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The purpose of this paper is to explore how linguistic style and message substance influence persuasion in civic crowdfunding marketplaces in which written narrative pitch become a vital communication to attract private contributions to public goods and services. Drawing on the elaboration likelihood model (ELM), the authors operationalize the linguistic style of the narrative pitch as language power and message substance as issue-relevant argument quality. In this paper, the authors examine how characteristics of both style and message are related to the outcome of civic crowdfunded projects.

The data on civic crowdfunding projects were retrieved from Spacehive, the platform that dedicated mainly to civic projects ranging from community programs, social-oriented enterprises, to infrastructure or facility development. Each of the narrative samples is analyzed using a computerized text analysis package called the Linguistic Inquiry and Word Count to extract the features of the linguistic style and message substance in the narratives. The logistic regression models are estimated to assess the impact of both linguistic style and message substance on crowdfunding decisions.

The results show that funding outcomes can be improved with psychological language dimensions (i.e. positive affective and perceptual language). However, extensive use of social language does not help project creators to increase their chance of funding performance; but instead, such language reduces the likelihood of project success. Additionally, message substance or issue-relevant information such as money and risk language influences funding outcome.

Very few empirical studies investigated the differential effects of language style and message substance on funding performance of crowdfunding campaigns. The authors draw upon the dual process of persuasion as a theoretical base to identify a comprehensive set of linguistic style and message substance and to examine the role of such features in an emerging civic crowdfunding market. This study advances the application of the dual process in ELM by identifying and examining distinct persuasive cues originating from linguistics styles and message contents.

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.

Understanding when an individual is being deceptive is an important part of police and criminal investigations. While investigators have developed multiple methods, the research literature has yet to fully explore some of the newer applied techniques. This study aims to investigate statement analysis, a recent approach in forensic linguistic analysis that has been applied to criminal investigations.

Real-world statements of individuals exposed as deceptive or truthful were used in the analyses. A behaviour sequence analysis approach is used to provide a timeline analysis of the individuals’ statements.

Results indicate that sequential patterns are different in deceptive statements compared to truthful statements. For example, deceptive statements were more likely to include vague words and temporal lacunas, to convince investigators into believing that the suspect was not present when the crime occurred. The sample in this research did not use one deceptive indicator, instead, electing to frequently change the order of deceptive indicators. Gaps in deception were also noted, and there was common repetition found in both the deceptive and truthful statements. While gaps are predicted to occur in truthful statements to reflect an absence of deception, gaps occurring in the deceptive statements are likely due to cognitive load.

The current research provides more support for using statement analysis in real-world criminal cases.

The purpose of this paper is to address the complexity of missing persons cases and highlight the linguistic differences that arise in this type of crime. Missing persons cases are typically very complex investigations. Without a body, crime scene forensics is not possible, and police are often left only with witness and suspect statements. Forensic linguistics methods may help investigators to prioritise or remove suspects. There are many competing approaches in forensic linguistic analysis; however, there is limited empirical research available on emerging methods.

This research investigates Statement Analysis, a recent development in linguistic analysis that has practical applications in criminal investigations. Real-world statements of individuals convicted of or found to be not guilty of their involvement in missing persons cases were used in the analyses. In addition, Behaviour Sequence Analysis was used to map the progressions of language in the suspects' statements.

Results indicated differences between the guilty and innocent individuals based on their language choices, for example, guilty suspects in missing [alive] cases were found more likely to use passive language and vague words because of high levels of cognitive load associated with the several types of guilty knowledge suspects in missing persons cases possess. Of particular interest is the use of untruthful words in the innocent suspects’ statements in missing [murdered] cases. While typically seen in deceptive statements, untruthful words in innocent statements may result because of false acquittals.

This research provides some support for Statement Analysis as a suitable approach to analysing linguistic statements in missing persons cases.

The study of deception and the theories, which have been developed have relied heavily on laboratory experiments in controlled environments, using American college students participating in mock scenarios. The purpose of this paper is to validate previous deception detection research in a real-world, high stakes environment where the unit of analysis is the question–response pair.

The study used previously confirmed linguistic and paralinguistic speech cues and the constructs of deception in an attempt to validate a leading deception theory, interpersonal deception theory (IDT). A combination of descriptive and predictive analysis was conducted to best understand the relationship between speech cues and changes in the subjects’ behavior.

The result validates IDT with mixed results on individual measures and their constructs. However, there is clear evidence across the 711 question-response pairs that not only was it possible to differentiate truth from deceptive behavior but also patterns of behavior can be seen over time.

Because of the real-world nature of the study, it is difficult to generalize the results to a larger population. However, one implication for future research is the development of methods to capture, process and prepare raw speech into data ready for analysis.

This paper attempts to fill the gap between the controlled mock scenarios and the harsh reality of real-world deception.

The purpose of this study is to investigate the effects of the innovativeness-related language of crowdfunding pitches on funding outcomes under different boundary conditions specified by two context-relevant signals, entrepreneurial passion and social endorsement.

This study develops six hypotheses about the focal impacts of innovativeness-related language (i.e. incremental and radical) and the moderating effects of entrepreneurial passion and social endorsement. The hypotheses are tested with a sample of 1,057 real projects collected from a typical platform with a computer-aided content analysis method.

This study finds that pitches containing more incremental innovativeness language can generate more funds and that those containing more radical innovativeness language can lead to less favorable funding outcomes. While incremental innovativeness language interacts with entrepreneurial passion language to positively affect funding outcomes, radical innovativeness language requires social endorsement to diminish its negative effect on funding outcomes.

This study demonstrates that the content of messages of entrepreneurial narratives does indeed drive funding success in the context of reward-based crowdfunding and confirms the relevance of the consumer perspective of reward-based crowdfunding by using a real dataset.

This work joins a number of entrepreneurial narrative studies investigating the impacts of the innovativeness-related language of pitches (issue-relevant content) and their interactions with informational signals (i.e. entrepreneurial passion and social endorsement) on funding outcomes in the context of reward-based crowdfunding.

This study aims to evaluate elements of corporate communication in online communities (OCs) and their influence on corporate impression formation. Interactive online platforms such as OCs are growing. Companies are discovering their importance and increasingly include OCs in their communication activities. The present study identifies the underlying components relevant to successful corporate communication in OCs, and further explore if and how online community members (OCMs) expect companies to communicate with them, explaining how corporate impressions are formed.

A qualitative research method was chosen, consisting of two stages. In stage one, 17 expert interviews with academics and practitioners were conducted, and in stage two, 12 OCMs were interviewed to clarify the concepts and gain new insights.

The study gains new knowledge relating to corporate communication in OCs and image formation. Specifically, the authors identify and confirm important key constructs in corporate impression formation in OCs, namely, relevance of messages, communication style, social context cues, affiliation, perceived similarity, source credibility and interpersonal communication. Furthermore, a conceptual model is proposed on the relationship between communication elements relevant in online communities and their influence on corporate impression.

The study helps to refine existing concepts of corporate impression formation in OCs. It is suggested that understanding how corporate impression is formed in OCs helps companies to participate in virtual networks, improving their corporate impression.

This study extends prior findings on word-of-mouth on the Internet (word-of-mouse) to demonstrate that communication among virtual community (VC) members can influence the image formation process, such that positive word-of-mouse has a positive effect on corporate image.

Contextual cues have become a hot research topic in the field of mobile consumer behavior, owing to the continuous rise of digital marketing. However, the complex online shopping scene makes it challenging to directly identify the association between the characteristics of contextual cues and consumer behavior. Presently, few studies have only systematically extracted and refined the types and characteristics of contextual cues. The purpose of this study is to explore the types and mechanisms of contextual cues in online shopping scenarios.

This study uses the word2vec algorithm, grounded theory and co-occurrence cluster method, along with online shopping word-of-mouth (WOM) text and consumer behavior theory, in order to explore different types of contextual cues and its efficiency from 5,619 comment corpus.

This study puts forward the following conclusions. (1) From the perspective of online shopping, contextual cues comprise aesthetic perception cues, value perception cues, trust-dependent cues, time perception cues, memory attention cues, spatial perception cues, attribute cues and relationship cues. (2) Based on the online shopping scenarios, contextual cues and their interaction effects exert an effect on consumer satisfaction, recommendation, purchase and return behavior.

The study conclusions are helpful to further reveal the deep association between contextual cues and consumer behavior in the process of online shopping, thus providing practical and theoretical enlightenment for enterprises to not only effectively reshape the scene but also promote the consumers' active purchase behavior.

Consumers often search for movie information and purchase tickets on the go. A synopsis is often provided by producers and theatres in mobile apps and websites. However, to the best of the authors’ knowledge, little research has investigated whether the synopsis has an impact on a movie’s box office. This research uses computerized text analysis in examining the influence of linguistic cues of a synopsis on the movie’s financial performance. This paper aims to show that language choice in a synopsis is a significant factor in predicting box office performance.

A total usable sample of 5973 movies was collected using a web crawler. Computerised text analysis using linguistic inquiry and word count was adopted to analyse the movie synopses data. The empirical study comprises two phases. Phase 1 used exploratory factor analysis on 50 per cent of the sample (Sample 1) to establish the dimensionality of psychological processes as reflected in the linguistic expressions. The analysis identified 11 linguistic variables that loaded on four dimensions. The factor structure was replicated on an independent sample (Sample 2) using confirmatory factor analysis. Phase 2 tested the hypotheses using structure equation modelling.

Results show that consistency between movie genres and linguistic cues in a film synopsis promotes movie box office revenue when linguistic cues shown in the synopsis confirm a consumer’s expectancies about a focal movie genre. Conversely, a synopsis reduces the movie box office revenue when the linguistic cues shown disconfirm the genre-based expectancies. These linguistic cues exert similar effects on action and crime films but different effects on comedies and drama films.

It is likely that consumer tastes and linguistic styles of film synopses have evolved over time. As a cross-sectional study, such changes were not taken into consideration in the current research. A longitudinal study in the future can reveal the dynamic relationship between film synopses and audience.

Managerially, the findings show that a synopsis is an effective communication touch point to position a movie. This research provides concrete guidelines in crafting synopses with the “rights words’ aligned with movie-goers’ expectations within each specific genre. Beyond movie consumption, the research findings can be applied to other entertainment products, such as TV series and books.

To our knowledge, this research is the first in studying the linguistic cues in synopses and its relation to box office performance. It addresses this knowledge gap by answering the basic question of whether movie synopses matter. Methodically, the paper marks the first attempt to use the two-step structural equation modelling method on computerised content analysis data.