User-generated Content Platforms Research Articles

Two-tier regulation models for the user-generated content platform: A game theoretic analysis

This paper explores the optimal regulation strategies of the government and platforms to provide guidelines for how to maintain the order of user-generated content platforms and prevent adverse social events. The platform decides the intensity of regulation measures to be implemented on its content, and the government decides to enforce either direct or indirect regulation on platform content. The main result is that the platform's regulation strategy depends on the relationship between the loss and fine caused by adverse social events and the cost to improve regulation intensity. We find that the optimal regulation strategy of the government depends largely on the potential probability occurrence of adverse social events and the efficiency of direct regulation. Competition prompts platforms to reduce regulation intensity, and counterintuitively, platform users can benefit from fierce competition. However, weak competition may result in lower consumer surplus in a duopoly market than in a monopoly market. In a duopoly market with greatly disparate intrinsic values of two platforms, the government can appropriately relax regulations.

How Attitude and Para-Social Interaction Influence Purchase Intentions of Mukbang Users: A Mixed-Method Study.

Mukbang is widely recognized as a new type of food video on user-generated content (UGC) platforms. The purpose of this study was to identify motivators to watch mukbangs and to examine the relationship between these motivators and the intention to watch mukbangs via attitudes toward mukbangs and para-social relationships. In addition, this study examined how the intention to watch mukbangs affected purchase intention. Interviews were conducted to determine the motivation factors for watching mukbangs by collecting data from mukbang viewers. The results of the interviews suggested that vicarious satisfaction, enjoyment, information, exposure, and attractiveness were motivators for watching mukbangs. Using a survey, this study collected data from 399 participants who watched mukbangs to test relationships. Using SmartPLS, structural equation modeling (SEM) was conducted. The outcomes of the SEM indicated that vicarious satisfaction, enjoyment, and information influenced the intention to watch mukbangs via attitudes toward mukbangs. The results also indicated that exposure and attractiveness had an impact on the intention to watch mukbangs via para-social relationships. Furthermore, the intention to watch mukbangs influenced the intention to purchase food items portrayed in the mukbang content. This study contributes to the literature by empirically confirming the effect of watching mukbang on purchase intention.

User-Generated Content Platforms: Managing the Relationship Triangle

User-Generated Content Platforms: Managing the Relationship Triangle

Buying Future Endorsements from Prospective Influencers on User-Generated Content Platforms

Buying Future Endorsements from Prospective Influencers on User-Generated Content Platforms

Protecting the anonymity of online users through Bayesian data synthesis

Privacy concerns emerge when online users of popular user-generated content (UGC) platforms are identified through a combination of their structured data (e.g., location and name) and textual content (e.g., word choices and writing style). To overcome this problem, we introduce a Bayesian sequential synthesis methodology for organizations to share structured data adjoined to textual content. Our proposed approach enables platforms to use a single shrinkage parameter to control the privacy level of their released UGC data. Our results show that our synthesis strategy decreases the probability of identification of a user to an acceptable threshold while maintaining much of the textual content present in the structured data. Additionally, we find that the value of sharing our protected data exceeds that of sharing the unprotected structured data and textual content separately. These findings encourage UGC platforms that wish to be known for consumer privacy to protect anonymity of their online users with synthetic data.

Popularising Vlogging in China: Bilibili’s Institutional Promotion of Vlogging Culture

Vlogging culture has experienced rapid growth in China since 2018. Central to this expansion, social media platforms have played a dominant role in popularising vlogging culture. By conducting a digital ethnography of the Chinese user-generated content platform Bilibili from September 2019 to May 2022, this article explores the institutional power of platforms in promoting and shaping vlogging production and practices in China. Beyond the function of intermediating, Bilibili shapes vlogging as an intensive production and interactive practice with high performativity to compete for visibility. This article theorises four ways that Bilibili popularises vlogging culture in China: pillarising discourses, metric-based monetisation, advertising mediation and vlog-focused campaigns. In taking this approach, this study sheds light on the institutional power of platforms in promoting and shaping cultural production. In addition, it uncovers the precarity embedded in the promotion strategies, notably the interplay with the platform economy in the context of China.

Immediate and enduring effects of digital badges on online content consumption and generation

Awarding users digital badges for their contributions such as generating valuable content and participating in community activities has become an increasingly popular practice on user-generated content (UGC) platforms to incentivize user engagement. Beyond their immediate effects, digital badges can have enduring effects on UGC consumption and generation by affecting users’ underlying engagement states. To account for both effects, the authors develop a bivariate negative binomial hidden Markov model of content consumption and generation and estimate the model using a panel data set obtained from a large UGC platform. They find that users increase their content generation but decrease their content consumption immediately after being awarded a digital badge. Furthermore, being awarded a digital badge has a positive enduring effect on both content consumption and content generation behaviors of a user. This positive enduring effect mainly applies to users in relatively engaged states but not to users in the least engaged state. Finally, the authors demonstrate the value of the proposed model with respect to assessing consumer responses to the design of digital badges.

THE ROLES OF TECHNOLOGY ACCEPTANCE, USER CREDIBILITY AND COVID-19 PERCEIVED HEALTH RISK IN TOURIST’S SOCIAL MEDIA USER-GENERATED-CONTENT USAGE INTENTION

This study examines the direct effects of technology acceptance (perceived usefulness and ease of use), trustworthiness, expertise, and the moderating effect of COVID-19 perceived health risk on tourists’ social media User-Generated-Content (UGC) usage intention. The study respondent was 233 Malaysian tourists who travelled domestically for leisure during the COVID-19 pandemic. The study hypotheses were examined using multiple regression analysis. The hypotheses testing indicates that perceived usefulness, ease of use, trustworthiness, and expertise significantly affect future usage of social media UGC. In addition, the findings confirm that perceived health risk does not affect the user trustworthiness and future usage of social media UGC. The findings assist tourism stakeholders in understanding tourist behaviour towards social media UGC, especially during the COVID-19 pandemic. The tourism business and policymakers should continuously improve and monitor their UGC platform, especially since UGC was deemed one of the vital information dissemination channels during the COVID-19 pandemic.

Platformed playworkers: Game video creators’ affective labour and emotional labour on Bilibili

This article investigates the game video creators’ playbour on Bilibili, a leading Chinese user-generated content platform with a focus on animation, comics and games. The creators’ labour involves creating content through affective labour and managing the fan communities through emotional labour, situated in a network production model. Current studies of platformed playbour either interchangeably use affective and emotional labour or rarely discuss the interplay between the two concepts. We argue that it is important to recognize their nuance and investigate their relationship. Our research clarifies the difference between affective labour and emotional labour and discovers the conflict between the two types of labour. We argue that the conflict derives from enhanced alienation of leisure activities caused by platformization of playbour. Although the video creators consider strategies to solve conflicts, they can barely escape from the unequal labour relationship, constructed by the platform. This study involves semi-structured interviews with 13 playworkers, one Bilibili employee and three advertisers. The playworkers’ Bilibili channels were also observed online from 2019 to 2020.

Content moderation as language policy

Commercial content moderation removes harassment, abuse, hate, or any material deemed harmful or offensive from user-generated content platforms. A platform’s content policy and related government regulations are forms of explicit language policy. This kind of policy dictates the classifications of harmful language and aims to change users’ language practices by force. However, the de facto language policy is the actual practice of language moderation by algorithms and humans. Algorithms and human moderators enforce which words (and thereby, content) can be shared, revealing the normative values of hateful, offensive, or free speech and shaping how users adapt and create new language practices. This paper will introduce the process and challenges of commercial content moderation, as well as Canada’s proposed Bill C-36 with its complementary regulatory framework, and briefly discuss the implications for language practices.

Exploring Event-synced Navigation Attacks across User-generated Content Platforms in the Wild

Exploring Event-synced Navigation Attacks across User-generated Content Platforms in the Wild

Introducing Contests to a Social Community: The Effects of Contest Participation on a User-Generated Content Platform

Introducing Contests to a Social Community: The Effects of Contest Participation on a User-Generated Content Platform

More than the Quantity: The Value of Editorial Reviews for a User-Generated Content Platform

We investigate an editorial review program for which a review platform supplements user reviews with editorial ones written by professional writers. Specifically, we examine whether and how editorial reviews influence subsequent user reviews (reviews written by noneditor reviewers). A quasiexperiment conducted on a leading review platform in Asia, based on several econometric and natural language processing techniques, yields empirical evidence of an overall positive effect of editorial reviews on subsequent user reviews from the platform’s perspective. First, more reviews are provided for restaurants that receive editorial reviews. In addition, these reviews discuss substantive topics while also including a discussion on other topics, leading to a net increase in content length and variety. They also are more neutral in sentiment and are associated with lower rating valences. Further analysis of the mechanism reveals that the subsequent user reviews of the restaurants that receive editorial reviews become more similar to the editorial reviews in regard to topics, sentiment/rating, length, and readability, indicating a herding effect in how to write a review as the main driver of the change in the subsequent reviews. We further empirically isolate this herding effect among long-time reviewers. The findings suggest that review platforms could use an editorial review program not only to boost the quantitative aspect of user reviews but also, to manage the qualitative aspect as well. This paper was accepted by Kartik Hosanagar, information systems.

Blockchain and Cloud to Overcome the Problems of Buyer and Seller Watermarking Protocols

Copyright protection of digital content has become a problem not only for web content providers but also for ordinary web users who like to publish their digital contents on social or user generated content platforms. Among the possible solutions to such a problem, digital watermarking, in conjunction with watermarking protocols, appears to be a valid alternative to current DRM (digital rights management) systems. In fact, watermarking based solutions insert perceptually invisible copyright information into the copies of contents published or distributed on the web in order to track them. Such insertions are carried out according to the watermarking protocols, which have evolved over the years from the classic “buyer and seller” paradigm into a simpler and versatile “buyer friendly” and “mediated” approach. However, such an approach cannot exploit the new technologies that characterize the current Internet. This paper presents a new watermarking protocol able to adapt the “buyer friendly” and “mediated” approach to the use of innovative technologies such as cloud platforms and blockchain. In this way, (1) content providers and common web users can take advantage of the computing and storage resources made available by cloud platforms; (2) the involvement of trusted third parties in the protocols can be reduced by using blockchain without complicating the protection scheme. In fact, these two goals make the protocol particularly suited for the current Internet.

Three Currents of Platformization in China

This essay explores the three currents of user-generated content (UGC) platform development in China: one is full of improvised endeavors in the cultural production through amateur creativity; one is featured with affective laboring and networking by prosumers, who struggle with the algorithm-conditioned visibility of platforms; and one is featured with regulatory attempts by platforms and authorities to introduce a new “creator economy.” Our investigation into the platformization has focused on the multifaceted role of networking that unfolds among prosumers and platforms, and subsequently the changing networks and hierarchies of the crowd-based economy. We argue for an emerging landscape of multiple networked territories at multiple scales. The logic of visibility-making coordinates the distributed agency of networking by prosumers, platforms, and cultural and political authorities, giving birth to territories at multiple scales, from themed cultural communities to techno-giants with a sense of national pride.

Proletariat Digital dalam Citizen Journalism: Kasus Kompasiana

The trend of citizen journalism in Indonesia has increased since the emergence of amateur videos of the Aceh tsunami in 2004. This is considered as a momentum of new democracy in media because it allows public to independently produce and disseminate information without being intervened by agendasetting of mainstream media. The power of publication was seen to shift from mainstream media to personal ones. However, this trend of citizen journalism changed as it begun to be co-opted by mainstream media in the form of a user-generated content platform in 2008. This paper examines changes in citizen journalism which is managed by mainstream media by focusing on Kompasiana of Kompas Gramedia Group as its unit of analysis. Using Van Djik’s Critical Discourse Analysis and Marxist political economy of media as theoretical approach, it shows that the involvement of mainstream media in citizen journalism is not only seen as a collaboration, but also construction of digital labor. This can be explained by looking at three aspects of Kompasiana commodification practices: regulations, wages, and working hours.

Topical Interest and Degree of Involvement of Bilingual Editors in Wikipedia

Language reveals a lot of information about its speakers. Speakers of one language usually share common cultural habits or regional characteristics, and their similarities become more obvious within the context where there are multiple languages in use. We focus on studying bilingual users of Wikipedia, one of the largest multilingual user-generated content platforms. In Wikipedia, we can observe the patterns in the English edition, where users of multiple languages come together to express their thoughts and interests in the common language of English. To understand the specific topics edited by bilingual users, we analyze them in terms of revision counts, topics, and country names. We find that bilingual users are generally interested in more local topics, and their language is highly related with their topics. Also, we observe that the topical diversity decreases with the proportion of English edits, and more concentrates on topics related with countries and cultures.

Social Influence, Popularity and Interestingness of Online Contents

From user-generated content platforms to shopping portals, an important feature of websites is to identify which contents or items are the most popular and list them on the front page — assuming these contents are also the most interesting. In this paper, we question this assumption by studying data from a major news aggregator website where stories are contributed by users, and by focusing on the consequences of social influence. We first observe that the popularity of contents is correlated with the visibility of their authors, and can thus be explained by social influence. We then provide evidence of a feedback loop between the visibility of contributors and the popularity of their contributions, which increases the importance of social influence over time. Finally we quantify the effect of social influence in making each story popular and show that this effect tends to favor less interesting stories.

The Impact of Learning through Management System vs. Learning through Experience Platform on Exam Results of Digital Natives and Digital Immigrants

The upheaval time of COVID-19 highlighted the importance of an effective way of teaching English to the front-line healthcare workers such as medical doctors and researchers with different digital-divide status, particularly in non-English-speaking countries because they were first-hand users of critical pandemic-related information in mostly-English articles published online by scientific journals. This study attempted to investigate the pedagogical effects of utilizing the two main User-Generated Content (UGC) platforms in E-learning, namely LMS vs. LXP, on the results of the Electronic Ministry of Health Language Examinations (E-MHLE) among Iranian English for Medical Purposes (EMP) learners across their digital-divide status (digital natives vs. digital immigrants) during the COVID-19 pandemic. A series of focus-group E-interviews were conducted to determine the reasons behind the lowest scores among the participants and to find out possible suggestions for success in high-stake E-tests. To this end, 272 EMP learners who were users of LMS and LXP were conveniently selected from a university of medical science to participate in this sequential explanatory mixed-method research. The results of descriptive and inferential statistics showed that the LXP group outperformed the LMS one in the results of E-MHLE. Moreover, the digital natives obtained higher scores than the digital immigrants in both groups but the difference was not significant in the LXP. The findings of the E-interviews were thematically analyzed and discussed. The findings of this study might offer practical and realistic benefits to the whole EMP community, particularly policymakers for the post-COVID-19 era.

Development of a Codebook of Online Anti-Vaccination Rhetoric to Manage COVID-19 Vaccine Misinformation.

Vaccine hesitancy (delay in obtaining a vaccine, despite availability) represents a significant hurdle to managing the COVID-19 pandemic. Vaccine hesitancy is in part related to the prevalence of anti-vaccine misinformation and disinformation, which are spread through social media and user-generated content platforms. This study uses qualitative coding methodology to identify salient narratives and rhetorical styles common to anti-vaccine and COVID-denialist media. It organizes these narratives and rhetorics according to theme, imagined antagonist, and frequency. Most frequent were narratives centered on “corrupt elites” and rhetorics appealing to the vulnerability of children. The identification of these narratives and rhetorics may assist in developing effective public health messaging campaigns, since narrative and emotion have demonstrated persuasive effectiveness in other public health communication settings.