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)
1Zhang, J. ; Chen, Y. ; Zhao, Y. ; Wolfram, D. ; Ma, F.: Public health and social media : a study of Zika virus-related posts on Yahoo! Answers.
In: Journal of the Association for Information Science and Technology. 71(2020) no.3, S.282-299.
Abstract: This study investigates the content of questions and responses about the Zika virus on Yahoo! Answers as a recent example of how public concerns regarding an international health issue are reflected in social media. We investigate the contents of posts about the Zika virus on Yahoo! Answers, identify and reveal subject patterns about the Zika virus, and analyze the temporal changes of the revealed subject topics over 4 defined periods of the Zika virus outbreak. Multidimensional scaling analysis, temporal analysis, and inferential statistical analysis approaches were used in the study. A resulting 2-layer Zika virus schema, and term connections and relationships are presented. The results indicate that consumers' concerns changed over the 4 defined periods. Consumers paid more attention to the basic information about the Zika virus, and the prevention and protection from the Zika virus at the beginning of the outbreak of the Zika virus. During the later periods, consumers became more interested in the role that the government and health organizations played in the public health emergency.
Inhalt: Vgl.: https://asistdl.onlinelibrary.wiley.com/doi/10.1002/asi.24245.
2Castanha, R.C.G. ; Wolfram, D.: ¬The domain of knowledge organization : a bibliometric analysis of prolific authors and their intellectual space.
In: Knowledge organization. 45(2018) no.1, S.13-22.
Abstract: The domain of knowledge organization (KO) represents a foundational area of information science. One way to better understand the intellectual structure of the KO domain is to apply bibliometric methods to key contributors to the literature. This study analyzes the most prolific contributing authors to the journal Knowledge Organization, the sources they cite and the citations they receive for the period 1993 to 2016. The analyses were conducted using visualization outcomes of citation, co-citation and author bibliographic coupling analysis to reveal theoretical points of reference among authors and the most prominent research themes that constitute this scientific community. Birger Hjørland was the most cited author, and was situated at or near the middle of each of the maps based on different citation relationships. The proximities between authors resulting from the different citation relationships demonstrate how authors situate themselves intellectually through the citations they give and how other authors situate them through the citations received. There is a consistent core of theoretical references as well among the most productive authors. We observed a close network of scholarly communication between the authors cited in this core, which indicates the actual role of the journal Knowledge Organization as a space for knowledge construction in the area of knowledge organization.
3Park, H. ; You, S. ; Wolfram, D.: Informal data citation for data sharing and reuse is more common than formal data citation in biomedical fields.
In: Journal of the Association for Information Science and Technology. 69(2018) no.11, S.1346-1354.
Abstract: Data citation, where products of research such as data sets, software, and tissue cultures are shared and acknowledged, is becoming more common in the era of Open Science. Currently, the practice of formal data citation-where data references are included alongside bibliographic references in the reference section of a publication-is uncommon. We examine the prevalence of data citation, documenting data sharing and reuse, in a sample of full text articles from the biological/biomedical sciences, the fields with the most public data sets available documented by the Data Citation Index (DCI). We develop a method that combines automated text extraction with human assessment for revealing candidate occurrences of data sharing and reuse by using terms that are most likely to indicate their occurrence. The analysis reveals that informal data citation in the main text of articles is far more common than formal data citations in the references of articles. As a result, data sharers do not receive documented credit for their data contributions in a similar way as authors do for their research articles because informal data citations are not recorded in sources such as the DCI. Ongoing challenges for the study of data citation are also outlined.
Inhalt: Vgl.: https://onlinelibrary.wiley.com/doi/10.1002/asi.24049.
4Lu, K. ; Cai, X. ; Ajiferuke, I. ; Wolfram, D.: Vocabulary size and its effect on topic representation.
In: Information processing and management. 53(2017) no.3, S.653-665.
Abstract: This study investigates how computational overhead for topic model training may be reduced by selectively removing terms from the vocabulary of text corpora being modeled. We compare the impact of removing singly occurring terms, the top 0.5%, 1% and 5% most frequently occurring terms and both top 0.5% most frequent and singly occurring terms, along with changes in the number of topics modeled (10, 20, 30, 40, 50, 100) using three datasets. Four outcome measures are compared. The removal of singly occurring terms has little impact on outcomes for all of the measures tested. Document discriminative capacity, as measured by the document space density, is reduced by the removal of frequently occurring terms, but increases with higher numbers of topics. Vocabulary size does not greatly influence entropy, but entropy is affected by the number of topics. Finally, topic similarity, as measured by pairwise topic similarity and Jensen-Shannon divergence, decreases with the removal of frequent terms. The findings have implications for information science research in information retrieval and informetrics that makes use of topic modeling.
Inhalt: Vgl.: http://www.sciencedirect.com/science/article/pii/S0306457317300298.
5Wolfram, D.: ¬The power to influence : an informetric analysis of the works of Hope Olson.
In: Knowledge organization. 43(2016) no.5, S.331-337.
Abstract: This paper examines the influence of the works of Hope A. Olson by conducting an ego-centric informetric analysis of her published works. Publication and citation data were collected from Google Scholar and the Thomson Reuters Web of Science. Classic informetrics techniques were applied to the datasets including co-authorship analysis, citer analysis, citation and co-citation analysis and text-based analysis. Co-citation and text-based data were analyzed and visualized using VOSviewer and CiteSpace, respectively. The analysis of her citation identity reveals how Dr. Olson situates her own research within the knowledge landscape while the analysis of her citation image reveals how others have situated her work in relation to the authors with whom she has been co-cited. This reflection of Dr. Olson's research contributions reveals the influence of her scholarship not only on knowledge organization but other areas of library and information science and allied disciplines.
Inhalt: Beitrag in: Special Issue: "A Festschrift for Hope A. Olson," Guest Editor Thomas Walker.
7Wang, F. ; Wolfram, D.: Assessment of journal similarity based on citing discipline analysis.
In: Journal of the Association for Information Science and Technology. 66(2015) no.6, S.1189-1198.
Abstract: This study compares the range of disciplines of citing journal articles to determine how closely related journals assigned to the same Web of Science research area are. The frequency distribution of disciplines by citing articles provides a signature for a cited journal that permits it to be compared with other journals using similarity comparison techniques. As an initial exploration, citing discipline data for 40 high-impact-factor journals assigned to the "information science and library science" category of the Web of Science were compared across 5 time periods. Similarity relationships were determined using multidimensional scaling and hierarchical cluster analysis to compare the outcomes produced by the proposed citing discipline and established cocitation methods. The maps and clustering outcomes reveal that a number of journals in allied areas of the information science and library science category may not be very closely related to each other or may not be appropriately situated in the category studied. The citing discipline similarity data resulted in similar outcomes with the cocitation data but with some notable differences. Because the citing discipline method relies on a citing perspective different from cocitations, it may provide a complementary way to compare journal similarity that is less labor intensive than cocitation analysis.
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23241/abstract.
8Lu, K. ; Wolfram, D.: Measuring author research relatedness : a comparison of word-based, topic-based, and author cocitation approaches.
In: Journal of the American Society for Information Science and Technology. 63(2012) no.10, S.1973-1986.
Abstract: Relationships between authors based on characteristics of published literature have been studied for decades. Author cocitation analysis using mapping techniques has been most frequently used to study how closely two authors are thought to be in intellectual space based on how members of the research community co-cite their works. Other approaches exist to study author relatedness based more directly on the text of their published works. In this study we present static and dynamic word-based approaches using vector space modeling, as well as a topic-based approach based on latent Dirichlet allocation for mapping author research relatedness. Vector space modeling is used to define an author space consisting of works by a given author. Outcomes for the two word-based approaches and a topic-based approach for 50 prolific authors in library and information science are compared with more traditional author cocitation analysis using multidimensional scaling and hierarchical cluster analysis. The two word-based approaches produced similar outcomes except where two authors were frequent co-authors for the majority of their articles. The topic-based approach produced the most distinctive map.
9Ajiferuke, I. ; Lu, K. ; Wolfram, D.: ¬A comparison of citer and citation-based measure outcomes for multiple disciplines.
In: Journal of the American Society for Information Science and Technology. 61(2010) no.10, S.2086-2096.
Abstract: Author research impact was examined based on citer analysis (the number of citers as opposed to the number of citations) for 90 highly cited authors grouped into three broad subject areas. Citer-based outcome measures were also compared with more traditional citation-based measures for levels of association. The authors found that there are significant differences in citer-based outcomes among the three broad subject areas examined and that there is a high degree of correlation between citer and citation-based measures for all measures compared, except for two outcomes calculated for the social sciences. Citer-based measures do produce slightly different rankings of authors based on citer counts when compared to more traditional citation counts. Examples are provided. Citation measures may not adequately address the influence, or reach, of an author because citations usually do not address the origin of the citation beyond self-citations.
10Wolfram, D. ; Wang, P. ; Zhang, J.: Identifying Web search session patterns using cluster analysis : a comparison of three search environments.
In: Journal of the American Society for Information Science and Technology. 60(2009) no.5, S.896-910.
Abstract: Session characteristics taken from large transaction logs of three Web search environments (academic Web site, public search engine, consumer health information portal) were modeled using cluster analysis to determine if coherent session groups emerged for each environment and whether the types of session groups are similar across the three environments. The analysis revealed three distinct clusters of session behaviors common to each environment: hit and run sessions on focused topics, relatively brief sessions on popular topics, and sustained sessions using obscure terms with greater query modification. The findings also revealed shifts in session characteristics over time for one of the datasets, away from hit and run sessions toward more popular search topics. A better understanding of session characteristics can help system designers to develop more responsive systems to support search features that cater to identifiable groups of searchers based on their search behaviors. For example, the system may identify struggling searchers based on session behaviors that match those identified in the current study to provide context sensitive help.
11Zhang, J. ; Wolfram, D. ; Wang, P.: Analysis of query keywords of sports-related queries using visualization and clustering.
In: Journal of the American Society for Information Science and Technology. 60(2009) no.8, S.1550-1571.
Abstract: The authors investigated 11 sports-related query keywords extracted from a public search engine query log to better understand sports-related information seeking on the Internet. After the query log contents were cleaned and query data were parsed, popular sports-related keywords were identified, along with frequently co-occurring query terms associated with the identified keywords. Relationships among each sports-related focus keyword and its related keywords were characterized and grouped using multidimensional scaling (MDS) in combination with traditional hierarchical clustering methods. The two approaches were synthesized in a visual context by highlighting the results of the hierarchical clustering analysis in the visual MDS configuration. Important events, people, subjects, merchandise, and so on related to a sport were illustrated, and relationships among the sports were analyzed. A small-scale comparative study of sports searches with and without term assistance was conducted. Searches that used search term assistance by relying on previous query term relationships outperformed the searches without the search term assistance. The findings of this study provide insights into sports information seeking behavior on the Internet. The developed method also may be applied to other query log subject areas.
12Wolfram, D. ; Olson, H.A. ; Bloom, R.: Measuring consistency for multiple taggers using vector space modeling.
In: Journal of the American Society for Information Science and Technology. 60(2009) no.10, S.1995-2003.
Abstract: A longstanding area of study in indexing is the identification of factors affecting vocabulary usage and consistency. This topic has seen a recent resurgence with a focus on social tagging. Tagging data for scholarly articles made available by the social bookmarking Website CiteULike (www.citeulike.org) were used to test the use of inter-indexer/tagger consistency density values, based on a method developed by the authors by comparing calculations for highly tagged documents representing three subject areas (Science, Social Science, Social Software). The analysis revealed that the developed method is viable for a large dataset. The findings also indicated that there were no significant differences in tagging consistency among the three topic areas, demonstrating that vocabulary usage in a relatively new subject area like social software is no more inconsistent than the more established subject areas investigated. The implications of the method used and the findings are discussed.
Themenfeld: Social tagging
13Wolfram, D. ; Zhang, J.: ¬The influence of indexing practices and weighting algorithms on document spaces.
In: Journal of the American Society for Information Science and Technology. 59(2008) no.1, S.3-11.
Abstract: Index modeling and computer simulation techniques are used to examine the influence of indexing frequency distributions, indexing exhaustivity distributions, and three weighting methods on hypothetical document spaces in a vector-based information retrieval (IR) system. The way documents are indexed plays an important role in retrieval. The authors demonstrate the influence of different indexing characteristics on document space density (DSD) changes and document space discriminative capacity for IR. Document environments that contain a relatively higher percentage of infrequently occurring terms provide lower density outcomes than do environments where a higher percentage of frequently occurring terms exists. Different indexing exhaustivity levels, however, have little influence on the document space densities. A weighting algorithm that favors higher weights for infrequently occurring terms results in the lowest overall document space densities, which allows documents to be more readily differentiated from one another. This in turn can positively influence IR. The authors also discuss the influence on outcomes using two methods of normalization of term weights (i.e., means and ranges) for the different weighting methods.
14Wolfram, D.: Search characteristics in different types of Web-based IR environments : are they the same?.
In: Information processing and management. 44(2008) no.3, S.1279-1292.
Abstract: Transaction logs from four different Web-based information retrieval environments (bibliographic databank, OPAC, search engine, specialized search system) were analyzed for empirical regularities in search characteristics to determine whether users engage in different behaviors in different Web-based search environments. Descriptive statistics and relative frequency distributions related to term usage, query formulation, and session duration were tabulated. The analysis revealed that there are differences in these characteristics. Users were more likely to engage in extensive searching using the OPAC and specialized search system. Surprisingly, the bibliographic databank search environment resulted in the most parsimonious searching, more similar to a general search engine. Although on the surface Web-based search facilities may appear similar, users do engage in different search behaviors.
15Olson, H.A. ; Wolfram, D.: Syntagmatic relationships and indexing consistency on a larger scale.
In: Journal of documentation. 64(2008) no.4, S.602-615.
Abstract: Purpose - The purpose of this article is to examine interindexer consistency on a larger scale than other studies have done to determine if group consensus is reached by larger numbers of indexers and what, if any, relationships emerge between assigned terms. Design/methodology/approach - In total, 64 MLIS students were recruited to assign up to five terms to a document. The authors applied basic data modeling and the exploratory statistical techniques of multi-dimensional scaling (MDS) and hierarchical cluster analysis to determine whether relationships exist in indexing consistency and the coocurrence of assigned terms. Findings - Consistency in the assignment of indexing terms to a document follows an inverse shape, although it is not strictly power law-based unlike many other social phenomena. The exploratory techniques revealed that groups of terms clustered together. The resulting term cooccurrence relationships were largely syntagmatic. Research limitations/implications - The results are based on the indexing of one article by non-expert indexers and are, thus, not generalizable. Based on the study findings, along with the growing popularity of folksonomies and the apparent authority of communally developed information resources, communally developed indexes based on group consensus may have merit. Originality/value - Consistency in the assignment of indexing terms has been studied primarily on a small scale. Few studies have examined indexing on a larger scale with more than a handful of indexers. Recognition of the differences in indexing assignment has implications for the development of public information systems, especially those that do not use a controlled vocabulary and those tagged by end-users. In such cases, multiple access points that accommodate the different ways that users interpret content are needed so that searchers may be guided to relevant content despite using different terminology.
16Zhang, J. ; Wolfram, D. ; Wang, P. ; Hong, Y. ; Gillis, R.: Visualization of health-subject analysis based on query term co-occurrences.
In: Journal of the American Society for Information Science and Technology. 59(2008) no.12, S.1933-1947.
Abstract: A multidimensional-scaling approach is used to analyze frequently used medical-topic terms in queries submitted to a Web-based consumer health information system. Based on a year-long transaction log file, five medical focus keywords (stomach, hip, stroke, depression, and cholesterol) and their co-occurring query terms are analyzed. An overlap-coefficient similarity measure and a conversion measure are used to calculate the proximity of terms to one another based on their co-occurrences in queries. The impact of the dimensionality of the visual configuration, the cutoff point of term co-occurrence for inclusion in the analysis, and the Minkowski metric power k on the stress value are discussed. A visual clustering of groups of terms based on the proximity within each focus-keyword group is also conducted. Term distributions within each visual configuration are characterized and are compared with formal medical vocabulary. This investigation reveals that there are significant differences between consumer health query-term usage and more formal medical terminology used by medical professionals when describing the same medical subject. Future directions are discussed.
17Ajiferuke, I. ; Wolfram, D.: Analysis of Web page image tag distribution characteristics.
In: Information processing and management. 41(2005) no.4, S.987-1002.
Abstract: The authors investigate the frequency distribution of the use of image tags in Web pages. Using data sampled from top level Web pages across five top level domains and from sample pages within individual websites, the authors model observed patterns in the frequency of image tag usage by fitting collected data distributions to different theoretical models used in informetrics. Models tested include the modified power law (MPL), Mandelbrot (MDB), generalized waring (GW), generalized inverse Gaussian-Poisson (GIGP), and generalized negative binomial (GNB) distributions. The GIGP provided the best fit for data sets for top level pages across the top level domains tested. The poor fits of the models to the observed data distributions from specific websites were due to the multimodal nature of the observed data sets. Mixtures of the tested models for the data sets provided better fits. The ability to effectively model Web page attributes, such as the distribution of the number of image tags used per page, is needed for accurate simulation models of Web page content, and makes it possible to estimate the number of requests needed to display the complete content of Web pages.
18Wolfram, D.: Applied informetrics for information retrieval research.
Westport, CT : Greenwood Press, 2003. 232 S.
Abstract: The author demonstrates how informetric analysis of information retrieval system content and use provides valuable insights that have applications for the modelling, design, and evaluation of information retrieval systems.
19Wolfram, D. ; Xie, H.I.: Traditional IR for web users : a context for general audience digital libraries.
In: Information processing and management. 38(2002) no.5, S.627-648.
Anmerkung: Beitrag in einem Themenheft: "Issues of context in information retrieval (IR)"
Themenfeld: Semantisches Umfeld in Indexierung u. Retrieval
20Xie, H.I. ; Wolfram, D.: State digital library usability contributing organizational factors.
In: Journal of the American Society for Information Science and technology. 53(2002) no.13, S.1085-1097.
Abstract: In this issue Xie and Wolfram study the Wisconsin state digital library BadgerLink to determine the organizational factors that lead to different use requirements and the degree to which these are met, as well as impact on physical libraries. To this end, usage data from EBSCOhost and ProQuest logs for BadgerLink were analyzed, 313 Wisconsin libraries of all types were surveyed (76% response rate), and analyzed along with 81 responses to a voluntary web survey of end users. Heaviest users were K-12 schools and institutions of higher education. Heaviest use sites were the two largest state universities and the state's largest public library. Small libraries were infrequent users. Web survey respondents were mature working professionals. Sixty percent searched for specific information, but 46% reported browsing in subject areas. Libraries with dedicated Internet access reported more frequent usage than those with dial-up connection. Those who accessed from libraries reported more frequent use than those at work or at home. Libraries that trained end users reported more use, but the majority of the web survey respondents reported themselves as self-taught. Logs confirm reported subject interests. Three surrogates were requested for every full text document but full text availability is reported as the reason for use by 30% of users. Availability has led to the cancellation of subscriptions in many libraries that are important promoters of the service. A model will need to include interactions based upon the influence of each involved participant on the others. It will also need to include the extension of the activities of one participant to other participant organizations and the communication among these organizations.