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The purpose of this paper is to treat disinformation and misinformation (intentionally deceptive and unintentionally inaccurate misleading information, respectively) as a socio-cultural technology-enabled epidemic in digital news, propagated via social media.

The proposed disinformation and misinformation triangle is a conceptual model that identifies the three minimal causal factors occurring simultaneously to facilitate the spread of the epidemic at the societal level.

Following the epidemiological disease triangle model, the three interacting causal factors are translated into the digital news context: the virulent pathogens are falsifications, clickbait, satirical “fakes” and other deceptive or misleading news content; the susceptible hosts are information-overloaded, time-pressed news readers lacking media literacy skills; and the conducive environments are polluted poorly regulated social media platforms that propagate and encourage the spread of various “fakes.”

The three types of interventions – automation, education and regulation – are proposed as a set of holistic measures to reveal, and potentially control, predict and prevent further proliferation of the epidemic. Partial automated solutions with natural language processing, machine learning and various automated detection techniques are currently available, as exemplified here briefly. Automated solutions assist (but not replace) human judgments about whether news is truthful and credible. Information literacy efforts require further in-depth understanding of the phenomenon and interdisciplinary collaboration outside of the traditional library and information science, incorporating media studies, journalism, interpersonal psychology and communication perspectives.

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.

Though not new to online gamers, griefing – an act of play intended to cause grief to game players – is fairly understudied in LIS scholarship. The purpose of this paper is to expand the inventory of griefing varieties, consider their deceptive elements and examine attitudes towards the phenomenon.

The authors collected and content analysed 80 (non‐elicited) posts from the Something Awful forum thread and compared them to the results of ten (elicited) e‐mail interviews.

As a complex phenomenon, griefing has multiple interpretations and opposing attitudes. The thread results show that griefers, as perpetrators, have predominantly positive or neutral attitudes towards the act. About 15 per cent of the examined griefers reportedly resort to deceptive techniques. More extravagant griefs that require verbal interactions in player‐versus‐player (PvP) online games involve deception and often fall into two categories: scamming or greed play (prioritising personal benefits). The authors found self‐reported instances of deception by scheming, luring, entrapment, pretence and verbal concealment in griefing acts. The interview respondents, as predominantly victims of griefs, do not think of griefing (or may not be aware of it) as an act of deception and primarily associate it with harassment (inciting emotional reactions) or power imposition (exerting superiority). Casual griefing – refusing to comply with the rules for mere entertainment – stands out as another griefing variety.

With the growth of popularity of video gaming, libraries are largely unaware of griefing and should be prepared to address it in video game use policies for online gaming units or tournaments. Online gaming affords a unique opportunity to examine deception in computer‐mediated human‐to‐human communication. The complexity of the phenomenon and associated opposing views are offered here to be weighted by the LIS scholars and professionals.

The main purpose of our study is to analyze the influence of Artificial Intelligence (AI) on firm performance, notably by building on the business value of AI-based transformation projects. This study was conducted using a four-step sequential approach: (1) analysis of AI and AI concepts/technologies; (2) in-depth exploration of case studies from a great number of industrial sectors; (3) data collection from the databases (websites) of AI-based solution providers; and (4) a review of AI literature to identify their impact on the performance of organizations while highlighting the business value of AI-enabled projects transformation within organizations.

This study has called on the theory of IT capabilities to seize the influence of AI business value on firm performance (at the organizational and process levels). The research process (responding to the research question, making discussions, interpretations and comparisons, and formulating recommendations) was based on a review of 500 case studies from IBM, AWS, Cloudera, Nvidia, Conversica, Universal Robots websites, etc. Studying the influence of AI on the performance of organizations, and more specifically, of the business value of such organizations’ AI-enabled transformation projects, required us to make an archival data analysis following the three steps, namely the conceptual phase, the refinement and development phase, and the assessment phase.

AI covers a wide range of technologies, including machine translation, chatbots and self-learning algorithms, all of which can allow individuals to better understand their environment and act accordingly. Organizations have been adopting AI technological innovations with a view to adapting to or disrupting their ecosystem while developing and optimizing their strategic and competitive advantages. AI fully expresses its potential through its ability to optimize existing processes and improve automation, information and transformation effects, but also to detect, predict and interact with humans. Thus, the results of our study have highlighted such AI benefits in organizations, and more specifically, its ability to improve on performance at both the organizational (financial, marketing and administrative) and process levels. By building on these AI attributes, organizations can, therefore, enhance the business value of their transformed projects. The same results also showed that organizations achieve performance through AI capabilities only when they use their features/technologies to reconfigure their processes.

AI obviously influences the way businesses are done today. Therefore, practitioners and researchers need to consider AI as a valuable support or even a pilot for a new business model. For the purpose of our study, we adopted a research framework geared toward a more inclusive and comprehensive approach so as to better account for the intangible benefits of AI within organizations. In terms of interest, this study nurtures a scientific interest, which aims at proposing a model for analyzing the influence of AI on the performance of organizations, and at the same time, filling the associated gap in the literature. As for the managerial interest, our study aims to provide managers with elements to be reconfigured or added in order to take advantage of the full benefits of AI, and therefore improve organizations’ performance, the profitability of their investments in AI transformation projects, and some competitive advantage. This study also allows managers to consider AI not as a single technology but as a set/combination of several different configurations of IT in the various company’s business areas because multiple key elements must be brought together to ensure the success of AI: data, talent mix, domain knowledge, key decisions, external partnerships and scalable infrastructure.

This article analyses case studies on the reuse of secondary data from AI deployment reports in organizations. The transformation of projects based on the use of AI focuses mainly on business process innovations and indirectly on those occurring at the organizational level. Thus, 500 case studies are being examined to provide significant and tangible evidence about the business value of AI-based projects and the impact of AI on firm performance. More specifically, this article, through these case studies, exposes the influence of AI at both the organizational and process performance levels, while considering it not as a single technology but as a set/combination of the several different configurations of IT in various industries.

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.

Conversational agents are natural language interaction interfaces designed to simulate conversation with a real person. This paper seeks to investigate current development and applications of these systems worldwide, while focusing on their availability in Canadian libraries. It aims to argue that it is both timely and conceivable for Canadian libraries to consider adopting conversational agents to enhance – not replace – face‐to‐face human interaction. Potential users include library web site tour guides, automated virtual reference and readers' advisory librarians, and virtual story‐tellers. To provide background and justification for this argument, the paper seeks to review agents from classic implementations to state‐of‐the‐art prototypes: how they interact with users, produce language, and control conversational behaviors.

The web sites of the 20 largest Canadian libraries were surveyed to assess the extent to which specific language‐related technologies are offered in Canada, including conversational agents. An exemplified taxonomy of four pragmatic purposes that conversational agents currently serve outside libraries – educational, informational, assistive, and socially interactive – is proposed and translated into library settings.

As of early 2010, artificially intelligent conversational systems have been found to be virtually non‐existent in Canadian libraries, while other innovative technologies proliferate (e.g. social media tools). These findings motivate the need for a broader awareness and discussion within the LIS community of these systems' applicability and potential for library purposes.

This paper is intended for reflective information professionals who seek a greater understanding of the issues related to adopting conversational agents in libraries, as this topic is scarcely covered in the LIS literature. The pros and cons are discussed, and insights offered into perceptions of intelligence (artificial or not) as well as the fundamentally social nature of human‐computer interaction.

To maximize their effectiveness, exit interviews should incorporate employee voice and be aligned with other HR processes. The purpose of this paper is to describe a three-step approach to the strategic use of exit interviews.

The current study synthesizes extant theory including that of employee voice to enhance the exit interview process. A qualitative study conducted within a large marketing research organization demonstrates how exit interviews that utilize employee voice can inform HR and organizational strategy.

Application of the proposed process to the case study revealed conditions, critical incidents, and cognitive processes underlying exit decisions for employees in several job categories. Qualitative exit information is used to describe corresponding employee withdrawal paths.

Use of the three-step exit interview process is expected to enhance HR decisions. Data gathered from the three-step process can be used by HR and organizational leaders to develop action plans as well as inform an organization’s strategic decisions.

An organizational example is presented in which insight into underlying causes of voluntary turnover are discovered through exit interviews. Exit interview information suggested interventions related to HR processes. Such targeted insights from exit interviews can greatly improve retention and enhance organizational effectiveness.

In the age of social media, when publishers are vying for consumer attention, click-baits have become very common. Not only viral websites but also mainstream publishers, such as news channels, use click-baits for generating traffic. Therefore, click-bait detection and prediction of click-bait virality have become important challenges for social media platforms to keep the platform click-bait free and give a better user experience. The purpose of this study is to try exploring how the contents of the social media posts and the article can be used to explain and predict social media posts and the virality of a click-bait.

This study has used 17,745 tweets from Twitter with 4,370 click-baits from top 27 publishers and applied econometric along with machine learning methods to explain and predict click-baitiness and click-bait virality.

This study finds that language formality, readability, sentiment scores and proper noun usage of social media posts and various parts of the target article plays differential and important roles in click-baitiness and click-bait virality.

The paper contributes toward the literature of dark behavior in social media at large and click-bait prediction and explanation in particular. It focuses on the differential roles of the social media post, the article shared and the source in explaining click-baitiness and click-bait virality via psycho-linguistic framework. The paper also provides explanability to the econometric and machine learning predictive models, thus performing methodological contribution too.

The paper helps social media managers create a mechanism to detect click-baits and also predict which ones of them can become viral so that corrective measures can be taken.

To the best of the authors’ knowledge, this is one of the first papers which focus on both explaining and predicting click-baitiness and click-bait virality.