central route) and source credibility (peripheral route) of digital libraries are significantly higher than those of academic search engines, while there is no significant difference between digital libraries and academic search engines in terms of affinity (peripheral route). In the digital information society, the important status of digital libraries as conventional information sources should be spread by necessary measures. Academic search engines can act as complementary online information sources for seeking academic information rather than the substitute for digital libraries. Practitioners of digital libraries should value the complementary role of academic search engines and encourage users to use academic search engines while emphasizing the importance of digital libraries as conventional information sources. According to the dual-route model, this study compares digital libraries and academic search engines in terms of information quality, source credibility and affinity, which the authors believe presents a new lens for digital libraries research and practice alike.
      Citation: The Electronic Library
      PubDate: 2021-06-10
      DOI: 10.1108/EL-09-2020-0265
      Issue No: Vol. ahead-of-print, No. ahead-of-print (2021)
       
  • Evaluation of open health data portals for COVID-19 from the perspective
           of the user experience

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      Authors: Dan Wu, Le Ma, Hui Zhang
      Abstract: The purpose of this paper is to construct an indicator framework for evaluating open health data portals from the perspective of user experience (UX) to reduce users’ learning costs, save their time and energy and strengthen the emotional connection with users, thereby encouraging them to actively use open health data. This study uses card sorting, Delphi and analytic hierarchy process to determine the weights of indicators for evaluating open health data portals. Then, this study uses a coding method to score, evaluate and compare the selection of more than 120 open health data portals supported by organizations in more than 100 countries or regions that are in the World's top confirmed cases of COVID-19 as released by the World Health Organization. At present, open health data portals have shortcomings with regard to UX. Different types of open health data portals vary significantly in the dimensions of technical experience and functional experience, but the differences in the dimensions of aesthetic experience, emotional experience and content experience are not significant. The constructed open health data portal evaluation indicator framework introduces users' actual application needs and proposes optimization suggestions for the portal to meet the needs of users to quickly obtain, reliable and accurate health data.
      Citation: The Electronic Library
      PubDate: 2021-06-10
      DOI: 10.1108/EL-01-2021-0011
      Issue No: Vol. ahead-of-print, No. ahead-of-print (2021)
       
  • Applications of Semantic Web in integrating open data and bibliographic
           records: a development example of an infomediary of Taiwanese indigenous
           people

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      Authors: Han-Yu Sung, Yu-Liang Chi
      Abstract: This study aims to develop a Web-based application system called Infomediary of Taiwanese Indigenous Peoples (ITIP) that can help individuals comprehend the society and culture of indigenous people. The ITIP is based on the use of Semantic Web technologies to integrate a number of data sources, particularly including the bibliographic records of a museum. Moreover, an ontology model was developed to help users search cultural collections by topic concepts. Two issues were identified that needed to be addressed: the integration of heterogeneous data sources and semantic-based information retrieval. Two corresponding methods were proposed: SPARQL federated queries were designed for data integration across the Web and ontology-driven queries were designed to semantically search by knowledge inference. Furthermore, to help users perform searches easily, three searching interfaces, namely, ethnicity, region and topic, were developed to take full advantage of the content available on the Web. Most open government data provides structured but non-resource description framework data, Semantic Web consumers, therefore, require additional data conversion before the data can be used. On the other hand, although the library, archive and museum (LAM) community has produced some emerging linked data, very few data sets are released to the general public as open data. The Semantic Web’s vision of “web of data” remains challenging. This study developed data integration from various institutions, including those of the LAM community. The development was conducted based on the mode of non-institution members (i.e. institutional outsiders). The challenges encountered included uncertain data quality and the absence of institutional participation.
      Citation: The Electronic Library
      PubDate: 2021-06-10
      DOI: 10.1108/EL-09-2020-0258
      Issue No: Vol. ahead-of-print, No. ahead-of-print (2021)
       
  • The effect of multilingual suggested tags on cross-language information
           tagging behaviour

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      Authors: Xiaoyue Ma, Siya Zhang, Pengwei Zhao
      Abstract: Suggested tag was considered as one of the critical factors affecting a user’s tagging behaviour. However, compared to the findings on the suggested tags for the monolingual environment, it still lacks focused studies on the tag suggestions for cross-language information. Therefore, this paper aims to concern with annotation behaviour and psychological cognition in the cross-language environment when suggested tags are provided. A cross-language tagging experiment was conducted to explore the impact of suggested tags on the tagging results and process. The descriptive statistics of tags, the sources and semantic relations of tags, as well as the user’s psychological cognition were all measured in the test. The experimental results demonstrated that the multilingual suggested tags could bring some costs to a user’s tagging perception. Furthermore, the language factor of suggested tags led to different paths of tagging imitation (reflected by longer semantic mapping and imitation at the visual level) and different cognitive processes (topic extraction and inference process). To the best of the authors’ knowledge, this study is one of the first to emphasize the effect of suggested tags during multilingual tagging. The findings will enrich the theories of user-information interaction in the cross-language environment and, in turn, provide practical implications for tag-based information system design.
      Citation: The Electronic Library
      PubDate: 2021-06-08
      DOI: 10.1108/EL-07-2020-0177
      Issue No: Vol. ahead-of-print, No. ahead-of-print (2021)
       
  • Using latent features for building an interpretable recommendation system

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      Authors: Ziming Zeng, Yu Shi, Lavinia Florentina Pieptea, Junhua Ding
      Abstract: Aspects extracted from the user’s historical records are widely used to define user’s fine-grained preferences for building interpretable recommendation systems. As the aspects were extracted from the historical records, the aspects that represent user’s negative preferences cannot be identified because of their absence from the records. However, these latent aspects are also as important as those aspects representing user’s positive preferences for building a recommendation system. This paper aims to identify the user’s positive preferences and negative preferences for building an interpretable recommendation. First, high-frequency tags are selected as aspects to describe user preferences in aspect-level. Second, user positive and negative preferences are calculated according to the positive and negative preference model, and the interaction between similar aspects is adopted to address the aspect sparsity problem. Finally, an experiment is designed to evaluate the effectiveness of the model. The code and the experiment data link is: https://github.com/shiyu108/Recommendation-system Experimental results show the proposed approach outperformed the state-of-the-art methods in widely used public data sets. These latent aspects are also as important as those aspects representing the user’s positive preferences for building a recommendation system. This paper provides a new approach that identifies and uses not only users’ positive preferences but also negative preferences, which can capture user preference precisely. Besides, the proposed model provides good interpretability.
      Citation: The Electronic Library
      PubDate: 2021-05-17
      DOI: 10.1108/EL-06-2020-0154
      Issue No: Vol. ahead-of-print, No. ahead-of-print (2021)
       
  • A ten-year literature review of content-based image retrieval (CBIR)
           studies in the tourism industry

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      Authors: Chanattra Ammatmanee, Lu Gan
      Abstract: Due to the worldwide growth of digital image sharing and the maturity of the tourism industry, the vast and growing collections of digital images have become a challenge for those who use and/or manage these image data across tourism settings. To overcome the image indexing task with less labour cost and improve the image retrieval task with less human errors, the content-based image retrieval (CBIR) technique has been investigated for the tourism domain particularly. This paper aims to review the relevant literature in the field to understand these previous works and identify research gaps for future directions. A systematic and comprehensive review of CBIR studies in tourism from the year 2010 to 2019, focussing on journal articles and conference proceedings in reputable online databases, is conducted by taking a comparative approach to critically analyse and address the trends of each fundamental element in these research experiments. Based on the review of the literature, the trends of CBIR studies in tourism is to improve image representation and retrieval by advancing existing feature extraction techniques, contributing novel techniques in the feature extraction process through fine-tuning fusion features and improving image query of CBIR systems. Co-authorship, tourist attraction sector and fusion image features have been in focus. Nonetheless, the number of studies in other tourism sectors and available image databases could be further explored. The fact that no existing academic review of CBIR studies in tourism makes this paper a novel contribution.
      Citation: The Electronic Library
      PubDate: 2021-05-13
      DOI: 10.1108/EL-06-2020-0149
      Issue No: Vol. ahead-of-print, No. ahead-of-print (2021)
       
  • Archivists’ golden egg: environmental sustainability practices of
           archives

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      Authors: James Faulkner, Liuxing Lu, Jiangping Chen
      Abstract: Archivists are charged with the preservation of their collections by reducing deterioration because of temperature, relative humidity, atmospheric pollutants and other factors. The methods archivists use to preserve their collections may have a negative impact on the environment. This paper aims to identify factors for building environmentally sustainable archives to help guide archival environmental sustainability practices. This paper identifies factors through a literature review, and conducts a content analysis of the websites of seven national/state archives. The analysis focuses on the policy statements of these archives. The authors found that the literature lists 31 factors under 7 categories: electricity, facilities, water, exhibitions, pollution, collection practices and education and outreach. The content analysis of the policy documents or statements demonstrated that archives applied and addressed mostly “resource-related” efforts to protect the environment, such as factors related to electricity, facilities, water and pollution. However, factors related to “work-related” efforts, such as exhibitions, collection practices and education and outreach, were ignored. This study can provide insights to archivists on current implementation and help to guide their further environmental sustainability practices. Little is known regarding archivists’ implementation of environmentally sustainable practices. This study focuses on identifying factors for environmental sustainability of archives addressed by literature and existing archives, trying to find the gap between literature and practice.
      Citation: The Electronic Library
      PubDate: 2021-05-05
      DOI: 10.1108/EL-09-2020-0260
      Issue No: Vol. ahead-of-print, No. ahead-of-print (2021)
       
  • Determining the types of internet plus government platform usage behaviour
           in selected cities of China

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      Authors: Ge Wang , Qiang Chen , Shenghua Xie
      Abstract: Although internet plus government platforms (IPGPs) are being increasingly used by citizens around the world, questions emerge regarding the public adoption, utilization and use of IPGPs. This study aims to explore the determinants of citizens’ differentiated IPGPs usage behaviors. An analytical framework has been built upon the rational choice theory and the cultural dimension theory. The present study draws on a survey of 866 citizens from Guangzhou, Wuhan and Chengdu. The empirical findings suggest that the perceived functional benefits and personalization features both significantly affect citizens’ informational, service and participatory uses of IPGPs, to varying degrees. Furthermore, long-term orientation plays a moderating role in the relationship between perceived functional benefits and the service use of IPGPs. The findings demonstrate that the public’s rational choice of a new digitalized service channel depends on to what extent and to what degree the absolute and relative benefits they consider important compare to other possible channels. Users also consider how the new service channel satisfies their personalized demands of digitalized services. Also, users’ long-term orientation can affect their rational choices by adjusting the perceived functional benefits of the channel when that channel is used for service transactions.
      Citation: The Electronic Library
      PubDate: 2021-10-15
      DOI: 10.1108/EL-06-2021-0117
      Issue No: Vol. ahead-of-print , No. ahead-of-print (2021)
       
  • An empirical study on the adoption of blockchain-based games from
           users’ perspectives

         This is an Open Access Article Open Access Article

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      Authors: Shang Gao , Ying Li
      Abstract: The purpose of the research is to investigate users’ adoption of blockchain-based games in China. This research applied existing technology diffusion theories to develop a research model to examine users’ adoption of blockchain-based games. As a result, a research model with nine research hypotheses was developed. The developed research model was empirically tested using data collected from a survey of 210 blockchain-based games users. Structural equation modeling was applied to analyse the collected data. The results indicated that seven of nine research hypotheses were supported. It was found that trust, perceived usefulness, perceived enjoyment and perceived ease of use were key determinants for users’ behavioural intention to use blockchain-based games. The most influential relationship in the research model appeared to be the effect of perceived usefulness on users’ behavioural intention to use blockchain-based games. However, subjective norms did not have significant positive impacts on users’ behavioural intention to use blockchain-based games. The regulatory support from governmental authorities is essential to provide additional legal certainty to build users’ trust in playing blockchain-based games. Blockchain-based games providers should arrange the training program targeted to the general users to enhance their understanding of the key features associated with blockchain-based games. Blockchain-based games developers should come up with good design solutions to maximize user enjoyment with blockchain-based games by considering additional entertainment elements. To the best of the authors’ knowledge, this study is first of its kind in investigating the adoption of blockchain-based games from users’ perspectives. This study contributes to the existing literature on the adoption of blockchain technology.
      Citation: The Electronic Library
      PubDate: 2021-10-14
      DOI: 10.1108/EL-01-2021-0009
      Issue No: Vol. ahead-of-print , No. ahead-of-print (2021)
       
  • Application of gamification to library services: awareness, perception,
           and readiness of academic librarians in Nigeria

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      Authors: Ismail Olatunji Adeyemi , Adedoyin Oluwatosin Esan , Abdulmalik Aleem
      Abstract: Gamification is a growing field of study that has not been touched by Nigerian academic librarians. This study aims to explore the awareness, perception and readiness of academic librarians on the application of gamification to library services. This study adopts an interpretive research design and a qualitative research approach. This involves using semi-structured interviews to collect data for the study. Purposive sampling technique was used to select a sample of 20 participants but only 15 participated in the study. Participants were interviewed on their lived experience as to gamification; hence, phenomenology research method was adopted for the study. Thematic analysis was used to analyze collected data. The findings of the study show that most of the academic librarians in Nigeria were not aware of gamification to library services. However, the few that were aware knew about the gamification of library service through their personal academic reading. It was shown that there is a link between awareness and positive perception of gamification to library services. It was found that most of the academic librarians did not have a positive perception of applying gamification to library services in Nigeria. Results show that important factors to consider in readiness towards application of gamification to academic library services in Nigeria include library management support, librarians’ technical know-how and IT compliance. The findings of this study will provide insights as to academic librarians’ awareness, perception and readiness in applying gamification to library services in Nigeria and may provide insights into other developing Africa countries at large.
      Citation: The Electronic Library
      PubDate: 2021-10-07
      DOI: 10.1108/EL-05-2021-0096
      Issue No: Vol. ahead-of-print , No. ahead-of-print (2021)
       
  • Towards better library services: an investigation of factors affecting
           tourists’ satisfaction with “library + cultural tourism”

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      Authors: Ying Pan , Lia H. Sun , Heqing Yang , Jianming Zheng
      Abstract: “Library + cultural tourism” (LCT) is a new direction for the sustainable development of libraries, but few scholars have researched it from a tourist perspective. The purpose of this paper is to identify what factors affect tourist satisfaction (TS) with LCT, reveal the interaction among these factors and provide strategies for better library services. This study collected 5,308 comments on Tianjin Binhai Library from three popular online travel communities. Grounded theory was adopted to identify what factors affect TS with LCT and reveal the interaction among these factors. The results indicated that TS with LCT was affected by complex factors related to tour plans, tour expectations, cultural characteristics, environment, support services and emotions. Cultural characteristics, environment and support services were impacted by tour plans and tour expectations, which directly or indirectly affected TS mediated by emotions. TS further influenced their expectation of their next tour. This paper uncovered critical problems with LCT using a case study of Tianjin Binhai Library. The results provide a reference for library practitioners to develop better library services for tourists and regular users/readers.
      Citation: The Electronic Library
      PubDate: 2021-10-06
      DOI: 10.1108/EL-03-2021-0070
      Issue No: Vol. ahead-of-print , No. ahead-of-print (2021)
       
  • Research on influencing factors of information diffusion in online social
           networks under different themes

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      Authors: Ling Zhang , De Li , Robert J Boncella
      Abstract: This paper aims to study the factors influencing online social network (OSN) information diffusion under different themes helps to understand information diffusion in general. This study collects data from the Web of Science, use the strategic consulting intelligent support system for word frequency analysis and use keyword clustering to classify themes, then research information themes as influencing factors of OSN information diffusion. Five themes of “natural disaster”, “political event”, “product marketing”, “sport and entertainment” and “health-disease” have been identified. It is found that the research objects, research methods and research theories used by scholars under different themes have different focuses, and the factors affecting information diffusion are different. The limitation of this paper is that it only focuses on five typical themes, and there may be more themes. The research helps other scholars to conduct in-depth research on the diffusion of OSN information under different topics and focus on the content of the research on OSN information diffusion under different topics. The research helps other scholars to conduct in-depth research on the diffusion of social network information under different topics, so as to better understand and predict the law of information diffusion. The research summarizes the research on information diffusion in OSNs from the theme level and analyses the key points and theories and further enriches the research system on information diffusion in OSNs.
      Citation: The Electronic Library
      PubDate: 2021-10-06
      DOI: 10.1108/EL-12-2020-0329
      Issue No: Vol. ahead-of-print , No. ahead-of-print (2021)
       
  • Exploring the distribution regularities of user attention and sentiment
           toward product aspects in online reviews

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      Authors: Chenglei Qin , Chengzhi Zhang , Yi Bu
      Abstract: To better understand the online reviews and help potential consumers, businessmen and product manufacturers effectively obtain users’ evaluation on product aspects, this paper aims to explore the distribution regularities of users’ attention and sentiment on product aspects from the temporal perspective of online reviews. Temporal characteristics of online reviews (purchase time, review time and time intervals between purchase time and review time), similar attributes clustering and attribute-level sentiment computing technologies are used based on more than 340k smartphone reviews of three products from JD.COM (a famous online shopping platform in China) to explore the distribution regularities of users’ attention and sentiment on product aspects in this paper. The empirical results show that a power-law distribution can fit users’ attention on product aspects, and the reviews posted in short time intervals contain more product aspects. Besides, the results show that the values of users’ sentiment on product aspects are significantly higher/lower in short time intervals which contribute to judging the advantages and weaknesses of a product. This paper cannot acquire online reviews for more products with temporal characteristics to verify the findings because of the restriction on reviews crawling by the shopping platforms. This work reveals the distribution regularities of users’ attention and sentiment on product aspects, which is of great significance in assisting decision-making, optimizing review presentation and improving the shopping experience.
      Citation: The Electronic Library
      PubDate: 2021-10-05
      DOI: 10.1108/EL-11-2020-0324
      Issue No: Vol. ahead-of-print , No. ahead-of-print (2021)
       
  • A new subject-based retrieval and search result visualization approach for
           scientific digital libraries

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      Authors: Sayed Mahmood Bakhshayesh , Abbas Ahmadi , Azadeh Mohebi
      Abstract: Many search engines in digital libraries are restricted to the terms presented in users’ queries. When users cannot represent their information needs in terms of keywords in a query, the search engine fails to provide appropriate results. In addition, most search engines do not have the ability to visualize search results for users to help them in their information journey. The purpose of this paper is to develop a new approach for search result visualization in digital libraries. The visualization approach enables subject-based visualization of search results and search queries. To enable subject-based visualization of search results in digital libraries, new subject-based document retrieval is proposed in which each document is represented as a vector of subjects as well. Then, using a vector space model for information retrieval, along with the subject-based vector, related documents to the user’s query are retrieved, whilst each document is visualized through a ring chart, showing the inherent subjects within each document and the query. The proposed subject-based retrieval and visualization approach is evaluated from various perspectives to amplify the impact of the visualization approach from users’ opinions. Users have evaluated the performance of the proposed subject-based retrieval and search result visualization, whilst 67% of users prefer subject-based document retrieval and 80% of them believe that the proposed visualization approach is practical. This research has provided a subject-based representation scheme for search result visualization in a digital library. The implication of this research can be viewed from two perspectives. First, the subject-based retrieval approach provides an opportunity for the users to understand their information needs, beyond the explicit terms in the query, leading to results, which are semantically relevant to the query. Second, the simple subject-based visualization scheme, helps users to explore the results easily, whilst allowing them to build their knowledge experience. A new vectorized subject-based representation of documents and queries is proposed. This representation determines the semantic and subject-based relationship between a given query and documents within a digital scientific library. In addition, it also provides a subject-based representation of the retrieved documents through which users can track the semantic relationship between the query and retrieve documents, visually.
      Citation: The Electronic Library
      PubDate: 2021-09-22
      DOI: 10.1108/EL-08-2020-0243
      Issue No: Vol. ahead-of-print , No. ahead-of-print (2021)
       
  • Investigating the use of metadata record graphs to analyze subject
           headings in the digital public library of America

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      Authors: Mark Edward Phillips , Hannah Tarver
      Abstract: This study furthers metadata quality research by providing complementary network-based metrics and insights to analyze metadata records and identify areas for improvement. Metadata record graphs apply network analysis to metadata field values; this study evaluates the interconnectedness of subjects within each Hub aggregated into the Digital Public Library of America. It also reviews the effects of NACO normalization – simulating revision of values for consistency – and breaking up pre-coordinated subject headings – to simulate applying the Faceted Application of Subject Terminology to Library of Congress Subject Headings. Network statistics complement count- or value-based metrics by providing context related to the number of records a user might actually find starting from one item and moving to others via shared subject values. Additionally, connectivity increases through the normalization of values to correct or adjust for formatting differences or by breaking pre-coordinated subject strings into separate topics. This analysis focuses on exact-string matches, which is the lowest-common denominator for searching, although many search engines and digital library indexes may use less stringent matching methods. In terms of practical implications for evaluating or improving subjects in metadata, the normalization components demonstrate where resources may be most effectively allocated for these activities (depending on a collection). Although the individual components of this research are not particularly novel, network analysis has not generally been applied to metadata analysis. This research furthers previous studies related to metadata quality analysis of aggregations and digital collections in general.
      Citation: The Electronic Library
      PubDate: 2021-08-16
      DOI: 10.1108/EL-11-2020-0317
      Issue No: Vol. ahead-of-print , No. ahead-of-print (2021)
       
  • Public library Twitter use during the early period of the COVID-19
           lockdown in the United States

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      Authors: Youngok Choi , Sung Un Kim
      Abstract: The purpose of this study is to explore the Twitter use of public libraries during the early period of lockdown due to the COVID-19 pandemic to evaluate the focus of Twitter communication. A total of 57 active, public library Twitter accounts were used for data collection and analysis. The tweets examined were a combination of original tweets (n = 1,465) and retweets (n = 516) posted from other Twitter accounts on the public libraries’ Twitter feeds. A content analysis scheme was developed to analyse topical aspects of the tweets. The most frequent tweets were about library events, programmes and activities. However, there was a relatively low focus on sharing community information and addressing information related to the pandemic. The study suggests that public libraries could use Twitter to provide library resources and services to their patrons, whilst also acting as a virtual community centre safely keeping patrons engaged in the face of a global pandemic. By doing so, Twitter could be used as an integral part of promoting the mission of public libraries. The study examined a limited number of public libraries’ Twitter posts. Whilst the study carried out a random sampling of 10% of public libraries from the five states that had the highest COVID-19 cases in the month of April 2020, the study only examined tweets of 57 public libraries being active in posting. Thus, the findings of the study are not for generalizing. The content scheme includes content types regarding library services and community information. The content category scheme is general to reflect themes of content during a normal time and any emergency. Thus, this framework could be helpful for the content development of public libraries in planning social media use. The study used a new content analysis framework to examine both original tweets and retweets for information sharing of library services and community information. The approach of content analysis is distinctive to examine libraries’ communication trends on social media not only in normal times but also in times of crisis as well. The study also incorporated additional measures to assess Twitter practices including hashtags.
      Citation: The Electronic Library
      PubDate: 2021-08-09
      DOI: 10.1108/EL-03-2021-0067
      Issue No: Vol. ahead-of-print , No. ahead-of-print (2021)
       
  • Collecting and evaluating large volumes of bibliographic metadata
           aggregated in the WorldCat database: a proposed methodology to overcome
           challenges

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      Authors: Vyacheslav I. Zavalin , Shawne D. Miksa
      Abstract: This paper aims to discuss the challenges encountered in collecting, cleaning and analyzing the large data set of bibliographic metadata records in machine-readable cataloging [MARC 21] format. Possible solutions are presented. This mixed method study relied on content analysis and social network analysis. The study examined subject representation in MARC 21 metadata records created in 2020 in WorldCat – the largest international database of “big smart data.” The methodological challenges that were encountered and solutions are examined. In this general review paper with a focus on methodological issues, the discussion of challenges is followed by a discussion of solutions developed and tested as part of this study. Data collection, processing, analysis and visualization are addressed separately. Lessons learned and conclusions related to challenges and solutions for the design of a large-scale study evaluating MARC 21 bibliographic metadata from WorldCat are given. Overall recommendations for the design and implementation of future research are suggested. There are no previous publications that address the challenges and solutions of data collection and analysis of WorldCat’s “big smart data” in the form of MARC 21 data. This is the first study to use a large data set to systematically examine MARC 21 library metadata records created after the most recent addition of new fields and subfields to MARC 21 Bibliographic Format standard in 2019 based on resource description and access rules. It is also the first to focus its analyzes on the networks formed by subject terms shared by MARC 21 bibliographic records in a data set extracted from a heterogeneous centralized database WorldCat.
      Citation: The Electronic Library
      PubDate: 2021-08-09
      DOI: 10.1108/EL-11-2020-0316
      Issue No: Vol. ahead-of-print , No. ahead-of-print (2021)
       
  • An exploratory analysis: extracting materials science knowledge from
           unstructured scholarly data

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      Authors: Xintong Zhao , Jane Greenberg , Vanessa Meschke , Eric Toberer , Xiaohua Hu
      Abstract: The output of academic literature has increased significantly due to digital technology, presenting researchers with a challenge across every discipline, including materials science, as it is impossible to manually read and extract knowledge from millions of published literature. The purpose of this study is to address this challenge by exploring knowledge extraction in materials science, as applied to digital scholarship. An overriding goal is to help inform readers about the status knowledge extraction in materials science. The authors conducted a two-part analysis, comparing knowledge extraction methods applied materials science scholarship, across a sample of 22 articles; followed by a comparison of HIVE-4-MAT, an ontology-based knowledge extraction and MatScholar, a named entity recognition (NER) application. This paper covers contextual background, and a review of three tiers of knowledge extraction (ontology-based, NER and relation extraction), followed by the research goals and approach. The results indicate three key needs for researchers to consider for advancing knowledge extraction: the need for materials science focused corpora; the need for researchers to define the scope of the research being pursued, and the need to understand the tradeoffs among different knowledge extraction methods. This paper also points to future material science research potential with relation extraction and increased availability of ontologies. To the best of the authors’ knowledge, there are very few studies examining knowledge extraction in materials science. This work makes an important contribution to this underexplored research area.
      Citation: The Electronic Library
      PubDate: 2021-08-09
      DOI: 10.1108/EL-11-2020-0320
      Issue No: Vol. ahead-of-print , No. ahead-of-print (2021)
       
  • Towards an entity relation extraction framework in the cross-lingual
           context

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      Authors: Chuanming Yu , Haodong Xue , Manyi Wang , Lu An
      Abstract: Owing to the uneven distribution of annotated corpus among different languages, it is necessary to bridge the gap between low resource languages and high resource languages. From the perspective of entity relation extraction, this paper aims to extend the knowledge acquisition task from a single language context to a cross-lingual context, and to improve the relation extraction performance for low resource languages. This paper proposes a cross-lingual adversarial relation extraction (CLARE) framework, which decomposes cross-lingual relation extraction into parallel corpus acquisition and adversarial adaptation relation extraction. Based on the proposed framework, this paper conducts extensive experiments in two tasks, i.e. the English-to-Chinese and the English-to-Arabic cross-lingual entity relation extraction. The Macro-F1 values of the optimal models in the two tasks are 0.880 1 and 0.789 9, respectively, indicating that the proposed CLARE framework for CLARE can significantly improve the effect of low resource language entity relation extraction. The experimental results suggest that the proposed framework can effectively transfer the corpus as well as the annotated tags from English to Chinese and Arabic. This study reveals that the proposed approach is less human labour intensive and more effective in the cross-lingual entity relation extraction than the manual method. It shows that this approach has high generalizability among different languages. The research results are of great significance for improving the performance of the cross-lingual knowledge acquisition. The cross-lingual transfer may greatly reduce the time and cost of the manual construction of the multi-lingual corpus. It sheds light on the knowledge acquisition and organization from the unstructured text in the era of big data.
      Citation: The Electronic Library
      PubDate: 2021-08-03
      DOI: 10.1108/EL-10-2020-0304
      Issue No: Vol. ahead-of-print , No. ahead-of-print (2021)
       
  • Data set entity recognition based on distant supervision

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      Authors: Pengcheng Li , Qikai Liu , Qikai Cheng , Wei Lu
      Abstract: This paper aims to identify data set entities in scientific literature. To address poor recognition caused by a lack of training corpora in existing studies, a distant supervised learning-based approach is proposed to identify data set entities automatically from large-scale scientific literature in an open domain. Firstly, the authors use a dictionary combined with a bootstrapping strategy to create a labelled corpus to apply supervised learning. Secondly, a bidirectional encoder representation from transformers (BERT)-based neural model was applied to identify data set entities in the scientific literature automatically. Finally, two data augmentation techniques, entity replacement and entity masking, were introduced to enhance the model generalisability and improve the recognition of data set entities. In the absence of training data, the proposed method can effectively identify data set entities in large-scale scientific papers. The BERT-based vectorised representation and data augmentation techniques enable significant improvements in the generality and robustness of named entity recognition models, especially in long-tailed data set entity recognition. This paper provides a practical research method for automatically recognising data set entities in scientific literature. To the best of the authors’ knowledge, this is the first attempt to apply distant learning to the study of data set entity recognition. The authors introduce a robust vectorised representation and two data augmentation strategies (entity replacement and entity masking) to address the problem inherent in distant supervised learning methods, which the existing research has mostly ignored. The experimental results demonstrate that our approach effectively improves the recognition of data set entities, especially long-tailed data set entities.
      Citation: The Electronic Library
      PubDate: 2021-07-26
      DOI: 10.1108/EL-10-2020-0301
      Issue No: Vol. ahead-of-print , No. ahead-of-print (2021)
       
  • Personalized news recommendation based on an improved conditional
           restricted Boltzmann machine

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      Authors: Linxia Zhong , Wei Wei , Shixuan Li
      Abstract: Because of the extensive user coverage of news sites and apps, greater social and commercial value can be realized if users can access their favourite news as easily as possible. However, news has a timeliness factor; there are serious cold start and data sparsity in news recommendation, and news users are more susceptible to recent topical news. Therefore, this study aims to propose a personalized news recommendation approach based on topic model and restricted Boltzmann machine (RBM). Firstly, the model extracts the news topic information based on the LDA2vec topic model. Then, the implicit behaviour data are analysed and converted into explicit rating data according to the rules. The highest weight is assigned to recent hot news stories. Finally, the topic information and the rating data are regarded as the conditional layer and visual layer of the conditional RBM (CRBM) model, respectively, to implement news recommendations. The experimental results show that using LDA2vec-based news topic as a conditional layer in the CRBM model provides a higher prediction rating and improves the effectiveness of news recommendations. This study proposes a personalized news recommendation approach based on an improved CRBM. Topic model is applied to news topic extraction and used as the conditional layer of the CRBM. It not only alleviates the sparseness of rating data to improve the efficient in CRBM but also considers that readers are more susceptible to popular or trending news.
      Citation: The Electronic Library
      PubDate: 2021-07-22
      DOI: 10.1108/EL-06-2020-0165
      Issue No: Vol. ahead-of-print , No. ahead-of-print (2021)
       
  • Construction of metadata database structured by conceptual elements of
           text structure and semantic search evaluation of Korean studies

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      Authors: Young Man Ko , Min Sun Song , Seung Jun Lee
      Abstract: This study aims to develop metadata of conceptual elements based on the text structure of research articles on Korean studies, to propose a search algorithm that reflects the combination of semantically relevant data in accordance with the search intention of research paper and to examine the algorithm whether there is a difference in the intention-based search results. This study constructed a metadata database of 5,007 research articles on Korean studies arranged by conceptual elements of text structure and developed F1(w)-score weighted to conceptual elements based on the F1-score and the number of data points from each element. This study evaluated the algorithm by comparing search results of the F1(w)-score algorithm with those of the Term Frequency- Inverse Document Frequency (TF-IDF) algorithm and simple keyword search. The authors find that the higher the F1(w)-score, the closer the semantic relevance of search intention. Furthermore, F1(w)-score generated search results were more closely related to the search intention than those of TF-IDF and simple keyword search. Even though the F1(w)-score was developed in this study to evaluate the search results of metadata database structured by conceptual elements of text structure of Korean studies, the algorithm can be used as a tool for searching the database which is a tuning process of weighting required. A metadata database based on text structure and a search method based on weights of metadata elements – F1(w)-score – can be useful for interdisciplinary studies, especially for semantic search in regional studies. This paper presents a methodology for supporting IR using F1(w)-score—a novel model for weighting metadata elements based on text structure. The F1(w)-score-based search results show the combination of semantically relevant data, which are otherwise difficult to search for using similarity of search words.
      Citation: The Electronic Library
      PubDate: 2021-07-16
      DOI: 10.1108/EL-03-2021-0055
      Issue No: Vol. ahead-of-print , No. ahead-of-print (2021)
       
  • The role of library user preferences in the willingness to read and pay
           for e-books: case of the Czech Republic

         This is an Open Access Article Open Access Article

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      Authors: Jan Stejskal , Petr Hajek , Viktor Prokop
      Abstract: The study aims to analyse library user preferences in the willingness to read and pay for e-books, using a sample of both active readers (users of public library services) and non-users (the general population). Two empirical surveys were conducted from August to November of 2019; the research sample consisted of 1,334 users from the Municipal Library of Prague and 1,101 non-users from the general Czech population. The research was focussed on e-book user preferences. The willingness to pay (WTP) for e-book services and the determinants that affect this willingness were also examined. The results show the specific approach of Czech readers, whose main determinant of WTP is not the content, but the price and method of its payment (allocation). Some people prefer a cheaper annual lump sum, whereas others may prefer a charge of small regular fees. The decision to pay depends on their reading or payment habits. This study also aims to clarify the demand for various types of digital media in Czech libraries and the preferred distribution models. Furthermore, the study determines the dependence of the preferences of library users in their WTP for e-books using different evaluation models. The originality of this study is in the evaluation of the determinants of WTP for e-books, which makes this study unique, and the findings should contribute to the expansion of existing knowledge in the field of information science.
      Citation: The Electronic Library
      PubDate: 2021-07-05
      DOI: 10.1108/EL-01-2021-0001
      Issue No: Vol. ahead-of-print , No. ahead-of-print (2021)
       
  • Towards evolutionary knowledge representation under the big data
           circumstance

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      Authors: Xuhui Li , Liuyan Liu , Xiaoguang Wang , Yiwen Li , Qingfeng Wu , Tieyun Qian
      Abstract: The purpose of this paper is to propose a graph-based representation approach for evolutionary knowledge under the big data circumstance, aiming to gradually build conceptual models from data. A semantic data model named meaning graph (MGraph) is introduced to represent knowledge concepts to organize the knowledge instances in a graph-based knowledge base. MGraph uses directed acyclic graph–like types as concept schemas to specify the structural features of knowledge with intention variety. It also proposes several specialization mechanisms to enable knowledge evolution. Based on MGraph, a paradigm is introduced to model the evolutionary concept schemas, and a scenario on video semantics modeling is introduced in detail. MGraph is fit for the evolution features of representing knowledge from big data and lays the foundation for building a knowledge base under the big data circumstance. The representation approach based on MGraph can effectively and coherently address the major issues of evolutionary knowledge from big data. The new approach is promising in building a big knowledge base.
      Citation: The Electronic Library
      PubDate: 2021-07-05
      DOI: 10.1108/EL-11-2020-0318
      Issue No: Vol. ahead-of-print , No. ahead-of-print (2021)
       
  • An empirical examination of open source software adoption in US public
           libraries

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      Authors: Namjoo Choi
      Abstract: Similarly to Choi and Pruett (2019), which addressed open source software (OSS) adoption in the academic library context, this study aims to examine barriers and drivers to OSS adoption and to provide a snapshot of the current state of OSS adoption in US public libraries. An online survey of the public library staff members who oversee information systems/technology in their library was conducted. A total number of 288 valid responses were used for data analysis. A range of barriers and drivers to OSS adoption in US public libraries were revealed, but, unlike academic libraries, awareness was found to be a barrier. Additionally, the vast majority of the non-adopters showed very low levels of OSS adoption intent in the near future, more than that which was indicated by academic libraries. Several practical implications tailored for public libraries are provided, such as promoting OSS awareness among public libraries in rural and town areas, the importance of the initial trial/adoption and funding and marketing towards public libraries with small service population sizes and so on. Following Choi and Pruett (2019) which examined OSS adoption in the academic library context, this study conducted a similar online survey with US public libraries and made several contributions to the literature and to the public library field.
      Citation: The Electronic Library
      PubDate: 2021-06-01
      DOI: 10.1108/EL-01-2021-0013
      Issue No: Vol. ahead-of-print , No. ahead-of-print (2021)
       
  • The Electronic Library

    • Free pre-print version: Loading...

       
 
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