Journal of Information Science    [599 followers]  Follow    
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
     ISSN (Print) 0165-5515 - ISSN (Online) 1741-6485
     Published by Sage Publications Homepage  [718 journals]   [SJR: 1.199]   [H-I: 35]
  • Static analysis and exponential random graph modelling for micro-blog
           network
    • Authors: Yang, D.-H; Yu, G.
      Pages: 3 - 14
      Abstract: Social network analysis has been used to study complex networks by analysing their static structure and the dynamic changes. Although one of the newer forms of social media, micro-blogs have quickly become one of the most popular communication platforms. This popularity accounts for, in part, an increase in the scientific interest in micro-blogs and their users. In this paper, we chose as our test bed diabetes-related posts from the Chinese micro-blog Sina Weibo. We calculated the degree, average shortest path, betweenness and clustering coefficient of the Sian Weibo network to analyse its static structure. We demonstrate the characteristic results of average degree, diameter and clustering coefficient of diabetes micro-blog static structure. More importantly, we introduce a general model for micro-blog with directed network data, Exponential-family Random Graph Models (ERGMs). Meanwhile, we illustrate the utility for estimating, analysing and simulating micro-blog network. We also provide a goodness-of-fit approach to capture and reproduce the structure of the fitted micro-blog network. Parameter estimation of the model, similarity results of simulated networks and observed networks, and goodness of fit analysis for the micro-blog network all illustrate that ERGMs are excellent methods for deeply capturing complex network structures.
      PubDate: 2014-01-16T07:26:02-08:00
      DOI: 10.1177/0165551513512251|hwp:master-id:spjis;0165551513512251
      Issue No: Vol. 40, No. 1 (2014)
       
  • A PAM-based ontology concept and hierarchy learning method
    • Authors: Yu, M; Wang, J, Zhao, X.
      Pages: 15 - 24
      Abstract: As a shared conceptual model that can express knowledge and a modelling tool that can describe conceptual model in the semantic and knowledge level, ontology plays an important role in the related fields of the Semantic Web, natural language processing and information retrieval. Ontology learning is a series of methods and technologies to construct ontology automatically or semi-automatically. Concept and hierarchy learning are the most important parts of the ontology construction. This paper proposes an ontology concept and hierarchy learning method based on the Pachinko Allocation Model. The above problem is transformed into a probability and statistical inference problem by building an ontology concept learning model. Gibbs sampling is used to estimate the parameters. Then, using the ontology concept generation algorithm based on WordNet, an abstract description of the ontology concept is obtained. Experimental results on the standard test dataset show that the proposed method can offer an effective solution to ontology concept and hierarchy learning.
      PubDate: 2014-01-16T07:26:02-08:00
      DOI: 10.1177/0165551513507406|hwp:master-id:spjis;0165551513507406
      Issue No: Vol. 40, No. 1 (2014)
       
  • Applying RADAR with new business postgraduates
    • Authors: Cullen; J. G.
      Pages: 25 - 27
      Abstract: In a recent ‘research in practice’ article in the Journal of Information Science, Mandalios introduced the RADAR tool, which she designed to assist students evaluate online information. She pointed out that the tool, although supported by preliminary qualitative research conducted at her own institution, required further empirical investigation. This brief communication aims to contribute empirical evidence which supports the efficacy of RADAR as a tool for evaluating online information resources by discussing student feedback on the application of the tool in an introductory session to a taught postgraduate business class. The context in which the RADAR tool was deployed is discussed, data on student reactions to it is reported and implications for future research are discussed.
      PubDate: 2014-01-16T07:26:02-08:00
      DOI: 10.1177/0165551513510094|hwp:master-id:spjis;0165551513510094
      Issue No: Vol. 40, No. 1 (2014)
       
  • Investigating the effect of definitions and best practice guidelines on
           errors in Dublin Core metadata records
    • Authors: Chuttur; M. Y.
      Pages: 28 - 37
      Abstract: Researchers argue that the utility of metadata records depends on the kinds of information used (i.e. definitions and best practice guidelines) when creating metadata. To verify this claim, a mixed factorial design experiment was conducted in which 120 participants were assigned to four groups on the basis of their training level and the kinds of information (definitions only or best practice guidelines) accessible to create metadata records. Participants used Dublin Core to create records for the same resources and errors were analysed and compared across groups. Although participants who used best practice guidelines made significantly fewer errors than those participants who used only definitions, the high error rates observed across all treatment groups suggest the need for additional measures to control errors in metadata records.
      PubDate: 2014-01-16T07:26:02-08:00
      DOI: 10.1177/0165551513507405|hwp:master-id:spjis;0165551513507405
      Issue No: Vol. 40, No. 1 (2014)
       
  • Keyword extraction for blogs based on content richness
    • Authors: Park, J; Kim, J, Lee, J.-H.
      Pages: 38 - 49
      Abstract: In this paper, a method is proposed to extract topic keywords of blogs, based on the richness of content. If a blog includes rich content related to a topic word, the word can be considered as a keyword of the blog. For this purpose, a new measure, richness, is proposed, which indicates how much a blog covers the trendy subtopics of a keyword. In order to obtain trendy subtopics of keywords, we use outside topical context data – the web. Since the web includes various and trendy information, we can find popular and trendy content related to a topic. For each candidate keyword, a set of web documents is retrieved by Google, and the subtopics found in the web documents are modelled by a probabilistic approach. Based on the subtopic models, the proposed method evaluates the richness of blogs for candidate keywords, in terms of how much a blog covers the trendy subtopics of keywords. If a blog includes various contents on a word, the word needs to be chosen as one of the keywords of the blog. In the experiments, the proposed method is compared with various methods, and shows better results, in terms of hit count, trendiness and consistency.
      PubDate: 2014-01-16T07:26:02-08:00
      DOI: 10.1177/0165551513508877|hwp:master-id:spjis;0165551513508877
      Issue No: Vol. 40, No. 1 (2014)
       
  • A proposed IPC-based clustering method for exploiting expert knowledge and
           its application to strategic planning
    • Authors: Chiu; T.-F.
      Pages: 50 - 66
      Abstract: In order to exploit the professional knowledge of the patent office examiners (implied in the IPC assignment) in the clustering process, a modified method (IPC-based clustering) has been proposed and applied to strategic planning. The performance of the proposed method was evaluated by comparison with two existing methods: K-Means and TwoStep of SPSS Clementine using the DB index and Dunn index. Afterwards, the IPC-based clustering (accompanied by link analysis) was applied to a practical domain (strategic planning) using the patent data of thin-film solar cell, so as to understand the possibility of implementing it in the management areas. According to the experimental results, the technical topics have been identified, and suggested strategies for companies have been generated for assisting the decision-making of top management. Finally, in future work the proposed method will be employed to other kinds of patent data to test its performance and applied to other practical domains to examine its feasibility in different management areas.
      PubDate: 2014-01-16T07:26:02-08:00
      DOI: 10.1177/0165551513507404|hwp:master-id:spjis;0165551513507404
      Issue No: Vol. 40, No. 1 (2014)
       
  • A hybrid approach to Arabic named entity recognition
    • Authors: Shaalan, K; Oudah, M.
      Pages: 67 - 87
      Abstract: In this paper, we propose a hybrid named entity recognition (NER) approach that takes the advantages of rule-based and machine learning-based approaches in order to improve the overall system performance and overcome the knowledge elicitation bottleneck and the lack of resources for underdeveloped languages that require deep language processing, such as Arabic. The complexity of Arabic poses special challenges to researchers of Arabic NER, which is essential for both monolingual and multilingual applications. We used the hybrid approach to develop an Arabic NER system that is capable of recognizing 11 types of Arabic named entities: Person, Location, Organization, Date, Time, Price, Measurement, Percent, Phone Number, ISBN and File Name. Extensive experiments were conducted using decision trees, Support Vector Machines and logistic regression classifiers to evaluate the system performance. The empirical results indicate that the hybrid approach outperforms both the rule-based and the ML-based approaches when they are processed independently. More importantly, our system outperforms the state-of-the-art of Arabic NER in terms of accuracy when applied to ANERcorp standard dataset, with F-measures 0.94 for Person, 0.90 for Location and 0.88 for Organization.
      PubDate: 2014-01-16T07:26:02-08:00
      DOI: 10.1177/0165551513502417|hwp:master-id:spjis;0165551513502417
      Issue No: Vol. 40, No. 1 (2014)
       
  • Slow Delphi: An investigation into information behaviour and the Slow
           Movement
    • Authors: Poirier, E; Robinson, L.
      Pages: 88 - 96
      Abstract: As part of a wider study of the relevance of the principles and practices of the Slow Movement to the information disciplines and professions, a Delphi study was carried out with 17 researchers in information behaviour and practices. A novel variant of the Delphi technique, termed the Slow Delphi, was devised for this study. This is aimed at eliciting qualitative understanding of complex conceptual topics, where there are a variety of perspectives and positions to be considered. The results of the study show a variety of points of potential applicability of Slow principles in research into information behaviour and practices, and in information provision. These include: more explicit inclusion of a temporal dimension in information behaviour models; greater recognition of the importance of the tempo of information seeking; more critical consideration of speed and scale as factors in the information environment; and the potential for individuals to exercise greater control over their information environment.
      PubDate: 2014-01-16T07:26:02-08:00
      DOI: 10.1177/0165551513506360|hwp:master-id:spjis;0165551513506360
      Issue No: Vol. 40, No. 1 (2014)
       
  • Hierarchical graph maps for visualization of collaborative recommender
           systems
    • Authors: Hernando, A; Moya, R, Ortega, F, Bobadilla, J.
      Pages: 97 - 106
      Abstract: In this paper we provide a method that allows the visualization of similarity relationships present between items of collaborative filtering recommender systems, as well as the relative importance of each of these. The objective is to offer visual representations of the recommender system’s set of items and of their relationships; these graphs show us where the most representative information can be found and which items are rated in a more similar way by the recommender system’s community of users. The visual representations achieved take the shape of phylogenetic trees, displaying the numerical similarity and the reliability between each pair of items considered to be similar. As a case study we provide the results obtained using the public database Movielens 1M, which contains 3900 movies.
      PubDate: 2014-01-16T07:26:02-08:00
      DOI: 10.1177/0165551513507407|hwp:master-id:spjis;0165551513507407
      Issue No: Vol. 40, No. 1 (2014)
       
  • Describing the development of molecular research in the context of nervous
           system diseases using year-based h-cores
    • Authors: Hu, X; Rousseau, R.
      Pages: 107 - 114
      Abstract: This article introduces year-based h-indices as a tool to produce easy-to-use research overviews. Based on PubMed data, a general framework is constructed to study the development of molecular research in the context of nervous system diseases. It is shown which molecular substances are the centre of attention and which have passed their peak. Year-based h-indices have the following interesting features for representing changes in a field or discipline: flexibility, sensitivity to dynamic changes, fluctuation detection and trend detection.
      PubDate: 2014-01-16T07:26:02-08:00
      DOI: 10.1177/0165551513502418|hwp:master-id:spjis;0165551513502418
      Issue No: Vol. 40, No. 1 (2014)
       
  • Short and amusing: The relationship between title characteristics,
           downloads, and citations in psychology articles
    • Authors: Subotic, S; Mukherjee, B.
      Pages: 115 - 124
      Abstract: The aim of this study was to conduct a unified investigation of various, previously mostly individually studied scientific article title characteristics, like: title length, type, amusement and pleasantness, and specific title ‘markers’ (e.g. colons, attention-grabbing words etc.) in relation to subsequent article citation and download rates. Based on a sample of 129 psychology ScienceDirect’s Top 25 Hottest Articles (i.e. highly downloaded articles) and 129 articles not appearing on the Top 25 list (i.e. less downloaded articles), we determined that the most relevant title characteristics were the title length and the title amusement/humour. The partial least squares model revealed that shorter titles were associated with more citations, but the effect was fully mediated by the journal impact, suggesting that the observed citational benefits of the shorter titles might be an artefact of some higher journal impact related attribute (perhaps editorial or peer review process). Title amusement level was slightly correlated with downloads, but with no association with citations. Additionally, downloads correlated positively with citations, and more amusing titles tended to be shorter. While these findings are limited to the psychology discipline only, our results suggest that the integrative structural approach is promising and that more research following this paradigm is needed before empirically grounded recommendations for good title writing can be given.
      PubDate: 2014-01-16T07:26:03-08:00
      DOI: 10.1177/0165551513511393|hwp:master-id:spjis;0165551513511393
      Issue No: Vol. 40, No. 1 (2014)
       
 
 
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