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Given the socialisation of men and women to their gender roles and expression of emotion, this study aims to investigate whether there are gender differences in the use of emotive language in electronic word-of-mouth (eWOM), specifically in online reviews. The authors propose that female reviewers will use strong emotive terms, such as love, more frequently in online reviews than do male reviewers. The authors further propose that the gender of the reviewer influences audience responses to the reviewer’s use of emotive terms in online reviews.

The authors conducted secondary data analysis of restaurant reviews (Study 1) to provide evidence on whether the gender of the reviewer affects the frequency of use of emotive terms in an online review. In addition, three separate experiments (Studies 2–4) were conducted to test the theoretical arguments.

The results of the secondary data analysis indicated that female online reviewers used the term “love” much more frequently in their reviews than male reviewers, whereas there was no usage difference for the term “like”. The experimental studies further showed that an emotive review by a male reviewer containing the word “love” resulted in a higher evaluation of the restaurant being reviewed than a non-emotive review containing the word “like”. This difference was stronger when the overall rating was less salient and for consumers who believe (vs do not believe) that men and women use emotional language differently.

First, the paper extends our understanding of gender differences in emotional expression within the domain of eWOM and online reviews as well as our understanding of consumer responses to these gender differences. Second, the authors identify a boundary condition for these gender effects, namely, the overall rating score. Third, the authors find that consumer beliefs regarding gender stereotypes in emotional expression provide an explanation for these effects.

The results of the research indicate that the electronic algorithms operating on review sites might be modified in terms of their criteria for selecting the reviews to display to consumers, as consumer decision-makers may find greater utility in reviews written by male reviewers that contain strongly positive emotive terms.

The research extends the knowledge on gender differences in emotional expression in online reviews by demonstrating the actual usage patterns and differing responses to the emotional expressions of each gender.

This paper aims to examine the underlying motivations, attitudes and behaviors of exaggerated review posters and readers by examining the effect of review valence, emotional expression and language complexity on perceived poster, website and firm trustworthiness and subsequent behavioral intentions.

This research uses a mixed-method approach using the qualitative critical incident technique (CIT) and quantitative experimental design. Study 1 uses CIT to examine exaggerated online reviews from the poster perspective where Study 2 uses CIT to examine readers’ perceptions of exaggerated reviews. Study 3 conducts a between-subjects experimental design examining the impact of valence (positive vs negative) × emotion (low vs high) × language (vague vs detailed) on trustworthiness and behavior intention.

Results of the two qualitative studies (Study 1 and 2) find posters and readers use language complexity and emotions in exaggerated reviews. The results from the quantitative experimental design study (Study 3) find that language style and emotions influence customer perceptions of poster, website and firm trustworthiness, which also mediates the relationship between the qualitative aspects of review text on behavioral intentions.

The findings provide multiple practical implications on the prevalence of exaggerated online reviews and the importance of language and emotion in determining customer perceptions and behavioral intentions.

By focusing on both readers and posters in exaggerated eWOM, specific motivations, emotions and language, this research contributes to the literature of online reviews, customer misbehavior, trustworthiness, language use and value co-destruction in online environments.

This study develops a computational method to investigate the predominant language styles in political discussions on Twitter and their connections with users' online characteristics.

This study gathers a large Twitter dataset comprising political discussions across various topics from general users. It utilizes an unsupervised machine learning algorithm with pre-defined language features to detect language styles in political discussions on Twitter. Furthermore, it employs a multinomial model to explore the relationships between language styles and users' online characteristics.

Through the analysis of over 700,000 political tweets, this study identifies six language styles: mobilizing, self-expressive, argumentative, narrative, analytic and informational. Furthermore, by investigating the covariation between language styles and users' online characteristics, such as social connections, expressive desires and gender, this study reveals a preference for an informational style and an aversion to an argumentative style in political discussions. It also uncovers gender differences in language styles, with women being more likely to belong to the mobilizing group but less likely to belong to the analytic and informational groups.

This study provides insights into the psychological mechanisms and social statuses of users who adopt particular language styles. It assists political communicators in understanding their audience and tailoring their language to suit specific contexts and communication objectives.

This study reveals gender differences in language styles, suggesting that women may have a heightened desire for social support in political discussions. It highlights that traditional gender disparities in politics might persist in online public spaces.

This study develops a computational methodology by combining cluster analysis with pre-defined linguistic features to categorize language styles. This approach integrates statistical algorithms with communication and linguistic theories, providing researchers with an unsupervised method for analyzing textual data. It focuses on detecting language styles rather than topics or themes in the text, complementing widely used text classification methods such as topic modeling. Additionally, this study explores the associations between language styles and the online characteristics of social media users in a political context.

This research study aims to examine: whether preschoolers at risk form a homogenous or a heterogeneous group of high‐risk children; and in case preschoolers form a heterogeneous group, what are the distinctive characteristics of specific language impairment and mild intellectual disabilities groups in language acquisition and social competence that make differential early intervention necessary.

A total of 143 Greek preschoolers aged 4.5 through 5.5 participated in the study. Among them, according to DTLA‐P:3, 42 with mild intellectual disabilities and 41 with specific language impairments were detected. A total of 60 typically developed children were also detected. Children's categorization to the above groups was verified by the Λ‐α‐T‐ω Language Competence Test Level I, which was used to estimate intra‐individual differences in language competence. To assess peer relations, a peer relation checklist was developed and standardized.

The findings of this study support the approach of the two distinct groups of high‐risk preschoolers in terms of their language and social characteristics.

Research findings highlight the different educational needs of high‐risk preschoolers, which make necessary the differential use of preschool curricula.

The purpose of this paper is to describe linkages between the techniques of poetical expression and the language used by scholars to communicate management practice.

The approach is to consider the stylistic perspective of the language used for management theorising or research, viewing the documents produced by management researchers as communicating devices and cultural products which contribute to the creation or construction of the reality that they seek to describe and analyse.

The paper uncovers the poetic aspects buried – often deeply – in the language of management studies through which the concepts of, and ideas about, management are expressed.

The links between ways of saying usually considered to be in opposition are made known, and enjoyed.

This chapter describes how conversational computer agents have been used in collaborative problem-solving environments. These agent-based systems are designed to (a) assess the students’ knowledge, skills, actions, and various other psychological states on the basis of the students’ actions and the conversational interactions, (b) generate discourse moves that are sensitive to the psychological states and the problem states, and (c) advance a solution to the problem. We describe how this was accomplished in the Programme for International Student Assessment (PISA) for Collaborative Problem Solving (CPS) in 2015. In the PISA CPS 2015 assessment, a single human test taker (15-year-old student) interacts with one, two, or three agents that stage a series of assessment episodes. This chapter proposes that this PISA framework could be extended to accommodate more open-ended natural language interaction for those languages that have developed technologies for automated computational linguistics and discourse. Two examples support this suggestion, with associated relevant empirical support. First, there is AutoTutor, an agent that collaboratively helps the student answer difficult questions and solve problems. Second, there is CPS in the context of a multi-party simulation called Land Science in which the system tracks progress and knowledge states of small groups of 3–4 students. Human mentors or computer agents prompt them to perform actions and exchange open-ended chat in a collaborative learning and problem-solving environment.

The use of artificial intelligence (AI) in management research is still nascent and has primarily focused on content analyses of text data. Some method scholars have begun to discuss the potential benefits of far broader applications; however, these discussions have not led yet to a wave of corresponding AI applications by management researchers. This chapter explores the feasibility and the potential value of using AI for a very specific methodological task: the reliable and efficient capturing of higher-level psychological constructs in management research. It introduces the capturing of basic emotions and emotional authenticity of entrepreneurs based on their macro- and microfacial expressions during pitch presentations as an illustrative example of related AI opportunities and challenges. Thus, this chapter provides both motivation and guidance to management scholars for future applications of AI to advance management research.

This research presents and evaluates a method for assessing the entrepreneurial mindset (EM) of students in higher education.

The research considers EM a multi-variable psychological construct, which can be broken down into several conceptual sub-categories. Using data from a master course in entrepreneurship, the authors show how these categories can be applied to analyze students’ written reflections to identify linguistic markers of EM.

The research reports three main findings: analyzing student reflections is an appropriate method to explore the state and development of students’ EM; the theoretically-derived EM categories can be nuanced and extended with insight from contextualized empirical insights; and student reflections reveal counter-EM categories that represent challenges in the educator’s endeavor to foster students’ EM.

The commitment of resources to researching EM requires the dedication of efforts to develop methods for assessing the state and development of students’ EM. The framework can be applied to enhance the theoretical rigor and methodological transparency of studies of EM in entrepreneurship education.

The framework can be of value to educators who currently struggle to assess if and how their educational design fosters EM attributes.

This inquiry contributes to the critical research discussion about how to operationalize EM in entrepreneurship education studies. The operationalization of a psychological concept such as EM is highly important because a research focus cannot be maintained on something that cannot be studied in a meaningful way.

This chapter discusses of the role of Spanish as the language of instruction in a multilingual classroom with Erasmus students at the Faculty of Teacher Training of the University of Valencia (Spain). The author also examines the role that first languages play in multilingual classroom integration as they have little place in the school system.

The author also discusses the use of digital technology as a means of expression and defense of the linguistic rights of minority languages. In that respect, collective linguistic production and the use of different languages relates to the aim of preserving mother tongues in their original contexts.

The current study focuses on a key element: artistic productions using new technology are characterized as having great communicative value, and an important potential for social change, which can improve the linguistic attitude of minority language speakers toward their mother tongue and reinforce their awareness of participating in a process of collectively and interactively creating the final product. This is a highly important collaborative tool meant to help preserve and maintain one’s language and identity.

The chapter concludes that education through multilingual language learning and mobility remains an important means of supporting and sustaining the first languages of Erasmus students, the successful acquisition of Spanish as the official language of the host country, and the use of English as an additional language in order to help students gradually master curriculum content, while improving their linguistic skills and language proficiency.

The paper aims to present the results of the first two tasks of a user study looking into mental models of the bibliographic universe and especially their comparison to the Functional Requirements for Bibliographic Records (FRBR) conceptual model, which has not yet been user tested.

The paper employes a combination of techniques for eliciting mental models and consisted of three tasks, two of which, card sorting and concept mapping, are presented herein. Its participants were 30 individuals residing in the general area of Ljubljana, Slovenia.

Cumulative results of concept mapping show a strong resemblance to FRBR. Card sorts did not produce conclusive results. In both tasks, participants paid special attention to the original expression, indicating that a special place for it should be considered.

The study was performed using a relatively small sample of participants living in a geographically limited space using relatively straight‐forward examples.

Some solid evidence is provided for adoption of FRBR as the conceptual basis for cataloguing.

This is the first widely published user study of FRBR, applying novel methodological approaches in the field of Library and Information Science.