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This study aims to explore the role of the linguistic style used in the brand-posted social media content on consumer engagement in the Fintech domain.

A total of 3,286 tweets (registering nearly 1.35 million impressions) published by 10 leading Fintech unicorns in India were extracted using the Twitter API. The Linguistic Inquiry and Word Count (LIWC) dictionary was used to analyse the linguistic characteristics of the shared tweets. Negative Binomial Regression (NBR) was used for testing the hypotheses.

This study finds that using drive words and cognitive language increases consumer engagement with Fintech messages via the central route of information processing. Further, affective words and conversational language drive consumer engagement through the peripheral route of information processing.

The study extends the literature on brand engagement by unveiling the effect of linguistic features used to design social media messages.

The study provides guidance to social media marketers of Fintech brands regarding what content strategies best enhance consumer engagement. The linguistic style to improve online consumer engagement (OCE) is detailed.

The study’s findings contribute to the growing stream of Fintech literature by exploring the role of linguistic style on consumer engagement in social media communication. The study’s findings indicate the relevance of the dual processing mechanism of elaboration likelihood model (ELM) as an explanatory theory for evaluating consumer engagement with messages posted by Fintech brands.

Product presentation plays a critical role in influencing consumers’ purchasing decisions in online shopping. The purpose of this study is to examine the effects of text-image information on online product presentation pages on sales. This study also specifically explores the moderating role of celebrity endorsements in the relationship between text-image presentation information and sales.

This study is based on regression analysis using data sets from the largest online book retailer in China, Dangdang.com.

The results of this study show that there is an inverse U-shaped relationship between word count and book sales. Conversely, image quantity has a positive linear effect on book sales. Furthermore, celebrity endorsements moderate the relationship between word count and sales in two distinct ways. First, the positive effect of increasing word count from low to medium is enlarged by increasing the number of celebrity endorsers. Second, the turning point of the inverse-U relationship between word count and sales rank moves to the right as the number of endorsers increases.

To the best of the authors’ knowledge, this study is among the first to examine the effects of text-image quantity on sales across the full continuum. This study adds understanding on how information load might have distinct consequences on the processing performance of text and images. Furthermore, this study investigates how sales are impacted by the quantity of celebrity endorsers in relation to textual and pictorial information in online shopping contexts, extending our knowledge of the effectiveness of celebrity endorsements.

Advanced big data analysis and machine learning methods are concurrently used to unleash the value of the data generated by government hotline and help devise intelligent applications including automated process management, standard construction and more accurate dispatched orders to build high-quality government service platforms as more widely data-driven methods are in the process.

In this study, based on the influence of the record specifications of texts related to work orders generated by the government hotline, machine learning tools are implemented and compared to optimize classify dispatching tasks by performing exploratory studies on the hotline work order text, including linguistics analysis of text feature processing, new word discovery, text clustering and text classification.

The complexity of the content of the work order is reduced by applying more standardized writing specifications based on combining text grammar numerical features. So, order dispatch success prediction accuracy rate reaches 89.6 per cent after running the LSTM model.

The proposed method can help improve the current dispatching processes run by the government hotline, better guide staff to standardize the writing format of work orders, improve the accuracy of order dispatching and provide innovative support to the current mechanism.

Distinguishing phishing emails from legitimate emails continues to be a difficult task for most individuals. This study aims to investigate the psycholinguistic factors associated with deception in phishing email text and their effect on end-user ability to discriminate phishing emails from legitimate emails.

Email messages and end-user decisions collected from a laboratory phishing study were validated and analyzed using natural language processing methods (Linguistic Inquiry Word Count) and penalized regression models (LASSO and Elastic Net) to determine the linguistic dimensions that attackers may use in phishing emails to deceive end-users and measure the impact of such choices on end-user susceptibility to phishing.

We found that most participants, who played the role of a phisher in the study, chose to deceive their end-user targets by pretending to be a familiar individual and presenting time pressure or deadlines. Results show that use of words conveying certainty (e.g. always, never) and work-related features in the phishing messages predicted higher end-user vulnerability. On the contrary, use of words that convey achievement (e.g. earn, win) or reward (cash, money) in the phishing messages predicted lower end-user vulnerability because such features are usually observed in scam-like messages.

Insights from this research show that analyzing emails for psycholinguistic features associated with computer-mediated deception could be used to fine-tune and improve spam and phishing detection technologies. This research also informs the kinds of phishing attacks that must be prioritized in antiphishing training programs.

Applying natural language processing and statistical modeling methods to analyze results from a laboratory phishing experiment to understand deception from both attacker and end-user is novel. Furthermore, results from this work advance our understanding of the linguistic factors associated with deception in phishing email text and its impact on end-user susceptibility.

Given the popularity of online health communities (OHCs) and medical question-and-answer (Q&A) services, it is increasingly important to understand what constitutes useful answers and user-adopted standards in healthcare domain. However, few studies provide insights into how health information characteristics, provider characteristics and recipient characteristics jointly influence user information adoption decisions. To fill this research gap, this study examines the combined effects of physicians' certainty tone as information characteristics, seniority as provider characteristics and disease severity as recipient characteristics on patients' health information adoption.

Drawing on dual-process theory and information adoption model, an extended information adoption model is established in this study to examine the effect of attitude certainty on patients' health information adoption, and the moderating effects of online seniority and offline seniority, as well as patient motivation level—disease severity. Utilizing logit regression models, the authors empirically tested the hypotheses based on 4,224 Q&A records from a popular Chinese OHC.

The results show that (1) attitude certainty has a significant positive impact on patients' health information adoption, (2) the relationship between attitude certainty and information adoption is negatively moderated by physicians' online seniority, but is positively moderated by offline seniority; (3) there is a negative three-way interaction effect of attitude certainty, online seniority and disease severity on patients' health information adoption.

This study extends the information adoption model to examine the two-way interaction between argument quality and source reliability, as well as the three-way interaction with user motivation level, especially for health information adoption in the healthcare field. These findings also provide direct practical applications for knowledge contributors and OHCs.

Hair loss is often overlooked but psychologically challenging. However, the emergence of online health communities provides opportunities for hair loss patients to seek social support through self-disclosure. Nevertheless, not all disclosures receive the desired support. This research explores what patients disclose within the community and how their health narrative (content, form and linguistic style) regarding self-disclosure influences the social support they receive.

This study investigated a 13-year-old online support group for Chinese hair loss patients with nearly 240,000 members. Using structural topic modeling, Linguistic Inquiry and Word Count, and a negative binomial model, the research analyzed the content of self-disclosure and the interrelationships between social support and three narrative dimensions of self-disclosure.

Self-disclosures are classified into 14 topics, grouped under analytical, informative and emotional categories. Emotion-related self-disclosures, whether in content or effective word use, receive deeper social support. Longer and image-rich posts attract more support in quantity, but not necessarily in quality, while cognitive words have a limited impact.

This study addresses the previously overlooked population of hair loss patients within online health communities. It employs a more comprehensive health narrative framework to explore the relationship between self-disclosure and social support, utilizing unsupervised structural topic modeling methods to mine text. The research offers practical implications for how patients seek support and for healthcare professionals in developing doctor-patient communication strategies.

This study investigates the key factors that influence customer satisfaction when interacting with augmented reality shopping assistance applications (ARSAPs). ARSAPs grant consumers the capability to experience products in a virtually simulated user environment before product acquisition. With the development of mobile e-commerce due to breakthroughs in smartphone and augmented reality (AR) technologies, there is an increasing potential for these emergent AR mobile services, yet there is a need for further improvement.

This study initially explored the key satisfaction factors for ARSAPs by utilizing topic modeling of a collection of actual user reviews. These factors are subsequently revisited and complemented by existing literature, and finally verified through logistic regression analysis supported by sentiment analysis.

This study identified the key factors that influence customer satisfaction with ARSAPs, including visuality, sense of reality, credibility, format, completeness, understandability, relevance, flexibility, response time, reliability, availability, ease of use and privacy. In particular, two additional factors (i.e. visuality and sense of reality) were newly identified as important in the context of AR, despite their previous omissions in existing literature.

This study is the first to investigate the key factors that influence customer satisfaction with ARSAPs from users' perspectives, utilizing topic modeling of a large amount of real-world data on actual user feedback. By identifying new factors (i.e. visuality and sense of reality) that were not identified in previous literature, this study provides important academic implications for a broader understanding of AR and related technologies that are essential elements of the metaverse. This study also provides valuable insights for developers and companies in the e-commerce industry on how to optimize AR applications and develop more targeted and effective marketing strategies in this field.

The purpose of this study is to examine the relationship between explanatory language, audit fees and audit hours to demonstrate that auditors use explanatory language in audit reports to explain perceived audit risk.

The authors construct the sentiment value, a novel audit risk proxy derived from audit reports, using big data analysis. The relationship between sentiment value and explanatory language is then investigated. The authors present the validity of their new metric by examining the relationship between sentiment value and accounting quality, taking audit fees and hours into account.

The authors first find that reporting explanatory language is positively related to audit fees. More importantly, the authors provide an evidence that explanatory language in audit reports is indicative of increased audit risk as it is negatively correlated with sentiment value. As a positive (negative) sentimental value means that the audit risk is low (high), the results indicate that auditors describe explanatory language in a negative manner to convey the inherent audit risk and receive higher audit fees from the risky clients. Furthermore, the relationship is strengthened when the explanatory language is more severe, such as reporting the multiple numbers of explanatory language or going-concern opinion. Finally, the sentiment value is correlated with accounting quality, as measured by the absolute value of discretionary accruals.

Contrary to previous research, the authors’ findings suggest that auditors disclose audit risks of client firms by including explanatory language in audit reports. In addition, the authors demonstrate that their new metric effectively identifies the audit risk outlined qualitatively in audit report. To the best of the authors’ knowledge, this is the first study that establishes a connection between sentiment analysis and audit-related textual data.

The objective of the study is to identify both reasons for ignoring and for paying attention to the country of origin (COO) by consumers when choosing brands of durable goods.

In this paper a qualitative approach was applied, i.e. 25 in-depth semistructured interviews with Polish consumers of durable goods purposively selected out of those who had previously participated in a quantitative survey conducted by the authors.

Among the reasons for paying attention to the COO when choosing brands of durable goods, cognitive (rational), affective (emotional) and normative factors have been identified, while among the reasons for ignoring the COO by consumers, the authors identified only cognitive (rational) and affective (emotional) factors.

The conclusions can be applied by brand managers, e.g. when making decisions whether and why to communicate COO dimensions.

This paper contributes to the international marketing literature as it develops a deeper insight into consumer behavior with reference to the consumers’ reasons for paying attention to and ignoring the COO, with very little published on the latter in particular. Furthermore, it is one of still relatively few qualitative studies conducted so far on COO taking a perspective of a consumer, especially the one from an emerging market from the European Union (EU).

This study aims to address the question of what coordination mechanism can be used for cultural production and, in particular, for the governance of music culture production. The authors locate their reflection within the specific institutional innovations introduced in Italy in 2017, focusing on the idea of shared administration and the public–private collaboration instituted in Trentino (a province located in northern Italy) in support of its cultural policy.

This study focusses on the Trentino’s music school system. This includes 13 organisations (musicians’ cooperatives as well as associations of musicians and students, plus one municipal school which do not overlap with the public school system). To analyse shared administration features, the authors rely on selected information from 50 interviews with Trentino Music Schools (TMS) teachers and administrators, and on the proceedings of the 1994 music school conference organised by the schools at the time when this novel educational system was created.

To offer an innovative educational service, the public actor (Provincia Autonoma di Trento [PAT]) and the schools (TMS) have developed a strong interdependence at the different levels of decision-making: PAT needs organisations that are sufficiently structured and organised to respect requirements of transparency and accountability, as well as educational standards, whereas TMS need public funding to maintain their service accessible for users, good labour conditions and be financially sustainable. Likewise, the success of TMS in educating thousands of students every year, including additional teaching programmes funded by PAT within general public schools, has contributed to decrease the exclusion from music education, raise interest in young people for music and fed enrolment in TMS as well as in the public schools related to the conservatoire filière. Conclusions emphasise the existence of a polycentric system of music culture production which needs to acknowledge the risk of being trapped in a static disequilibrium, while recognising change and the need to support and promote a culture of cooperation among schools and across layered institutional levels over time.

Further research can observe this system of cultural production over time, to appreciate changes and organisational tranformations, while introducing comparative analysis with other systems in different regions.

The relationship between the public and private sectors to design, organise and manage activities of collective interest (in the social, cultural, sporting and other fields) can increasingly become an effective and efficient alternative to the traditional bureaucratic as well as to the competitive method. For this to happen, however, all actors involved must be aware not only of areas of efficiency but also of inefficiency. To remedy the latter, corrective measures will have to be introduced. For example, fostering and improving “co-programmazione” and “co-progettazione” means giving all stakeholders involved the opportunity to actively participate. Should the number of participants increase, more discussion fora could be set up because one alone may not be sufficient to foster maximum involvement, to enhance different points of view, to allow for intersectoral and multidisciplinary interpretations and responses.

The system governance based on co-programming and co-design has allowed – despite limitations – to pursue educational purposes and thus well-being for the users, as well as for the teachers and the community as a whole. The continuity of this educational and cultural action has been guaranteed by the economic and financial sustainability of the schools, which is highly dependent on the public actor funding personnel costs, and in turn tied to the number of students (demand) attending each school. Actors embedded in the system need to build awareness of industry and cultural changes and knowledge of how to introduce more adaptive capacity. This points towards the need for strengthening networking capacity and collaboration among schools and other relevant stakeholders.

The case presented is a unique system of music culture production in Italy, and its governance has never been addressed by previous studies. It provides an application of shared administration to which public administrations and communities can learn to improve access to music culture and education. For public and private organisations to take advantage of the method of “co-programmazione” and “co-progettazione”, to make the production of a meritorious good more efficient and to favour its maximum accessibility, this study considers the strengths and weaknesses of this approach, or the areas of efficiency and inefficiency, for which new measures will have to be introduced.