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This paper aims to describe continuing effort to develop a repository of teaching materials for sharing and reuse in library and information science (LIS) schools in Asia. It also aims to propose a framework for carrying out a user study to validate the taxonomy and metadata, and evaluate how they support the reuse of teaching materials in four Asian countries.

This study uses a combination of approaches. The first phase focuses on building a repository of learning materials powered by taxonomy and metadata with enhanced searching and browsing capabilities. The second phase uses different evaluation techniques to propose a framework for assessing the usability of learning materials.

The potential for reuse of teaching materials in the area of information organization is examined by analyzing how various aspects of this topic are covered in three Master's programs in Information Studies, Knowledge Management, and Information Systems at Nanyang Technological University, Singapore. A faceted taxonomy has been helpful in tagging different types of learning objects. A metadata scheme based on DC‐Education and LOM has been used for enhanced description of learning materials.

This paper makes contributions in several ways. It suggests guidelines for developing taxonomies in different domains; describes steps in building repositories of learning materials; and suggests a methodology for studying reusability of learning material.

This paper aims to report a study of researchers' preferences in selecting information from cited papers to include in a literature review, and the kinds of transformations and editing applied to the selected information.

This is a part of a larger project to develop an automatic summarization method that emulates human literature review writing behaviour. Research questions were: how are literature reviews written – where do authors select information from, what types of information do they select and how do they transform it? What is the relationship between styles of literature review (integrative and descriptive) and each of these variables (source sections, types of information and types of transformation)? The authors analysed the literature review sections of 20 articles from the Journal of the American Society for Information Science and Technology, 2001‐2008, to answer these questions. Referencing sentences were mapped to 279 source papers to determine the source sentences. The type of information selected, the sections of source papers where the information was taken from, and the types of editing changes made to include in the literature review were analyzed.

Integrative literature reviews contain more research result information and critique, and reference more information from the results and conclusion sections of the source papers. Descriptive literature reviews contain more research method information, and reference more information from the abstract and introduction sections. The most common kind of transformation is the high‐level summary, though descriptive literature reviews have more cut‐pasting, especially for information taken from the abstract. The types of editing – substitutions, insertions and deletions – applied to the source sentences are identified.

The results are useful in the teaching of literature review writing, and indicate ways for automatic summarization systems to emulate human literature review writing.

Though there have been several studies of abstracts and abstracting, there are few studies of literature reviews and literature review writing. Little is known about how writers select information from source papers, integrate it and present it in a literature review. This paper fills some of the gaps.

A relevancy‐ranking algorithm for a natural language interface to Boolean online public access catalogs (OPACs) was formulated and compared with that currently used in a knowledge‐based search interface called the E‐Referencer, being developed by the authors. The algorithm makes use of seven well‐known ranking criteria: breadth of match, section weighting, proximity of query words, variant word forms (stemming), document frequency, term frequency and document length. The algorithm converts a natural language query into a series of increasingly broader Boolean search statements. In a small experiment with ten subjects in which the algorithm was simulated by hand, the algorithm obtained good results with a mean overall precision of 0.42 and mean average precision of 0.62, representing a 27 percent improvement in precision and 41 percent improvement in average precision compared to the E‐Referencer. The usefulness of each step in the algorithm was analyzed and suggestions are made for improving the algorithm.

The purpose of this study is to analyze the macro‐level discourse structure of literature reviews found in information science journal papers, and to identify different styles of literature review writing. Although there have been several studies of human abstracting, there are hardly any studies of how authors construct literature reviews.

This study is carried out in the context of a project to develop a summarization system to generate literature reviews automatically. A coding scheme was developed to annotate the high‐level organization of literature reviews, focusing on the types of information. Two sets of annotations were used to check inter‐coder reliability.

It was found that literature reviews are written in two distinctive styles, with different discourse structures. Descriptive literature reviews summarize individual papers/studies and provide more information on each study, such as research methods, results and interpretation. Integrative literature reviews provide fewer details of individual papers/studies, but focus on ideas and results extracted from these papers. They provide critical summaries of topics, and have a more complex structure of topics and sub‐topics. The reviewer's voice is also more dominant.

The coding scheme is useful for annotating the macro‐level discourse structure of literature reviews, and can be used for studying literature reviews in other fields. The basic characteristics of two styles of literature review writing are identified. The results have provided a foundation for further studies of literature reviews – to identify discourse relations and rhetorical functions employed in literature reviews, and their linguistic expressions.

The purpose of this research is to develop a method for automatic construction of multi‐document summaries of sets of news articles that might be retrieved by a web search engine in response to a user query.

Based on the cross‐document discourse analysis, an event‐based framework is proposed for integrating and organizing information extracted from different news articles. It has a hierarchical structure in which the summarized information is presented at the top level and more detailed information given at the lower levels. A tree‐view interface was implemented for displaying a multi‐document summary based on the framework. A preliminary user evaluation was performed by comparing the framework‐based summaries against the sentence‐based summaries.

In a small evaluation, all the human subjects preferred the framework‐based summaries to the sentence‐based summaries. It indicates that the event‐based framework is an effective way to summarize a set of news articles reporting an event or a series of relevant events.

Limited to event‐based news articles only, not applicable to news critiques and other kinds of news articles. A summarization system based on the event‐based framework is being implemented.

Multi‐document summarization of news articles can adopt the proposed event‐based framework.

An event‐based framework for summarizing sets of news articles was developed and evaluated using a tree‐view interface for displaying such summaries.

Potential and benefits of classification schemes and thesauri in building organizational taxonomies cannot be fully utilized by organizations. Empirical data of building an organizational taxonomy by the top‐down approach of using classification schemes and thesauri appear to be lacking. The paper seeks to make a contribution in this regard.

A case study of building an organizational taxonomy was conducted in the information studies domain for the Division of Information Studies at Nanyang Technology University, Singapore. The taxonomy was built by using the Dewey Decimal Classification, the Information Science Taxonomy, two information systems taxonomies, and three thesauri (ASIS&T, LISA, and ERIC).

Classification schemes and thesauri were found to be helpful in creating the structure and categories related to the subject facet of the taxonomy, but organizational community sources had to be consulted and several methods had to be employed. The organizational activities and stakeholders' needs had to be identified to determine the objectives, facets, and the subject coverage of the taxonomy. Main categories were determined by identifying the stakeholders' interests and consulting organizational community sources and domain taxonomies. Category terms were selected from terminologies of classification schemes, domain taxonomies, and thesauri against the stakeholders' interests. Hierarchical structures of the main categories were constructed in line with the stakeholders' perspectives and the navigational role taking advantage of structures/term relationships from classification schemes and thesauri. Categories were determined in line with the concepts and the hierarchical levels. Format of categories were uniformed according to a commonly used standard. The consistency principle was employed to make the taxonomy structure and categories neater. Validation of the draft taxonomy through consultations with the stakeholders further refined the taxonomy.

No similar study could be traced in the literature. The steps and methods used in the taxonomy development, and the information studies taxonomy itself, will be helpful for library and information schools and other similar organizations in their effort to develop taxonomies for organizing content and aiding navigation on organizational sites.

This paper aims to investigate the characteristics and differences in sentiment expression in movie review documents from four online opinion genres – blog postings, discussion board threads, user reviews, and critic reviews.

A collection of movie review documents was harvested from the four types of web sources, and a sample of 520 movie reviews were analysed to compare the content and textual characteristics across the four genres. The analysis focused on document and sentence length, part‐of‐speech distribution, vocabulary, aspects of movies discussed, star ratings used and multimedia content in the reviews. The study also identified frequently occurring positive and negative terms in the different genres, as well as the pattern of responses in discussion threads.

Critic reviews and blog postings are longer than user reviews and discussion threads, and contain longer sentences. Critic reviews and blogs contain more nouns and prepositions, whereas discussion board and user reviews have more verbs and adverbs. Critic reviews have the largest vocabulary and also the highest proportion of unique terms not found in the other genres. The most informative sentiment words in each genre are provided in the paper. With regard to content, critic reviews are more comprehensive in coverage, and discuss the movie director much more often than the other genres. User reviews discuss the scene aspects (including action and visual effects) more often than the other genres, while blogs tend to talk about the cast, and discuss the music and sound slightly more often.

The study only analysed movie review documents. Similar content and text analysis studies can be carried out in other domains, such as commercial product reviews, celebrity reviews, company reviews and political opinions to compare the results.

The main contribution of the study is the sentiment content analysis results across genres, which show the similarities and differences in content and textual characteristics in the four online opinion genres. The insights will be useful in designing automatic sentiment summarisation methods for multiple online genres.

Organizational researchers studying well-being – as well as organizations themselves – often place much of the burden on employees to manage and preserve their own well-being. Missing from this discussion is how – from a human resources management (HRM) perspective – organizations and managers can directly and positively shape the well-being of their employees. The authors use this review to paint a picture of what organizations could be like if they valued people holistically and embraced the full experience of employees’ lives to promote well-being at work. In so doing, the authors tackle five challenges that managers may have to help their employees navigate, but to date have received more limited empirical and theoretical attention from an HRM perspective: (1) recovery at work; (2) women’s health; (3) concealable stigmas; (4) caregiving; and (5) coping with socio-environmental jolts. In each section, the authors highlight how past research has treated managerial or organizational support on these topics, and pave the way for where research needs to advance from an HRM perspective. The authors conclude with ideas for tackling these issues methodologically and analytically, highlighting ways to recruit and support more vulnerable samples that are encapsulated within these topics, as well as analytic approaches to study employee experiences more holistically. In sum, this review represents a call for organizations to now – more than ever – build thriving organizations.

Sentiment analysis and emotion processing are attracting increasing interest in many fields. Computer and information scientists are developing automated methods for sentiment analysis of online text. Most of the studies have focused on identifying sentiment polarity or orientation – whether a document, usually a product or movie review, carries a positive or negative sentiment. It is time for researchers to address more sophisticated kinds of sentiment analysis. This paper aims to evaluate a particular linguistic framework called appraisal theory for adoption in manual as well as automatic sentiment analysis of news text.

The appraisal theory is applied to the analysis of a sample of political news articles reporting on Iraq and the economic policies of George W. Bush and Mahmoud Ahmadinejad to assess its utility and to identify challenges in adopting this framework.

The framework was useful in uncovering various aspects of sentiment that should be useful for researchers, such as the appraisers and object of appraisal, bias of the appraisers and the author, type of attitude and manner of expressing the sentiment. Problems encountered include difficulty in identifying appraisal phrases and attitude categories because of the subtlety of expression in political news articles, lack of treatment of tense and timeframe, lack of a typology of emotions, and need to identify different types of behaviours (political, verbal and material actions) that reflect sentiment.

The study has identified future directions for research in automated sentiment analysis as well as sentiment analysis of online news text. It has also demonstrated how sentiment analysis of news text can be carried out.

The following bibliography focuses mainly on programs which can run on IBM microcomputers and compatibles under the operating system PC DOS/MS DOS, and which can be used in online information and documentation work. They fall into the following categories: