Diese Datenbank enthält über 40.000 Dokumente zu Themen aus den Bereichen Formalerschließung – Inhaltserschließung – Information Retrieval.
© 2015 W. Gödert, TH Köln, Institut für Informationswissenschaft / Powered by litecat, BIS Oldenburg (Stand: 28. April 2022)
1Walsh, J.A. ; Cobb, P.J. ; Fremery, W. de ; Golub, K. ; Keah, H. ; Kim, J. ; Kiplang'at, J. ; Liu, Y.-H. ; Mahony, S. ; Oh, S.G. ; Sula, C.A. ; Underwood, T. ; Wang, X.: Digital humanities in the iSchool.
In: Journal of the Association for Information Science and Technology. 73(2022) no.2, S.188-203.
(JASIST special issue on digital humanities (DH): A. Landscapes of DH)
Abstract: The interdisciplinary field known as digital humanities (DH) is represented in various forms in the teaching and research practiced in iSchools. Building on the work of an iSchools organization committee charged with exploring digital humanities curricula, we present findings from a series of related studies exploring aspects of DH teaching, education, and research in iSchools, often in collaboration with other units and disciplines. Through a survey of iSchool programs and an online DH course registry, we investigate the various education models for DH training found in iSchools, followed by a detailed look at DH courses and curricula, explored through analysis of course syllabi and course descriptions. We take a brief look at collaborative disciplines with which iSchools cooperate on DH research projects or in offering DH education. Next, we explore DH careers through an analysis of relevant job advertisements. Finally, we offer some observations about the management and administrative challenges and opportunities related to offering a new iSchool DH program. Our results provide a snapshot of the current state of digital humanities in iSchools which may usefully inform the design and evolution of new DH programs, degrees, and related initiatives.
Inhalt: Vgl.: https://asistdl.onlinelibrary.wiley.com/doi/10.1002/asi.24535.
Themenfeld: Elektronisches Publizieren
2Wang, X. ; Zhang, M. ; Fan, W. ; Zhao, K.: Understanding the spread of COVID-19 misinformation on social media : the effects of topics and a political leader's nudge.
In: Journal of the Association for Information Science and Technology. 73(2022) no.5, S.726-737.
Abstract: The spread of misinformation on social media has become a major societal issue during recent years. In this work, we used the ongoing COVID-19 pandemic as a case study to systematically investigate factors associated with the spread of multi-topic misinformation related to one event on social media based on the heuristic-systematic model. Among factors related to systematic processing of information, we discovered that the topics of a misinformation story matter, with conspiracy theories being the most likely to be retweeted. As for factors related to heuristic processing of information, such as when citizens look up to their leaders during such a crisis, our results demonstrated that behaviors of a political leader, former US President Donald J. Trump, may have nudged people's sharing of COVID-19 misinformation. Outcomes of this study help social media platform and users better understand and prevent the spread of misinformation on social media.
Inhalt: Vgl.: https://asistdl.onlinelibrary.wiley.com/doi/10.1002/asi.24576. https://doi.org/10.1002/asi.24576.
3Wang, X. ; High, A. ; Wang, X. ; Zhao, K.: Predicting users' continued engagement in online health communities from the quantity and quality of received support.
In: Journal of the Association for Information Science and Technology. 72(2021) no.6, S.710-722.
Abstract: This article presents a rare insight into the migration of municipality record-keeping databases. The migration of a database for preservation purposes poses Online health communities (OHCs) have been major resources for people with similar health concerns to interact with each other. They offer easily accessible platforms for users to seek, receive, and provide supports by posting. Taking the advantage of text mining and machine learning techniques, we identified social support type(s) in each post and a new user's support needs in an OHC. We examined a user's first-time support-seeking experience by measuring both quantity and quality of received support. Our results revealed that the amount and match of received support are positive and significant predictors of new users' continued engagement. Our outcomes can provide insight for designing and managing a sustainable OHC by retaining users.
Inhalt: Vgl.: https://asistdl.onlinelibrary.wiley.com/doi/10.1002/asi.24436.
4Fang, Z. ; Costas, R. ; Tian, W. ; Wang, X. ; Wouters, P.: How is science clicked on Twitter? : click metrics for Bitly short links to scientific publications.
In: Journal of the Association for Information Science and Technology. 72(2021) no.7, S.918-932.
Abstract: To provide some context for the potential engagement behavior of Twitter users around science, this article investigates how Bitly short links to scientific publications embedded in scholarly Twitter mentions are clicked on Twitter. Based on the click metrics of over 1.1 million Bitly short links referring to Web of Science (WoS) publications, our results show that around 49.5% of them were not clicked by Twitter users. For those Bitly short links with clicks from Twitter, the majority of their Twitter clicks accumulated within a short period of time after they were first tweeted. Bitly short links to the publications in the field of Social Sciences and Humanities tend to attract more clicks from Twitter over other subject fields. This article also assesses the extent to which Twitter clicks are correlated with some other impact indicators. Twitter clicks are weakly correlated with scholarly impact indicators (WoS citations and Mendeley readers), but moderately correlated to other Twitter engagement indicators (total retweets and total likes). In light of these results, we highlight the importance of paying more attention to the click metrics of URLs in scholarly Twitter mentions, to improve our understanding about the more effective dissemination and reception of science information on Twitter.
Inhalt: Vgl.: https://asistdl.onlinelibrary.wiley.com/doi/10.1002/asi.24458.
5Wang, X. ; Duan, Q. ; Liang, M.: Understanding the process of data reuse : an extensive review.
In: Journal of the Association for Information Science and Technology. 72(2021) no.9, S.1161-1182.
Abstract: Data reuse has recently become significant in academia and is providing new impetus for academic research. This prompts two questions: What precisely is the data reuse process? What is the connection between each participating element? To address these issues, 42 studies were reviewed to identify the stages and primary data reuse elements. A meta-synthesis was used to locate and analyze the studies, and inductive coding was used to organize the analytical process. We identified three stages of data reuse-initiation, exploration and collection, and repurposing-and explored how they interact and form iterative characteristics. The results illuminated the data reuse at each stage, including issues of data trust, data sources, scaffolds, and barriers. The results indicated that multisource data and human scaffolds promote reuse behavior effectively. Further, two data and information search patterns were extracted: reticular centripetal patterns and decentralized centripetal patterns. Three paths with elements cooperating through flexible functions and motivated by different action items were identified: data centers, human scaffolds, and publications. This study supports improvements for data infrastructure construction, data reuse, and data reuse research by providing a new perspective on the effect of information behavior and clarifying the stages and contextual relationships between various elements.
Inhalt: Vgl.: https://asistdl.onlinelibrary.wiley.com/doi/10.1002/asi.24483.
6Tan, X. ; Luo, X. ; Wang, X. ; Wang, H. ; Hou, X.: Representation and display of digital images of cultural heritage : a semantic enrichment approach.
In: Knowledge organization. 48(2021) no.3, S.231-247.
Abstract: Digital images of cultural heritage (CH) contain rich semantic information. However, today's semantic representations of CH images fail to fully reveal the content entities and context within these vital surrogates. This paper draws on the fields of image research and digital humanities to propose a systematic methodology and a technical route for semantic enrichment of CH digital images. This new methodology systematically applies a series of procedures including: semantic annotation, entity-based enrichment, establishing internal relations, event-centric enrichment, defining hierarchy relations between properties text annotation, and finally, named entity recognition in order to ultimately provide fine-grained contextual semantic content disclosure. The feasibility and advantages of the proposed semantic enrichment methods for semantic representation are demonstrated via a visual display platform for digital images of CH built to represent the Wutai Mountain Map, a typical Dunhuang mural. This study proves that semantic enrichment offers a promising new model for exposing content at a fine-grained level, and establishing a rich semantic network centered on the content of digital images of CH.
Inhalt: Vgl.: doi.org/10.5771/0943-7444-2021-3-231.
7Wang, F. ; Wang, X.: Tracing theory diffusion : a text mining and citation-based analysis of TAM.
In: Journal of documentation. 76(2020) no.6, S.1109-1134.
Abstract: Theory is a kind of condensed human knowledge. This paper is to examine the mechanism of interdisciplinary diffusion of theoretical knowledge by tracing the diffusion of a representative theory, the Technology Acceptance Model (TAM). Design/methodology/approach Based on the full-scale dataset of Web of Science (WoS), the citations of Davis's original work about TAM were analysed and the interdisciplinary diffusion paths of TAM were delineated, a supervised machine learning method was used to extract theory incidents, and a content analysis was used to categorize the patterns of theory evolution. Findings It is found that the diffusion of a theory is intertwined with its evolution. In the process, the role that a participating discipline play is related to its knowledge distance from the original disciplines of TAM. With the distance increases, the capacity to support theory development and innovation weakens, while that to assume analytical tools for practical problems increases. During the diffusion, a theory evolves into new extensions in four theoretical construction patterns, elaboration, proliferation, competition and integration. Research limitations/implications The study does not only deepen the understanding of the trajectory of a theory but also enriches the research of knowledge diffusion and innovation. Originality/value The study elaborates the relationship between theory diffusion and theory development, reveals the roles of the participating disciplines played in theory diffusion and vice versa, interprets four patterns of theory evolution and uses text mining technique to extract theory incidents, which makes up for the shortcomings of citation analysis and content analysis used in previous studies.
Inhalt: Vgl.: https://doi.org/10.1108/JD-02-2020-0023.
8Reyes Ayala, B. ; Knudson, R. ; Chen, J. ; Cao, G. ; Wang, X.: Metadata records machine translation combining multi-engine outputs with limited parallel data.
In: Journal of the Association for Information Science and Technology. 69(2018) no.1, S.47-59.
Abstract: One way to facilitate Multilingual Information Access (MLIA) for digital libraries is to generate multilingual metadata records by applying Machine Translation (MT) techniques. Current online MT services are available and affordable, but are not always effective for creating multilingual metadata records. In this study, we implemented 3 different MT strategies and evaluated their performance when translating English metadata records to Chinese and Spanish. These strategies included combining MT results from 3 online MT systems (Google, Bing, and Yahoo!) with and without additional linguistic resources, such as manually-generated parallel corpora, and metadata records in the two target languages obtained from international partners. The open-source statistical MT platform Moses was applied to design and implement the three translation strategies. Human evaluation of the MT results using adequacy and fluency demonstrated that two of the strategies produced higher quality translations than individual online MT systems for both languages. Especially, adding small, manually-generated parallel corpora of metadata records significantly improved translation performance. Our study suggested an effective and efficient MT approach for providing multilingual services for digital collections.
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23925/full.
9Yang, B. ; Rousseau, R. ; Wang, X. ; Huang, S.: How important is scientific software in bioinformatics research? : a comparative study between international and Chinese research communities.
In: Journal of the Association for Information Science and Technology. 69(2018) no.9, S.1122-1133.
Abstract: Software programs are among the most important tools in data-driven research. The popularity of well-known packages and corresponding large numbers of citations received bear testimony of the contribution of scientific software to academic research. Yet software is not generally recognized as an academic outcome. In this study, a usage-based model is proposed with varied indicators including citations, mentions, and downloads to measure the importance of scientific software. We performed an investigation on a sample of international bioinformatics research articles, and on a sample from the Chinese community. Our analysis shows that scientists in the field of bioinformatics rely heavily on scientific software: the major differences between the international community and the Chinese example being how scientific packages are mentioned in publications and the time gap between the introduction of a package and its use. Biologists publishing in international journals tend to apply the latest tools earlier; Chinese scientists publishing in Chinese tend to follow later. Further, journals with higher impact factors tend to publish articles applying the latest tools earlier.
Inhalt: Vgl.: https://onlinelibrary.wiley.com/doi/10.1002/asi.24031.
10Wang, X. ; Hong, Z. ; Xu, Y.(C.) ; Zhang, C. ; Ling, H.: Relevance judgments of mobile commercial information.
In: Journal of the Association for Information Science and Technology. 65(2014) no.7, S.1335-1348.
Abstract: In the age of mobile commerce, users receive floods of commercial messages. How do users judge the relevance of such information? Is their relevance judgment affected by contextual factors, such as location and time? How do message content and contextual factors affect users' privacy concerns? With a focus on mobile ads, we propose a research model based on theories of relevance judgment and mobile marketing research. We suggest topicality, reliability, and economic value as key content factors and location and time as key contextual factors. We found mobile relevance judgment is affected mainly by content factors, whereas privacy concerns are affected by both content and contextual factors. Moreover, topicality and economic value have a synergetic effect that makes a message more relevant. Higher topicality and location precision exacerbate privacy concerns, whereas message reliability alleviates privacy concerns caused by location precision. These findings reveal an interesting intricacy in user relevance judgment and privacy concerns and provide nuanced guidance for the design and delivery of mobile commercial information.
11Ding, Y. ; Zhang, G. ; Chambers, T. ; Song, M. ; Wang, X. ; Zhai, C.: Content-based citation analysis : the next generation of citation analysis.
In: Journal of the Association for Information Science and Technology. 65(2014) no.9, S.1820-1833.
Abstract: Traditional citation analysis has been widely applied to detect patterns of scientific collaboration, map the landscapes of scholarly disciplines, assess the impact of research outputs, and observe knowledge transfer across domains. It is, however, limited, as it assumes all citations are of similar value and weights each equally. Content-based citation analysis (CCA) addresses a citation's value by interpreting each one based on its context at both the syntactic and semantic levels. This paper provides a comprehensive overview of CAA research in terms of its theoretical foundations, methodical approaches, and example applications. In addition, we highlight how increased computational capabilities and publicly available full-text resources have opened this area of research to vast possibilities, which enable deeper citation analysis, more accurate citation prediction, and increased knowledge discovery.
Themenfeld: Citation indexing
12Wang, X. ; Erdelez, S. ; Allen, C. ; Anderson, B. ; Cao, H. ; Shyu, C.-R.: Role of domain knowledge in developing user-centered medical-image indexing.
In: Journal of the American Society for Information Science and Technology. 63(2012) no.2, S.225-241.
Abstract: An efficient and robust medical-image indexing procedure should be user-oriented. It is essential to index the images at the right level of description and ensure that the indexed levels match the user's interest level. This study examines 240 medical-image descriptions produced by three different groups of medical-image users (novices, intermediates, and experts) in the area of radiography. This article reports several important findings: First, the effect of domain knowledge has a significant relationship with the use of semantic image attributes in image-users' descriptions. We found that experts employ more high-level image attributes which require high-reasoning or diagnostic knowledge to search for a medical image (Abstract Objects and Scenes) than do novices; novices are more likely to describe some basic objects which do not require much radiological knowledge to search for an image they need (Generic Objects) than are experts. Second, all image users in this study prefer to use image attributes of the semantic levels to represent the image that they desired to find, especially using those specific-level and scene-related attributes. Third, image attributes generated by medical-image users can be mapped to all levels of the pyramid model that was developed to structure visual information. Therefore, the pyramid model could be considered a robust instrument for indexing medical imagery.
13Jiang, Y. ; Zheng, H.-T. ; Wang, X. ; Lu, B. ; Wu, K.: Affiliation disambiguation for constructing semantic digital libraries.
In: Journal of the American Society for Information Science and Technology. 62(2011) no.6, S.1029-1041.
Abstract: With increasing digital information availability, semantic web technologies have been employed to construct semantic digital libraries in order to ease information comprehension. The use of semantic web enables users to search or visualize resources in a semantic fashion. Semantic web generation is a key process in semantic digital library construction, which converts metadata of digital resources into semantic web data. Many text mining technologies, such as keyword extraction and clustering, have been proposed to generate semantic web data. However, one important type of metadata in publications, called affiliation, is hard to convert into semantic web data precisely because different authors, who have the same affiliation, often express the affiliation in different ways. To address this issue, this paper proposes a clustering method based on normalized compression distance for the purpose of affiliation disambiguation. The experimental results show that our method is able to identify different affiliations that denote the same institutes. The clustering results outperform the well-known k-means clustering method in terms of average precision, F-measure, entropy, and purity.
14Teo, H.-H. ; Wang, X. ; Wei, K.-K. ; Sia, C.-L. ; Lee, M.K.O.: Organizational learning capacity and attitude toward complex technological innovations : an empirical study.
In: Journal of the American Society for Information Science and Technology. 57(2006) no.2, S.264-279.
Abstract: Recent studies have found organizational learning capacity to be a key factor in influencing organizational assimilation and exploitation of knowledge-intensive innovations. Despite its increasing importance, the impact of organizational learning capacity an technology assimilation is not well understood. Distilling from extant works an organizational learning and technology assimilation, this study identifies four components of organizational learning capacity, namely, systems orientation, organizational climate for learning orientation, knowledge acquisition and utilization orientation, and information sharing and dissemination orientation. The authors subject these components to structural equation modeling analyses to better understand their structure and dimensionality. The analyses strongly support the proposed four major dimensions underlying organizational learning capacity. Organizational learning capacity, as a higher-order factor, has a significant impact an attitude towards organizational adoption of knowledge-intensive innovations. Implications for practice and research are discussed.