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Digital electronic network and optical storage technologies are revolutionizing publishing. The new technology enables a disaggregation of value and an associated dis‐integration of production. The dimensions of new information technologies can be explored more carefully by thinking about ten discrete characteristics or attributes of information products, or “types of value.” A modern print publisher is a broker or assembler of all the types of value. Mechanical print formats will continue to offer better utility to consumers than digital electronic formats as long as they have more of these types of value than digital electronic formats. Lightweight “notebook” portable microcomputers, having most of the power of desktop computers, and pen‐operating systems at least partially satisfy the first need, the need for book‐size flat panel displays. Three inter‐related software requirements remain to be satisfied: improved browsability, zooming capability, and improved annotation capability. Network and CD‐ROM technologies make it possible for a larger number of competing suppliers of specific types of added value to offer diverse products, with some of the features likely to cause consumers to shift their preferences from paper to electronic formats.

Music elicits emotions and acts as a cultural definer of class values, political beliefs, and economic life. Students are intrinsically drawn to and possess an innate ability for interpreting music. Music, moreover, activates learning in ways other content sources cannot; yet, it is utilized infrequently in social studies classrooms as a historical inquiry tool. Harnessing its emotive and seductive power, music as a primary source naturally scaffolds understanding of the zeitgeist through sensory engagement and lyrical analyses. Focusing on Born in the U.S.A. (Springsteen, 1984), authors demonstrate how examining music can impart views often absent from mass media portrayal of historical events and eras. A music listening and analysis tool is employed as a heuristic for critically interpreting music to explore the past. The historical thinking processes presented offer an inquiry-oriented curricular model for integrating music and social studies.

Classification, indexing and abstracting can all be regarded as summarisations of the content of a document. A model of text comprehension by indexers (including classifiers and abstractors) is presented, based on task descriptions which indicate that the comprehension of text for indexing differs from normal fluent reading in respect of: operational time constraints, which lead to text being scanned rapidly for perceptual cues to aid gist comprehension; comprehension being task oriented rather than learning oriented, and being followed immediately by the production of an abstract, index, or classification; and the automaticity of processing of text by experienced indexers working within a restricted range of text types. The evidence for the interplay of perceptual and conceptual processing of text under conditions of rapid scanning is reviewed. The allocation of mental resources to text processing is discussed, and a cognitive process model of abstracting, indexing and classification is described.

In a hypertext database, the information is presented as a network of nodes connected by links. Such nodes may be text, graphics, audio, video, and even other software. Although hypertext provides a new approach to information management, it also leaves a whole new set of problems for the designers of the hypertext database to solve. As the volume of information grows, the task of authoring a hypertext database becomes much more complex. In this article, the author presents the experiences during the development of a hypertext version of the user's guide for information services on JANET, in the UK, by using HyperPAD, a hypertext shell for the IBM PC. It may be the first step to explore the proper way to solve those problems which come together with the increasing application of hypertext.

The development of reader devices and improvement of screen technology have made reading on screens less cumbersome. Our acts of reading are not univocal, as we read in many different ways with many different goals in mind. Reader software can provide different levels of navigation support for the manipulation of digital text, presenting capabilities for analytic reading not available in the print‐on‐paper reading experience and compensating for our lack of orientation and feeling of omnipotent dominance of text. The parameters of e‐text reading and the issues of access remain central to readers and researchers, whether the electronic text is designed and packaged as an “e‐book” for portable reading devices, or resides on a server for distribution to library terminals to be downloaded to desktop PCs, laptops or tablet PCs. The power and functionality of reading software – note‐taking, highlighting and indexing capabilities, robust open searching across databases – are ultimately linked to open access issues: interoperability, text standards, and digital rights management. These remain key questions for libraries, publishers and researchers.

Recent work at the Cambridge Language Research Unit has been concerned with the development of automatic classification procedures for information retrieval. This has taken the form of research into methods of classification of keywords extracted from documents, with a view to using the classes found for coordinate indexing of technical material. We cannot claim to have solved this problem because the methods we have been able to develop so far cannot be applied on a sufficiently large scale. We have, however, made enough progress to make us feel that this is a fruitful line of research.

Extracting information from unstructured data becomes a challenging task for computational linguistics. Public figure’s statement attributed by journalists in a story is one type of information that can be processed into structured data. Therefore, having the knowledge base about this data will be very beneficial for further use, such as for opinion mining, claim detection and fact-checking. This study aims to understand statement extraction tasks and the models that have already been applied to formulate a framework for further study.

This paper presents a literature review from selected previous research that specifically addresses the topics of quotation extraction and quotation attribution. Research works that discuss corpus development related to quotation extraction and quotation attribution are also considered. The findings of the review will be used as a basis for proposing a framework to direct further research.

There are three findings in this study. Firstly, the extraction process still consists of two main tasks, namely, the extraction of quotations and the attribution of quotations. Secondly, most extraction algorithms rely on a rule-based algorithm or traditional machine learning. And last, the availability of corpus, which is limited in quantity and depth. Based on these findings, a statement extraction framework for Indonesian language corpus and model development is proposed.

The paper serves as a guideline to formulate a framework for statement extraction based on the findings from the literature study. The proposed framework includes a corpus development in the Indonesian language and a model for public figure statement extraction. Furthermore, this study could be used as a reference to produce a similar framework for other languages.

Describes a combined approach to delivering information literacy skills at The Open University Library. Outlines the aims of the newly formed Information Literacy Unit, and identifies three approaches currently used to incorporate information literacy into the curriculum. Focuses on MOSAIC (Making Sense of Information in the Connected Age), an on‐line information literacy course, in particular on issues around assessment, on‐line delivery and support, its use as a staff development tool and positive results of a recent survey. Recommends that information literacy is considered at a strategic level in the higher education sector.

This study aimed to examine the mental health information entities and associations between the biomedical, psychological and social domains of bipolar disorder (BD) by analyzing social media data and scientific literature.

Reddit posts and full-text papers from PubMed Central (PMC) were collected. The text analysis was used to create a psychological dictionary. The text mining tools were applied to extract BD entities and their relationships in the datasets using a dictionary- and rule-based approach. Lastly, social network analysis and visualization were employed to view the associations.

Mental health information on the drug side effects entity was detected frequently in both datasets. In the affective category, the most frequent entities were “depressed” and “severe” in the social media and PMC data, respectively. The social and personal concerns entities that related to friends, family, self-attitude and economy were found repeatedly in the Reddit data. The relationships between the biomedical and psychological processes, “afraid” and “Lithium” and “schizophrenia” and “suicidal,” were identified often in the social media and PMC data, respectively.

Mental health information has been increasingly sought-after, and BD is a mental illness with complicated factors in the clinical picture. This paper has made an original contribution to comprehending the biological, psychological and social factors of BD. Importantly, these results have highlighted the benefit of mental health informatics that can be analyzed in the laboratory and social media domains.

Many existing interventions to reduce excessive drinking in university students attempt to target individual cognitions, which ignore the wider contextual features that drive excessive drinking and mark this as an important aspect of university life. The purpose of this paper is to explore students’ views about preventing excessive drinking at university, specifically by using frameworks that take into both account individual and social influences.

In all, 23 young adults aged 20-30 (12 females; M age=22.91; SD=2.57; 18 students, five recent graduates) took part in semi-structured interviews to explore their views about drinking and measures to reduce excessive consumption. Transcripts were analysed using thematic analysis.

There were three themes identified in the analysis. These themes were named “the role of alcohol in student life”, drinking transitions’, and “prevention challenges” and each had related sub-themes.

Targeting students before they commence their course and highlighting aspects of university life that do not involve alcohol may help to reduce the pressure often felt to drink in social situations. Providing novel, credible alternative socialising options that do not involve alcohol should be explored to determine their acceptability, and their potential to reduce excessive drinking.

Few studies explore what students themselves think about reducing alcohol consumption and most interventions focus on changing individual cognitions rather than features of the social environment. This study highlights that changing social practices related to drinking in combination with targeting individuals may be more fruitful avenue to reduce excessive alcohol consumption.