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The Electronic Library
Journal Prestige (SJR): 0.44
Citation Impact (citeScore): 1
Number of Followers: 1271  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0264-0473 - ISSN (Online) 1758-616X
Published by Emerald Homepage  [364 journals]
  • 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)
       
  • Information-seeking behavior of female doctor shoppers: results from an
           interview study

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      Authors: Shih-Chuan Chen
      Abstract: This study aims to explore the information-seeking behavior of female patients engaged in doctor shopping. An investigation was conducted on the following aspects: the reasons for doctor-shopping behavior (DSB), patients’ information needs and sources, patients’ use of the obtained information and the degree of satisfaction with the information collected. In-depth interviews were conducted in this study. In total, 30 female participants who lived or worked in the Taipei metropolitan area, Taiwan, were recruited. Dissatisfaction with treatment, confirmation of illness conditions, inconvenient treatment locations and hours and dissatisfaction with doctor’s attitude were the main reasons for DSB. Family members, friends, the internet and mass media were sources of information for participants when they sought second and successive doctors. In most cases, the degree of satisfaction toward the obtained information increased after each visit to a doctor during the doctor-shopping journey. However, not all participants shared information with doctors. The participants suggested that detailed explanations provided by doctors and better communication with doctors may reduce the occurrence of doctor shopping. The findings of this study help medical personnel better understand DSB. The findings revealed the significance of information to patients and indicated that the information collected during doctor shopping is beneficial for patients.
      Citation: The Electronic Library
      PubDate: 2021-05-07
      DOI: 10.1108/EL-04-2020-0092
      Issue No: Vol. ahead-of-print, No. ahead-of-print (2021)
       
  • University students’ attitudes towards ubiquitous library-supported
           learning: an empirical investigation in the context of the Line@Library

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      Authors: Yun-Fang Tu, Gwo-Jen Hwang, Joyce Chao-Chen Chen, Chiulin Lai
      Abstract: This study aims to investigate the influences of task-technology fit on university students’ attitudes towards ubiquitous library-supported learning when they use a mobile library app, Line@Library. In this study, structural equation modelling to examine 158 valid questionnaires are used. The study aims to examine the effects of task-technology fit (TTF) on university students’ attitudes towards mobile learning (AML) when using Line@Library. The results show that task-technology fit is an important role that influences the students’ attitudes towards mobile learning. The factor “technology characteristics” is considered when the students attempted to use the mobile app to solve problems or complete tasks. This study also found that the students responded with positive perceptions of the task-technology fit and had positive perceptions of its ease of use. Furthermore, usefulness, ease of use and affection of AML were found to be the most influential predictors of mobile library adoption intention. From the perspective of learners, this study investigates the relationships of the combination of social media and a mobile library between TTF and AML. This study further found that not only ease of use, usefulness and affection but also task-technology fit can be a predictor that influences students’ attitudes towards mobile learning.
      Citation: The Electronic Library
      PubDate: 2021-05-06
      DOI: 10.1108/EL-03-2020-0076
      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)
       
  • Entity influence and interactive relationship: the use of social media by
           publishing-related entities

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      Authors: Yanni Yang, Yue Zhang, An-Ling Xiang
      Abstract: The purpose of this paper is to explore factors influencing social media usage effectiveness of publishing-related entities and discuss the differences between publishing-related individuals and organizations in their usage of social media and the differences between commercial organizations and public service organizations (such as libraries). This paper studied 546 publishing-related entities’ accounts on the leading Chinese social media and built a theoretical model for the usage of social media by publishing-related entities. Furthermore, it examined the influencing factors from two aspects: power of influence of an entity (entity influence) and the relational interaction of a publishing-related entity with its audience (interactive relationship). The study found that for publishing-related individual users of social media, entity influence has a greater positive effect on the effectiveness of social media usage than on the effect of interactive relationship. For publishing-related commercial organizations, the entity influence and interactive relationship have equal impacts on the effectiveness of social media usage. It is also found that interactive relationship has a stronger positive effect on the usage effectiveness of social media, especially for publishing-related public service organizations. This research fills the gap in the research of comparative analysis in the understanding of social media usage by individuals and organizations related to publishing activities. Moreover, it has tried to propose a theoretical model that can help promote the effectiveness of social media usages by various publishing-related entities and their business strategies.
      Citation: The Electronic Library
      PubDate: 2021-04-05
      DOI: 10.1108/EL-08-2020-0228
      Issue No: Vol. ahead-of-print, No. ahead-of-print (2021)
       
  • What books will be your bestseller' A machine learning approach with
           Amazon Kindle

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      Authors: Seungpeel Lee, Honggeun Ji, Jina Kim, Eunil Park
      Abstract: With the rapid increase in internet use, most people tend to purchase books through online stores. Several such stores also provide book recommendations for buyer convenience, and both collaborative and content-based filtering approaches have been widely used for building these recommendation systems. However, both approaches have significant limitations, including cold start and data sparsity. To overcome these limitations, this study aims to investigate whether user satisfaction can be predicted based on easily accessible book descriptions. The authors collected a large-scale Kindle Books data set containing book descriptions and ratings, and calculated whether a specific book will receive a high rating. For this purpose, several feature representation methods (bag-of-words, term frequency–inverse document frequency [TF-IDF] and Word2vec) and machine learning classifiers (logistic regression, random forest, naive Bayes and support vector machine) were used. The used classifiers show substantial accuracy in predicting reader satisfaction. Among them, the random forest classifier combined with the TF-IDF feature representation method exhibited the highest accuracy at 96.09%. This study revealed that user satisfaction can be predicted based on book descriptions and shed light on the limitations of existing recommendation systems. Further, both practical and theoretical implications have been discussed.
      Citation: The Electronic Library
      PubDate: 2021-04-05
      DOI: 10.1108/EL-08-2020-0234
      Issue No: Vol. ahead-of-print, No. ahead-of-print (2021)
       
  • Facilitating learning by the visually impaired: development and usability
           evaluation of a specially designed ubiquitous library

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      Authors: Yun-Fang Tu, Gwo-Jen Hwang, Chiu-Lin Lai
      Abstract: This study aims to develop a ubiquitous library for the visually impaired (ULVI) application (app) and to explore its usability by collecting feedback from visually impaired participants to analyse the problems they might encounter. Their suggestions for improving the app further are also reported. A total of ten participants were recruited in the study. Ten tasks were assigned for the participants to complete using the ULVI app. The system usability scale was adopted to collect feedback on the app, and interviews were conducted to understand the participants’ usage behaviours and perceptions of the app. The findings indicated that the participants provided positive evaluation of the usability of the app and addressed the functions that might need improvement. Above all, this app was regarded as having great potential. Suggestions and improvements are proposed based on the participants’ feedback. In terms of the studies relevant to libraries and the visually impaired, few have evaluated the usability of the ULVI app from the perspectives of the visually impaired users. The ULVI app provides resources for the visually impaired and serves as the foundation for developing a more effective ULVI app.
      Citation: The Electronic Library
      PubDate: 2021-03-10
      DOI: 10.1108/EL-10-2020-0284
      Issue No: Vol. ahead-of-print, No. ahead-of-print (2021)
       
  • Building a training dataset for classification under a cost limitation

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      Authors: Yen-Liang Chen, Li-Chen Cheng, Yi-Jun Zhang
      Abstract: A necessary preprocessing of document classification is to label some documents so that a classifier can be built based on which the remaining documents can be classified. Because each document differs in length and complexity, the cost of labeling each document is different. The purpose of this paper is to consider how to select a subset of documents for labeling with a limited budget so that the total cost of the spending does not exceed the budget limit, while at the same time building a classifier with the best classification results. In this paper, a framework is proposed to select the instances for labeling that integrate two clustering algorithms and two centroid selection methods. From the selected and labeled instances, five different classifiers were constructed with good classification accuracy to prove the superiority of the selected instances. Experimental results show that this method can establish a training data set containing the most suitable data under the premise of considering the cost constraints. The data set considers both “data representativeness” and “data selection cost,” so that the training data labeled by experts can effectively establish a classifier with high accuracy. No previous research has considered how to establish a training set with a cost limit when each document has a distinct labeling cost. This paper is the first attempt to resolve this issue.
      Citation: The Electronic Library
      PubDate: 2021-02-24
      DOI: 10.1108/EL-07-2020-0209
      Issue No: Vol. ahead-of-print, No. ahead-of-print (2021)
       
  • A novel approach to the creation of a labelling lexicon for improving
           emotion analysis in text

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      Authors: Alejandra Segura Navarrete, Claudia Martinez-Araneda, Christian Vidal-Castro, Clemente Rubio-Manzano
      Abstract: This paper aims to describe the process used to create an emotion lexicon enriched with the emotional intensity of words and focuses on improving the emotion analysis process in texts. The process includes setting, preparation and labelling stages. In the first stage, a lexicon is selected. It must include a translation to the target language and labelling according to Plutchik’s eight emotions. The second stage starts with the validation of the translations. Then, it is expanded with the synonyms of the emotion synsets of each word. In the labelling stage, the similarity of words is calculated and displayed using WordNet similarity. The authors’ approach shows better performance to identification of the predominant emotion for the selected corpus. The most relevant is the improvement obtained in the results of the emotion analysis in a hybrid approach compared to the results obtained in a purist approach. The proposed lexicon can still be enriched by incorporating elements such as emojis, idioms and colloquial expressions. This work is part of a research project that aids in solving problems in a digital society, such as detecting cyberbullying, abusive language and gender violence in texts or exercising parental control. Detection of depressive states in young people and children is added. This semi-automatic process can be applied to any language to generate an emotion lexicon. This resource will be available in a software tool that implements a crowdsourcing strategy allowing the intensity to be re-labelled and new words to be automatically incorporated into the lexicon.
      Citation: The Electronic Library
      PubDate: 2021-02-08
      DOI: 10.1108/EL-04-2020-0110
      Issue No: Vol. ahead-of-print, No. ahead-of-print (2021)
       
  • Use analysis of the digital library of PhD dissertations defended at the
           University of Novi Sad

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      Authors: Ljubomir Paskali, Lidija Ivanovic, Dragan Ivanović
      Abstract: The purpose of this paper is to determine the digital library usage patterns as a means of improving the system, as well as the user experience, to give appropriate recognition to the most popular dissertations’ authors and to measure the interest of non-academic users for dissertations defended at the University of Novi Sad (UNS). A logging module of the digital library of theses and dissertations of University of Novi Sad (PHD UNS) application has been implemented. The module recorded the messages relating to the search queries and downloads over a three-year period from 2017–2019. These logs are analysed using the Elasticsearch, Logstash and Kibana (ELK) technology stack and the results are shown using graphs and tables. The analysis determined the perfect time for weekly maintenance of the system, defined a recommendation for improving the system and revealed the most popular dissertations. A significant number of downloads and queries originated from citizens, i.e. users outside the academic community. The conducted analysis defined recommendations for the system improvement which can be used by PHD UNS research and development (R&D) team and revealed the most popular dissertations which are used for the promotion of its authors through faculties’ websites. To the best of the authors’ knowledge, this is the first study of ELK based log analysis of a Serbian language documents’ repository. Besides, the value of results for the PHD UNS R&D team and UNS rector team, the study proves that PhD digital library presents an important Open Science communication channel for presenting scientific results to the citizens.
      Citation: The Electronic Library
      PubDate: 2021-02-08
      DOI: 10.1108/EL-11-2019-0268
      Issue No: Vol. ahead-of-print, No. ahead-of-print (2021)
       
  • An indexing system for the relevance of academic production and research
           from digital repositories and metadata

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      Authors: Jared David Tadeo Guerrero-Sosa, Víctor Hugo Menéndez-Domínguez, María Enriqueta Castellanos-Bolaños
      Abstract: This paper aims to propose a set of quantitative statistical indicators for measuring the scientific relevance of research groups and researchers, based on high-impact open-access digital production repositories. An action research (AR) methodology is proposed in which research is associated with the practice; research informs practice and practice is responsible for informing research in a cooperative way. AR is divided into five phases, beginning with the definition of the problematic scenario and an analysis of the state of the art and ending with conducting tests and publishing the results. The proposed indicators were used to characterise group and individual output in a major public university in south-eastern Mexico. University campuses hosting a large number of high-impact research groups. These indicators were very useful in generating information that confirmed specific assumptions about the scientific production of the university. The data used here were retrieved from Scopus and open access national repository of Mexico. It would be possible to use other data sources to calculate these indicators. The system used to implement the proposed indicators is independent of any particular technological tool and is based on standards for metadata description and exchange, thus facilitating the easy integration of new elements for evaluation. Many organisations evaluate researchers according to specific criteria, one of which is the prestige of journals. Although the guidelines differ between evaluation bodies, relevance is measured based on elements that can be adapted and where some have greater weight than others, including the prestige of the journal, the degree of collaboration with other researchers and individual production, etc. The proposed indicators can be used by various entities to evaluate researchers and research groups. Each country has its own organisations that are responsible for evaluation, using various criteria based on the impact of the publications. The proposed indicators assess based on the importance of the types of publications and the degree of collaborations. However, they can be adapted to other similar scenarios.
      Citation: The Electronic Library
      PubDate: 2021-01-25
      DOI: 10.1108/EL-06-2020-0160
      Issue No: Vol. ahead-of-print, No. ahead-of-print (2021)
       
  • The Electronic Library

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