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In this paper the authors seek to compare lay (consumer) and professional (physician) discourse structures in answers to diabetes‐related questions in a public consumer health information website.

Ten consumer and ten physician question threads were aligned. They generated 26 consumer and ten physician answers, constituting a total dataset of 717 discourse units (in sentences or sentence fragments). The authors depart from previous LIS health information behaviour research by utilizing a computational linguistics‐based theoretical framework of rhetorical structure theory, which enables research at the pragmatics level of linguistics in terms of the goals and effects of human communication.

The authors reveal differences in discourse organization by identifying prevalent rhetorical relations in each type of discourse. Consumer answers included predominately (66 per cent) presentational rhetorical structure relations, those intended to motivate or otherwise help a user do something (e.g. motivation, concession, and enablement). Physician answers included mainly subject matter relations (64 per cent), intended to inform, or simply transfer information to a user (e.g. elaboration, condition, and interpretation).

The findings suggest different communicative goals expressed in lay and professional health information sharing. Consumers appear to be more motivating, or activating, and more polite (linguistically) than physicians in how they share information with consumers online in similar topics in diabetes management. The authors consider whether one source of information encourages adherence to healthy behaviour more effectively than another.

Analysing discourse structure – using rhetorical structure theory – is a novel and promising approach in information behaviour research, and one that traverses the lexico‐semantic level of linguistic analysis towards pragmatics of language use.

The purpose of this paper is to present an algorithm to generate story problems via controlled parameters in the domain of mathematics. The generation process is performed in the problem generation module in the context of an intelligent tutoring system suggested in this paper. Controlling the question parameters allows for adapting the generated questions according to the specific student needs. Story problems are selected since they are one of the most important types of problems in mathematics, as they help train students to apply their knowledge to real-world problems. Such problems target improving different student’s skills including literacy skills through reading the problem, recognizing the embedded mathematical information, and applying the required arithmetic operators.

Natural language generation (NLG) techniques are used to control the difficulty level of the generated story problem header in addition to effecting variations from the natural language point of view. The proposed NLG technique is based on different separated knowledge categories to provide flexibility in the generation process and allow porting the module to other contexts, domains, and to other natural languages without a complete redesign.

The approach has been empirically evaluated, and the results show that the generated problems are sound, clear, and naturally readable. This is in addition to the usability of the tutoring system itself.

The generation technique is confined to the problem described using rhetorical schemas. Nevertheless, it can generate any problem provided that the rhetorical schema is available.

Most story problems generation systems limit the variation of the story problems to formulating the sentences that describe the story problem and the associated mathematical operations. In contrast, this paper presents a story problems generation technique that allows variations in the structure of the narrative story as well as the context, sentences, wordings, and mathematical operations. This variability allows assessing different student skills along different dimensions with gradually increasing difficulty levels.

Narrative comments about dentists on physician review sites have been documented to increasingly influence people's selection of their dentists. From a communication standpoint, these comments are a type of narrative communication that people share their experiences with dentists by telling stories. Based on the frameworks of rhetoric structure theory and extended elaborated likelihood model, this study aimed to examine the effects of such storytelling from two perspectives including narrative structure and narrative focus.

A 4 (narrative structure) × 2 (narrative focus) between-subjects experiment was conducted to examine the proposed hypotheses and research questions

The results showed that a one-sided comprehensive comment focusing on technical competence generated the strongest persuasion effects measured by attitude and behavioral intention. These effects were mediated by perceived narrative credibility and enjoyment.

This study contributes to the extant literature in two ways. First, it extends previous studies of online narrative comments by showing which narrative structure and focus are deemed to be more persuasive when selecting a dentist. Second, it offers a test of two routes of information processing (i.e. cognitive and experiential) to understand the mechanism underlying the effects of narrative comments.

The peer-review history for this article is available at: https://publons.com/publon/10.1108/OIR-08-2020-0359

The purpose of this paper is to lay a theoretical foundation for identifying operational information units for library and information professional activities in the context of scholarly communication.

The study adopts a deduction-verification approach to formulate a typology of units for scholarly information. It first deduces possible units from an existing conceptualization of information, which defines information as the combined product of data and meaning, and then tests the usefulness of these units via two empirical investigations, one with a group of scholarly papers and the other with a sample of scholarly information users.

The results show that, on defining an information unit as a piece of information that is complete in both data and meaning, to such an extent that it remains meaningful to its target audience when retrieved and displayed independently in a database, it is then possible to formulate a hierarchical typology of units for scholarly information. The typology proposed in this study consists of three levels, which in turn, consists of 1, 5 and 44 units, respectively.

The result of this study has theoretical implications on both the philosophical and conceptual levels: on the philosophical level, it hinges on, and reinforces the objective view of information; on the conceptual level, it challenges the conceptualization of work by IFLA’s Functional Requirements for Bibliographic Records and Library Reference Model but endorses that by Library of Congress’s BIBFRAME 2.0 model.

It calls for reconsideration of existing operational units in a variety of library and information activities.

The study strengthens the conceptual foundation of operational information units and brings to light the primacy of “one work” as an information unit and the possibility for it to be supplemented by smaller units.

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.

The purpose of this paper is to look into the latest advances in ontology-based text summarization systems, with emphasis on the methodologies of a socio-cognitive approach, the structural discourse models and the ontology-based text summarization systems.

The paper analyzes the main literature in this field and presents the structure and features of Texminer, a software that facilitates summarization of texts on Port and Coastal Engineering. Texminer entails a combination of several techniques, including: socio-cognitive user models, Natural Language Processing, disambiguation and ontologies. After processing a corpus, the system was evaluated using as a reference various clustering evaluation experiments conducted by Arco (2008) and Hennig et al. (2008). The results were checked with a support vector machine, Rouge metrics, the F-measure and calculation of precision and recall.

The experiment illustrates the superiority of abstracts obtained through the assistance of ontology-based techniques.

The authors were able to corroborate that the summaries obtained using Texminer are more efficient than those derived through other systems whose summarization models do not use ontologies to summarize texts. Thanks to ontologies, main sentences can be selected with a broad rhetorical structure, especially for a specific knowledge domain.

Browsing a database of article abstracts is one way to select and buy relevant magazine articles online. Our research contributes to the design and development of text grammars for abstracting texts in unlimited subject domains. We developed a system that parses texts based on the text grammar of a specific text type and that extracts sentences and statements which are relevant for inclusion in the abstracts. The system employs knowledge of the discourse patterns that are typical of news stories. The results are encouraging and demonstrate the importance of discourse structures in text summarisation.

The purpose of this paper is to criticise the paper by Jennie A. Abrahamson and Victoria L. Rubin (2012) “Discourse structure differences in lay and professional health communication”, Journal of Documentation, Vol. 68 No. 6, pp. 826-851.

The author reviewed the antecedents of Rhetorical Structure Theory (RST) in discourse analysis, and paid close attention to the differences between the original formulation of RST, later formulations of the RST model and the application of RST in this paper. The author also reviewed the literature on physician-patient communication, and patient-patient support to contextualise the findings of Abrahamson and Rubin.

The paper shows evidence of over-simplification of RST since its initial formulation. Next, the Motivation relationship in the original Mann/Thompson formulation of RST appears problematic. This makes the authors’ RST findings that patient-patient (or consumer-consumer) information sharing appear to be more effective than physician-consumer information sharing rather tenuous. An important additional flaw is that there was only one physician participant in this study. A practical limitation to the study is that physicians mostly interact face-to-face with patients and use of consumer advice web sites may not fit well with the current practice of medicine.

The author had limited examples in the paper to examine how the authors had categorised the binary unit relationships.

RST is promising for discourse analysis of information advice web sites but simplifications in its application can lead to unwarranted claims.

The purpose of this paper is to respond to Urquhart and Urquhart’s critique of the previous work entitled “Discourse structure differences in lay and professional health communication”, published in this journal in 2012 (Vol. 68 No. 6, pp. 826-851, doi: 10.1108/00220411211277064).

The authors examine Urquhart and Urquhart’s critique and provide responses to their concerns and cautionary remarks against cross-disciplinary contributions. The authors reiterate the central claim.

The authors argue that Mann and Thompson’s (1987, 1988) Rhetorical Structure Theory (RST) offers valuable insights into computer-mediated health communication and deserves further discussion of its methodological strength and weaknesses for application in library and information science.

While the authors agree that some methodological limitations pointed out by Urquhart and Urquhart are valid, the authors take this opportunity to correct certain misunderstandings and misstatements.

The authors argue for continued use of innovative techniques borrowed from neighbouring disciplines, in spite of objections from the researchers accustomed to a familiar strand of literature. The authors encourage researchers to consider RST and other computational linguistics-based discourse analysis annotation frameworks that could provide the basis for integrated research, and eventual applications in information behaviour and information retrieval.

Many tools exist to chart the progress of an organisation in its quest to become a learning organization or achieve organizational learning. Aims to expand a tool already developed to include learning organization conditions as they occur through dialogue between individuals within an organisation with an emphasis on social learning theory.

Literature relating to creating learning organizations as well as undertaking organizational learning is reviewed and critiqued. An argument for a tool in identifying learning activity functions as they take place through dialogue is presented along with the argument for expanding the tool to incorporate learning organization conditions that have been identified within the literature. The tool this work expands is the DISCOUNT scheme as developed by Pilkington. The paper closes with a discussion on justifying the use of the scheme and the future work that is to be undertaken.

Demonstrates that a tool can be expanded to take into account learning organization and organizational learning conditions and how they could be identified.

Individuals who use the tool need a number of hours practice to become familiar with the scheme and its structure.

A tool has been expanded to look at learning activities as they take place within an organisation. By identifying these activities, more successful approaches to learning may be encouraged by looking at an individual's behaviour, personal and cognitive factors and the environment as is stated to apply when viewed through social learning theory.

This paper offers a practical tool that can be used on dialogue and other speech acts to look at learning activities within organizations with a specific focus on organizations wanting to improve organizational learning or try to create learning organizations.