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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
Behind the Screen
An eye-opening look at the invisible workers who protect us from seeing humanity's worst on today's commercial internetSocial media on the internet can be a nightmarish place. A primary shield against hateful language, violent videos, and online cruelty uploaded by users is not an algorithm. It is people. Mostly invisible by design, more than 100,000 commercial content moderators evaluate posts on mainstream social media platforms: enforcing internal policies, training artificial intelligence systems, and actively screening and removing offensive material-sometimes thousands of items per day. Sarah T. Roberts, an award-winning social media scholar, offers the first extensive ethnographic study of the commercial content moderation industry. Based on interviews with workers from Silicon Valley to the Philippines, at boutique firms and at major social media companies, she contextualizes this hidden industry and examines the emotional toll it takes on its workers. This revealing investigation of the people \"behind the screen\" offers insights into not only the reality of our commercial internet but the future of globalized labor in the digital age.
eBook
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
Impact of YouTube User‐Generated Content on News Dissemination and Youth Information Reception
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
Wikipedia : the company and its founders
This volume examines the history of Wikipedia, and the lives and careers of its founders.
Book
Social Media Brand Community and Consumer Behavior: Quantifying the Relative Impact of User- and Marketer-Generated Content
Despite the popular use of social media by consumers and marketers, empirical research investigating their economic values still lags. In this study, we integrate qualitative user-marketer interaction content data from a fan page brand community on Facebook and consumer transactions data to assemble a unique data set at the individual consumer level. We then quantify the impact of community contents from consumers (user-generated content, i.e., UGC) and marketers (marketer-generated content, i.e., MGC) on consumers' apparel purchase expenditures. A content analysis method was used to construct measures to capture the informative and persuasive nature of UGC and MGC while distinguishing between directed and undirected communication modes in the brand community. In our empirical analysis, we exploit differences across consumers' fan page joining decision and across timing differences in fan page joining dates for our model estimation and identification strategies. Importantly, we also control for potential self-selection biases and relevant factors such as pricing, promotion, social network attributes, consumer demographics, and unobserved heterogeneity. Our findings show that engagement in social media brand communities leads to a positive increase in purchase expenditures. Additional examinations of UGC and MGC impacts show evidence of social media contents affecting consumer purchase behavior through embedded information and persuasion. We also uncover the different roles played by UGC and MGC, which vary by the type of directed or undirected communication modes by consumers and the marketer. Specifically, the elasticities of demand with respect to UGC information richness are 0.006 (directed communication) and 3.140 (undirected communication), whereas those for MGC information richness are insignificant. Moreover, the UGC valence elasticity of demand is 0.180 (undirected communication), whereas that for MGC valence is 0.004 (directed communication). Overall, UGC exhibits a stronger impact than MGC on consumer purchase behavior. Our findings provide various implications for academic research and practice.
Journal Article
Message content features and social media engagement: evidence from the media industry
Purpose
This paper aims to uncover the drivers of consumer-brand engagement on Facebook, understood here as users’ behavioral responses in the form of clicks, likes, shares and comments. We highlight which content components, interactivity cues (calls to action [CTA]) and media richness (e.g. video, photo and text) are most effective at inducing consumers to exhibit clicking, liking, commenting and sharing behaviors toward branded content.
Design/methodology/approach
This study analyzes 757 Facebook-based brand posts from a media and entertainment brand over a 15-week period. It investigates the relationship between interactive cues and media richness with consumer engagement using a negative binomial model.
Findings
Results show positive relationships for both interactivity cues and media richness content components on increasing consumer-brand engagement outcomes. The findings add clarity to previous inconsistent findings in the marketing literature. CTAs enhance all four engagement behaviors. Media richness also strongly influences all engagement behaviors, with visual imagery (photos and videos) attracting the most consumer responses.
Research limitations/implications
The sampled posts pertain to one brand (a radio station) and are thus concentrated within the media/entertainment industry, which limits the generalizability of findings. In addition, the authors limit their focus to Facebook but recognize that findings may differ across more visual or textual social networking sites.
Practical implications
The authors uncover the most effective pairings of media richness and interactivity components to trigger marketer-desired, behavioral responses. For sharing, for example, the authors show that photo-based posts are more effective on average than video-based posts. The authors also show that including an interactive call to act to encourage one type of engagement behavior has a near-universal effect in increasing all engagement behaviors.
Originality/value
This study takes two widely used concepts within the communications and advertising literatures – interactivity cues and media richness – and tests their relationship with engagement using real and actual users’ data available via Facebook Insights. This method is more robust than surveys or wall scrapping, as it mitigates Facebook’s algorithm effect. The results produce more consistent relationships than previous content marketing studies to date.
Journal Article