Content Cues Research Articles

What Constitutes a Helpful Health-Related Answer?

Given the unwieldy glut of information in online health question-answer (Q&A) service, it is essential to understand what constitutes helpful answers in the medical domain. Despite the fact that studies have examined the impacts of answer content factors on answer helpfulness, there are two gaps that need further analysis. First, the empirical results of the existing relevant studies on the effect of answer emotion are inconsistent. Second, prior studies only have examined the independent impacts of answer content factors and question content cues on answer helpfulness. To fill this gap, a research model reflecting the impacts of emotional content and question-answer congruence on answer helpfulness was developed and empirically examined. Our empirical analyses confirm that emotional content and answer helpfulness are related to one another in the form of an inverted U-shape and indicate that two types of question-answer congruence (emotional intensity congruence and linguistic style matching) positively affect answer helpfulness. Theoretical and practical implications are discussed.

FontDiffuser: One-Shot Font Generation via Denoising Diffusion with Multi-Scale Content Aggregation and Style Contrastive Learning

Automatic font generation is an imitation task, which aims to create a font library that mimics the style of reference images while preserving the content from source images. Although existing font generation methods have achieved satisfactory performance, they still struggle with complex characters and large style variations. To address these issues, we propose FontDiffuser, a diffusion-based image-to-image one-shot font generation method, which innovatively models the font imitation task as a noise-to-denoise paradigm. In our method, we introduce a Multi-scale Content Aggregation (MCA) block, which effectively combines global and local content cues across different scales, leading to enhanced preservation of intricate strokes of complex characters. Moreover, to better manage the large variations in style transfer, we propose a Style Contrastive Refinement (SCR) module, which is a novel structure for style representation learning. It utilizes a style extractor to disentangle styles from images, subsequently supervising the diffusion model via a meticulously designed style contrastive loss. Extensive experiments demonstrate FontDiffuser's state-of-the-art performance in generating diverse characters and styles. It consistently excels on complex characters and large style changes compared to previous methods. The code is available at https://github.com/yeungchenwa/FontDiffuser.

News bias perceptions as impacted by source cues, content cues, and media bias ratings

ABSTRACT Using three experimental studies, this research considers whether exposure to source cues, content cues, and media bias ratings impacts perceptions of ideological bias in news stories. As a possible news media literacy intervention strategy, viewing a media bias ratings chart after reading a news story had limited influence on assessments of bias. Source cues consistently influenced bias perceptions. Study 1 and Study 2 revealed evidence of the relative hostile media perception, where Republicans and Democrats perceived the news stories as biased in the same direction but to a significantly different degree. This finding did not replicate in Study 3, where content cues were held constant. Thus, content cues, alongside source cues, appear necessary in facilitating the relative hostile media perception.

Millennia of legal content criteria of lies and truths: wisdom or common-sense folly?

Long before experimental psychology, religious writers, orators, and playwrights described examples of lie detection based on the verbal content of statements. Legal scholars collected evidence from individual cases and systematized them as "rules of evidence". Some of these resemble content cues used in contemporary research, while others point to working hypotheses worth exploring. To examine their potential validity, we re-analyzed data from a quasi-experimental study of 95 perjury cases. The outcomes support the fruitfulness of this approach. Travelling back in time searching for testable ideas about content cues to truth and deception may be worthwhile.

Does it help to provide such posting content for interaction? An empirical study of physical and virtual goods branding

<p>The purpose of this study was to analyze several brands offering physical and virtual products to determine differences in content marketing, as well as the impact of content cues on brand awareness. An analytical framework examining the relationship between content messaging, cues, and positioning was also developed to investigate social media marketing and brand positioning. The study combines big data techniques, artificial intelligence and machine learning applications, data exploration, disambiguation, and model prediction techniques to observe public behavior and preferences. This study was intended to highlight the importance of functional cues (message recognition) and symbolic cues (positive emotional response) in brand communication, and the findings suggest that brands on social media platforms can use relevant messaging to stimulate brand awareness and facilitate user interaction. In summary, this study contributes to an understanding of key messaging characteristics of branding on social media, explores the differences in user behavior across brands, and documents the impact of cues on user engagement. The results demonstrate that advanced data analysis techniques can be used to extract representative keywords and determine their impact on brand interactions in the context of physical and virtual products. </p> <p> </p>

Catching eyes of social media wanderers: How pictorial and textual cues in visitor-generated content shape users’ cognitive-affective psychology

Documenting and sharing individual museum visits flourishes on social media. However, little research exists about how peer-generated content cues shape prospective visitors' perceptions and decisions. Drawing upon the stimulus‒organism‒response (SOR) framework, we holistically investigated the visual weight and attitudinal feedback of exhibition selfies and caption appeal types via eye-tracking technology and interviews, as well as the persuasive execution of accompanying texts using an experimental method. Two sequential studies were conducted: Study 1 empirically investigated the superiority of selfies and emotional titles in attracting visual attention and their influence on viewers' attitudinal evaluations through aesthetic judgments, mental imagery and flow experience during visual processing; Study 2 differentiated two types of textual stimuli (informational self-disclosure and emotional self-disclosure) that indirectly influence viewers’ behavioral intention through their inner organism changes in aesthetic experience and trust. The findings provide theoretical and marketing insights for tourism and cultural organizations to promote their social media communication.

Communicating Stigma About Invisible Illness: U.S. Military Veterans’ Descriptions of Stigma Communication About Posttraumatic Stress

ABSTRACT Due to mental illness stigma, veterans experiencing posttraumatic stress (PTS) may attempt to cope without seeking professional treatment. This can lead to detrimental consequences, including substance abuse, depression, and suicide. In an attempt to learn more about the stigma surrounding military-related PTS, this study used interviews to explore how veterans with PTS describe stigma communication in two different contexts: within the military organization and from members of society. All four of Smith’s (2007) model of stigma communication content cues (labels, marks, personal responsibility, and social peril) were present when veterans described military stigma about veterans experiencing PTS. Three content cues (labels, marks, and social peril) were present when veterans described public stigma surrounding veterans experiencing PTS. Theoretically, this study presents unique experiences related to how stigma is communicated about individuals experiencing an invisible illness, or what Goffman (1963) describes as “discreditable” individuals. Practically, the results can aid in developing destigmatizing campaigns and interventions.

Neural representations of the content and production of human vocalization

Speech, as the spoken form of language, is fundamental for human communication. The phenomenon of covert inner speech implies functional independence of speech content and motor production. However, it remains unclear how a flexible mapping between speech content and production is achieved on the neural level. To address this, we recorded magnetoencephalography in humans performing a rule-based vocalization task. On each trial, vocalization content (one of two vowels) and production form (overt or covert) were instructed independently. Using multivariate pattern analysis, we found robust neural information about vocalization content and production, mostly originating from speech areas of the left hemisphere. Production signals dynamically transformed upon presentation of the content cue, whereas content signals remained largely stable throughout the trial. In sum, our results show dissociable neural representations of vocalization content and production in the human brain and provide insights into the neural dynamics underlying human vocalization.

Impact of Content, Context and Creator on User Engagement on Instagram

Social media marketing is a powerful tool for businesses to grow their customer base and increase sales. However, the lack of an effective strategy can lead to low engagement rates, which in turn means less opportunity for growth. This paper aims to address why this happens and what you can do about it. This study aims to find out what exactly drives user engagement when it comes to content cues, context cues, and creators. In this paper, we will report on a study that will analyze the textual and visual content while also taking into account the creator and context variables, to find out what exactly drives user engagement. The results of our research will help marketers to understand what exactly drives user engagement and what they should keep in mind moving forward.

Call for Papers: Media and Moral Understanding

Call for Papers: Media and Moral Understanding

Disclosure, content cues, emotions and behavioural engagement in social media influencer marketing: an exploratory multi-stakeholder perspective

ABSTRACT Influencer marketing involves multiple stakeholders. Research, however, has predominately explored key influencer marketing concepts, such as disclosure for native advertising from a consumer perspective. In addition, a review of the literature identifies other factors such as content cues and emotions, which may be important in providing a comprehensive understanding of influencer marketing. To address these gaps, this research adopted an exploratory research design using convergent interviews with the three key stakeholder groups consumers, influencers and brands. The findings reveal that beyond disclosure, other content cues within influencer marketing can contribute to advertising recognition. Further, from the perspective of brands, influencers are perceived to have unique credibility attributes relating to expertise on social media platforms and product categories. Emotional responses in influencer marketing are also shown to be predominately positive and directed towards influencers rather than brands, with potential for this to be transferred to the brand through emotional contagion.

User information processing mechanisms for news quality judgment conformity to professional standards: Comparing combinations of news content/formal cue processing

It is more difficult to judge news quality on digital news platforms because editorial cues (such as size and placement of news articles that signal the quality of articles in the traditional news environment) are far less obvious. Without these editorial cues, how do users process news cues to judge news quality in conformity to professional standards? Relying on dual information processing literature, this study investigates five combinations of news content/formal cue processing to identify user information processing mechanisms for news quality judgment conformity to professional standards. A total of 88 news articles were evaluated by 3547 survey respondents and two professional editors. Based on the partial-least-squares structural equation modeling, we found that the joint functioning of content/formal cue processing better explains news quality judgment conformity than other combinations (such as the independent functioning of each cue processing and the biased functioning of content cue processing affected by formal cue processing). The large, negative effect of joint functioning suggests that the less the respondents relied on formal cues, the greater they achieved news quality judgment conformity as they elaborated more on content cues. Elaboration on a given article’s believability/depth as a content cue and heuristics regarding its number of quotes as a formal cue had greater impact on judgment conformity. These results imply how the elaborative and heuristic routes of news processing interact and in what ways news cues can be processed to identify quality news which is necessary for democratic decision making.

Evaluation of Web-Based Health Information From the Perspective of Women With Eating Disorders: Thematic Analysis.

BackgroundUsers with experience of eating disorders use the internet as a source of information, whether for prorecovery activities (such as web-based treatment, looking for information, support, and sharing) or activities that promote eating disorder behavior as a desirable lifestyle choice (such as pro–eating disorder communities and reading and creating pro–eating disorder posts). Their assessment of web-based eating disorder–related information is crucial for understanding the context of the illness and for health professionals and their web-based interventions.ObjectiveThis study aimed to understand the criteria young women with the experience of eating disorders use in evaluating eating disorder–related web-based information and what eating disorder–related characteristics of these women are involved in their evaluation.MethodsWe analyzed 30 semistructured individual interviews with Czech women aged 16 to 28 years with past or present eating disorder experience using a qualitative approach. Thematic analysis was adopted as an analytical tool.ResultsThe specifics of eating disorder phases (the disorder stage and the treatment process) emerged as important aspects in the process of information assessment. Other specific characteristics of respondents (eg, motivation, abilities, and resources) addressed how the respondents arrived at certain web-based information and how they evaluated it. In addition, the respondents described some content cues as features of information (eg, novelty and social information pooling). Another finding is that other users’ attitudes, experiences, activities, and personal features are involved in the information evaluation of these users and the information presented by them. Finally, the respondents evaluated the websites’ visual look and graphic components.ConclusionsThis study shows that web-based information evaluation reported by women with experience of eating disorders is a complex process. The assessment is influenced by current personal characteristics related to the illness (mainly the motivation for maintaining or curing the eating disorder) using cues associated with information content, other users, and website look. The study findings have important implications for health professionals, who should ask their clients questions about web-based communities and their needs to understand what information and sources they choose.

Generating destination brand awareness and image through the firm's social media

PurposeThe role of social media in the tourism industry growth cannot be ignored, because today the internet and social media platforms are one of the most popular information channels used by potential tourists and have become one of the main sources of online travel information. This study investigates the role of content cues of tourism information quality provided in Elie Gasht firm's Instagram page on enhancing awareness of the destination brand and forming users' destination image.Design/methodology/approachA quantitative research design was used to validate the hypotheses proposed in this research. A survey was deployed using the convenience method among 187 users of Elie Gesht's Instagram page to test the theoretical model. The structural relationships in the research were examined using the partial least squares structural equation modeling.FindingsThe findings of the present research indicated that the content cues of the quality of information provided by the firm have a positive effect on enhancing destination brand awareness and in turn improve affective image and cognitive image. Eventually, the content cues of the quality of information provided by the firm impact the formation of a conative image through the affective and cognitive image of the destination.Practical implicationsPragmatically, the findings of this study urge policymakers of tourism companies, managers and destination marketers to take into account the special role of the firm's social media in enhancing destination brand awareness, which in turn promotes destination brand image. Therefore, providing empirical evidence on what leads to the promotion of destination brand awareness and different types of image formation of the destination due to information content quality provided by the firm on social media, provides managerial insights for corporate marketers and tourism destinations.Originality/valueThis study contributes to the body of knowledge on the role of quality of tourism information content presented in the firm's social media by providing empirical evidence on enhancing destination brand awareness and destination image formation. It also helps firm managers and planners build their marketing strategies to attract more customers through social media.

Moral Disengagement Cues and Consequences for Victims in Entertainment Narratives: an Experimental Investigation

ABSTRACT The role of moral disengagement in evaluating narrative character behaviors has been a source of scholarly investigation for some time. Despite a theoretical interest in the process, little work has experimentally manipulated content features related to the mechanisms proposed by Bandura in his selective moral disengagement model. This paper presents the results of an experiment that manipulates the presence/absence of a victim of an immoral protagonist’s actions in an audio-visual narrative. We measure various narrative engagement variables including perspective-taking, approbation of behavior, and character liking. Thus, our study design tests content cues corresponding to Bandura’s selective moral disengagement hypotheses and links them to variables specified in Zillmann’s affective disposition theory. Findings indicate that perspective-taking with the immoral protagonist is enhanced when the victim is absent. Perspective-taking then has downstream effects on other narrative processing variables, such as character judgments, desires for specific story outcomes, and punitiveness toward similar real-world behaviors. The design of the current study thus provides a roadmap for future research, and we discuss the value of carefully manipulating narrative cues in order to encourage or discourage moral disengagement in viewers.

Language of Criminal Confessions


 Confession evidence is powerfully persuasive, and yet many wrongful convictions involving false confessions have surfaced in recent years (Innocence Project, 2021; National Registry of Exonerations, 2021). Although police are trained to corroborate admissions of guilt, research shows that most false confessions contain accurate details and other content cues suggesting credibility as well as extrinsic evidence of guilt. Hence, a method is needed to help distinguish true and false confessions. In this study, we utilized a corpus-based approach to outline the linguistic features of two sets of confessions: those that are presumed true (n = 98) and those that have been proven false (n = 37). After analyzing the two corpora in LIWC (Linguistic Inquiry and Word Count) to identify significant categories, we created a logistic regression model that distinguished the two corpora based on three identified predictors: personal pronouns, impersonal pronouns, and conjunctions. In a first sample comprised of 25 statements per set, the model correctly categorized 37 out of 50 confessions (74%); in a second out-of-model sample, the predictors accurately classified 20 of 24 confessions (83.3%). A high frequency of impersonal pronouns was associated with confessions proven false, while a high frequency of conjunctions and personal pronouns were associated with confessions presumed to be true. Several patterns were observed in the corpora. In the latter set of confessions, for example, “I” was often followed by a lexical verb, a pattern less frequent in false confessions. Although these data are preliminary and not to be used for practical diagnostic purposes, the findings suggest that additional research is warranted.

Detection of Promoted Social Media Campaigns

Information spreading on social media contributes to the formation of collective opinions. Millions of social media users are exposed every day to popular memes — some generated organically by grassroots activity, others sustained by advertising, information campaigns or more or less transparent coordinated efforts. While most information campaigns are benign, some may have nefarious purposes, including terrorist propaganda, political astroturf, and financial market manipulation. This poses a crucial technological challenge with deep social implications: can we detect whether the spreading of a viral meme is being sustained by a promotional campaign? Here we study trending memes that attract attention either organically, or by means of advertisement. We designed a machine learning framework capable to detect promoted campaigns and separate them from organic ones in their early stages. Using a dataset of millions of posts associated with trending Twitter hashtags, we prove that remarkably accurate early detection is possible, achieving 95% AUC score. Feature selection analysis reveals that network diffusion patterns and content cues are powerful early detection signals.

What can you perceive? Understanding user’s information quality judgment on academic social networking sites

Introduction. Considering the overwhelming amount of scientific information available on academic social networking sites, the purpose of this paper is to explore how users perceive and judge the information quality. Method. Drawing upon the dual-process model, we theorised that the results of perception depend on the influence of both content cues and context-related cues. Analysis. We conducted two controlled experiments to verify our hypotheses. Results. Our findings indicated that, (1) higher levels of information quality can be perceived with high content value than with low content value, and there was an interaction effect between content value and question type (Experiment 1); (2) three kinds of context-related cues (authority cues, peer cues, and recommendation cues) demonstrated the significant main effect on perceived information quality, and there was an interaction effect among these three cues (Experiment 2). Conclusions. This study contributes by addressing both central and peripheral cues based on a dual-process model, different from previous research which has mainly been confined to examining the external cues' effects. Our findings not only can deepen the comprehension about how users perceive and judge the information quality in academic social networking sites, but also can inform platform developers about the design of the interface and the information system.

The influence of content and non-content cues of tourism information quality on the creation of destination image in social media: A study of Khyber Pakhtunkhwa, Pakistan

This research examines the Content Cues (CC) and Non-Content Cues (NCC) of tourism Information Quality (IQ) in social media (e.g., Instagram, Twitter, Facebook) and its influence on creating Destination Image (DES) components i.e., “cognitive image (COG), affective image (AF), conative image (CON)” in the scope of Khyber Pakhtunkhwa (KP), Pakistan. We distributed 500 questionnaires at various tourist destinations, and 446 complete questionnaires were returned and use for further analysis. We use the Confirmatory Factor Analysis (CFA) and Structural Equation Modelling (SEM) to get the research outcomes. Our outcome suggests that CC and NCC of tourism IQ are significantly related to the COG and AF, which leads to the CON. Our finding also identified the relationship between CC and NCC with CON through the mediation role of COG and AF, which were positive and significant. This research extends the insight of tourism IQ in social media, precisely the contextual dimension of IQ, by providing empirical evidence. This research also helps the KP Destination Marketing Organizations (DMO’s) to develop their marketing strategies to encourage more visitors by utilizing Social Media (SM) platforms to their destinations.

Prestige and content biases together shape the cultural transmission of narratives.

Cultural transmission biases such as prestige are thought to have been a primary driver in shaping the dynamics of human cultural evolution. However, few empirical studies have measured the importance of prestige relative to other effects, such as content biases present within the information being transmitted. Here, we report the findings of an experimental transmission study designed to compare the simultaneous effects of a model using a high- or low-prestige regional accent with the presence of narrative content containing social, survival, emotional, moral, rational, or counterintuitive information in the form of a creation story. Results from multimodel inference reveal that prestige is a significant factor in determining the salience and recall of information, but that several content biases, specifically social, survival, negative emotional, and biological counterintuitive information, are significantly more influential. Further, we find evidence that reliance on prestige cues may serve as a conditional learning strategy when no content cues are available. Our results demonstrate that content biases serve a vital and underappreciated role in cultural transmission and cultural evolution. Social media summary: Storyteller and tale are both key to memorability, but some content is more important than the storyteller's prestige.