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"User-generated content"
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Is Neutral Really Neutral? The Effects of Neutral User-Generated Content on Product Sales
This article aims to specify the performance implications of neutral user-generated content (UGC) on product sales by differentiating mixed-neutral UGC, which contains an equal amount of positive and negative claims, from indifferent-neutral UGC, which includes neither positive nor negative claims. The authors propose that positive and negative UGC only provide opportunities for consumers to process product-related information, whereas both mixed- and indifferent-neutral UGC affect consumers’ motivation and ability to process positive and negative UGC. The results of three studies using multiple measures (text and numerical UGC), contexts (automobiles, movies, and tablets), and methods (empirical and behavioral experiment) indicate contrasting premium and discount effects such that mixed-neutral UGC amplifies the effects of positive and negative UGC, whereas indifferent-neutral UGC attenuates them. Empirical evidence further indicates that ignoring mixed- or indifferent-neutral UGC leads to substantial under- or overestimates of the effects of positive and negative UGC. The effects of neutral UGC on product sales thus are not truly neutral, and the direction of the bias depends on both the type of UGC and the distribution of positive and negative UGC.
Journal Article
Understanding the world of user-generated content
Describes how to use those parts of the Internet that are interactive, sometimes known as \"Web 2.0,\" including Wikipedia, blogs, podcasts, video sharing, and other types of user-generated content.
Book
Impact of YouTube User‐Generated Content on News Dissemination and Youth Information Reception
ABSTRACT
Background
User‐generated content (UGC) on YouTube has reshaped news dissemination, fostered engagement, raised concerns about credibility, algorithmic influence and the spread of misinformation. This study addresses the gap in understanding how UGC engagement, trust and algorithmic awareness influence digital news consumption.
Methods
A convergent parallel mixed‐methods design was employed, integrating survey data (n = 100), qualitative interviews and content analysis of 200 YouTube news videos. Data were collected over 6 weeks. Quantitative analyses included ANOVA, multivariate regression and structural equation modelling (SEM), while qualitative data were thematically analysed to contextualise statistical findings.
Results
UGC news consumption (M = 3.21, SD = 1.14) exceeded traditional news (M = 2.95, SD = 1.20), with trust in UGC (M = 3.48, SD = 1.05) surpassing traditional sources (M = 3.12, SD = 1.17). SEM analysis confirmed that UGC engagement significantly increased trust (β = 0.42, p < 0.001), while algorithmic influence negatively affected trust (β = −0.33, p = 0.015). Sensationalist content attracted higher engagement (30.0%) but had lower credibility, with misinformation prevalent in 38.0% of analysed videos.
Conclusion
Findings highlight the need for platform transparency, stronger content verification and policy interventions to balance engagement‐driven algorithms and news credibility. Media literacy initiatives are crucial for equipping users with the critical evaluation skills they need.
Journal Article
Scandal in a digital age
This book explores the way today's interconnected and digitized world--marked by social media, over-sharing, and blurred lines between public and private spheres--shapes the nature and fallout of scandal in a frenzied media environment. Today's digitized world has erased the former distinction between the public and private self in the social sphere. Scandal in a Digital Age marries scholarly research on scandal with journalistic critique to explore how our Internet culture driven by (over)sharing and viral, visual content impacts the occurrence of scandal and its rapid spread online through retweets and reposts. No longer are examples of scandalous behavior merely reported in the news. Today, news consumers can see the visual evidence of salacious behavior whether through an illicit tweet or video with a simple click. And we can't help but click. -- Back cover.
Book
The Power of Brand Selfies
Smartphones have made it nearly effortless to share images of branded experiences. This research classifies social media brand imagery and studies user response. Aside from packshots (standalone product images), two types of brand-related selfie images appear online: consumer selfies (featuring brands and consumers' faces) and an emerging phenomenon the authors term \"brand selfies\" (invisible consumers holding a branded product). The authors use convolutional neural networks to identify these arche-types and train language models to infer social media response to more than a quarter-million brand-image posts (185 brands on Twitter and Instagram). They find that consumer-selfie images receive more sender engagement (i.e., likes and comments), whereas brand selfies result in more brand engagement, expressed by purchase intentions. These results cast doubt on whether conventional social media metrics are appropriate indicators of brand engagement. Results for display ads are consistent with this observation, with higher click-through rates for brand selfies than for consumer selfies. A controlled lab experiment suggests that self-reference is driving the differential response to selfie images. Collectively, these results demonstrate how (interpretable) machine learning helps extract marketing-relevant information from unstructured multimedia content and that selfie images are a matter of perspective in terms of actual brand engagement.
Journal Article
Wikipedia : the company and its founders
This volume examines the history of Wikipedia, and the lives and careers of its founders.
Book
When a Doctor Knows, It Shows: An Empirical Analysis of Doctors’ Responses in a Q&A Forum of an Online Healthcare Portal
Healthcare portals are gaining in popularity, connecting doctors with potential consumers of healthcare services. As online search and transaction marketplaces, they bring both sides of the market onto the same platform. Managers or platform owners seek to create value by increasing the number of users on either side of demand and supply of services. User-generated activity on Q&A forums of such sites reduces information asymmetry and indicates an increased adoption by either side. In this study, we have provided insights into understanding drivers for increased recommendations for doctors in online healthcare-services marketplace. The identification of these drivers and their directionality, interplay, and magnitude of impact are all of direct relevance to site promoters and managers as well as users. We find that the introduction of doctors’ responses has a significant causal impact on demand-side user perception of medical services offered. More importantly, our research suggests that doctors’ specialty, experience, qualifications, transparency in appointment booking, service fees, and response quality moderate the effect of doctors’ Q&A responses on user recommendations.
Question-and-answer (Q&A) forums are gaining popularity as a user-engagement tool to drive traffic on multiservice portals. In a platform market model, demand-side users seek answers from supply-side users because such answers can indicate value offered, reduce buyer uncertainty, and offer social proof. Analyzing user-generated content on the Q&A forum of a prominent healthcare portal, we find that the introduction of doctors’ responses has a significant causal impact on demand-side user perception of medical services offered. More importantly, our research suggests that doctors’ specialty, experience, qualifications, transparency in appointment booking, service fees, and response quality moderate the effect of doctors’ Q&A responses on user recommendations. These results demonstrate that because of information asymmetry in healthcare, doctors use thoughtful online responses not only to socially interact with patients but also to signal their expertise.
Journal Article
In Mobile We Trust
In the context of user-generated content (UGC), mobile devices have made it easier for consumers to review products and services in a timely manner. In practice, some UGC sites indicate if a review was posted from a mobile device. For example, TripAdvisor uses a \"via mobile\" label to denote reviews from mobile devices. However, the extent to which such information affects consumers is unknown. To address this gap, the authors use TripAdvisor data and five experiments to examine how mobile devices influence consumers' perceptions of online reviews and their purchase intentions. They find that knowing a review was posted from a mobile device can lead consumers to have higher purchase intentions. Interestingly, this is due to a process in which consumers assume mobile reviews are more physically effortful to craft and subsequently equate this greater perceived effort with the credibility of the review.
Journal Article