Virtual Gifts Research Articles

Beyond the Watching: Understanding Viewer Interactions in Crowdsourced Live Video Broadcasting Services

Crowdsourced live video broadcasting services, such as Twitch and YouTube Live, are becoming increasingly popular. In such a service, viewers are allowed to perform rich interactions, such as posting comments and donating monetary virtual gifts, while watching videos. Understanding viewer interactions is essential for people to comprehend the production and consumption of the crowdsourced live video content and improve the service. However, the basic characteristics of the viewer interactions are still unknown. In this paper, we present a comprehensive measurement study of the viewer interactions on Douyu, a popular crowdsourced live video broadcasting website in China. Our measurement spans four months and contains comment posting and virtual gift donating interactions from tens of millions of viewers in hundreds of thousands of channels. Based on the measurement data, we carry out a content analysis on danmu comments and characterize the patterns of the viewer interactions. We build a suite of models for capturing the gift donating process, viewer activity, and channel popularity. We further analyze the influences of the broadcaster’s behavioral factors on a channel’s popularity and present methodologies for popularity predicting. Our measurement and analysis have important implications on the design and business policy of the crowdsourced live video broadcasting services.

Live streaming, intimate situations, and the circulation of same-sex affect: Monetizing affective encounters on Blued

Drawing on interviews with 10 gay streamers and 30 viewers, this article analyzes a new feature of live streaming on Blued, a Chinese gay male dating app. Live streaming invites users to either perform themselves or watch others perform. Unlike western gay dating apps that monetize users’ hooking-up encounters, the business model behind Blued instead capitalizes on affective encounters among gay streamers and viewers. Through paid virtual gifts, which circulate as affective signs, live streaming fosters and intensifies viewers’ intimate attachment to gay streamers. The virtual intimacy produced by gay live streaming entails a significant economic dimension, and is therefore stigmatized. In consequence, gay streamers do not see streaming as sex-related work, and paying viewers do not portray gifts as consumption. In understating the economic and sexual underpinnings of affective encounters mediated by live streaming, gay streamers and viewers not only reinforce heteronormativity, but also produce homonormativity.

Investigating the Effect of Paid and Free Feedback About Physicians' Telemedicine Services on Patients' and Physicians' Behaviors: Panel Data Analysis.

BackgroundIn recent years, paid online patient-physician interaction has been incorporated into the telemedicine markets. With the development of telemedicine and telemedicine services, online feedback has been widely applied, helping other patients to identify quality services. Recently, in China, a new type of service feedback has been applied to the telemedicine markets, namely, paid feedback. Patients who are satisfied with a physician’s online service can buy a virtual gift or give a tip to the physicians. This paid feedback can improve the reliability of service feedback and reduce the proportion of false information because it increases the cost for feedback providers. Paid online feedback can benefit the physicians, such as by providing them with monetary incentives; however, research on the impacts and value of such paid feedback from the physician perspective in the telemedicine markets is scant. To fill this research gap, this study was designed to understand the role of paid feedback by developing a research model based on the theories of signaling and self-determination.ObjectiveThis study aimed to explore the effects of free and paid feedback on patients’ choice and physicians’ behaviors as well as to investigate the substitute relationship between these 2 types of feedback in the telemedicine markets.MethodsA JAVA software program was used to collect online patient-doctor interaction data over a 6-month period from a popular telemedicine market in China (Good Physician Online). This study drew on a 2-equation panel model to test the hypotheses. Both fixed and random effect models were used to estimate the combined effects of paid feedback and free feedback on patients’ choice and physicians’ contribution. Finally, the Hausman test was adopted to investigate which model is better to explain our empirical results.ResultsThe results of this study show that paid feedback has a stronger effect on patients’ choice (a5=0.566; t2192=9.160; P<.001) and physicians’ contribution (β4=1.332; t2193=11.067; P<.001) in telemedicine markets than free feedback. Moreover, our research also proves that paid feedback and free feedback have a substitute relationship in determining patients’ and physicians’ behaviors (a6=−0.304; t2191=−5.805; P<.001 and β5=−0.823; t2192=−8.136; P<.001).ConclusionsOur findings contribute to the extant literature on service feedback in the telemedicine markets and provide insight for relevant stakeholders into how to design an effective feedback mechanism to improve patients’ service experience and physicians’ engagement.

The Effect of Online Effort and Reputation of Physicians on Patients' Choice: 3-Wave Data Analysis of China's Good Doctor Website.

BackgroundNowadays, patients are seeking physician information more frequently via the internet. Physician-rating websites (PRWs) have been recognized as the most convenient way to gain insight and detailed information about specific physicians before receiving consultation. However, little is known about how the information provided on PRWs may affect patients’ decisions to seek medical advice.ObjectiveThis study aimed to examine whether the physicians’ online efforts and their reputation have a relationship with patients’ choice of physician on PRWs.MethodsA model, based on social exchange theory, was developed to analyze the factors associated with the number of online patients. A 3-wave data collection exercise, covering 4037 physicians on China’s Good Doctor website, was conducted during the months of February, April, and June 2017. Increases in consultation in a 60-day period were used as the dependent variable, whereas 2 series of data were analyzed using linear regression modeling. The fixed-effect model was used to analyze the 3-wave data.ResultsThe adjusted R2 value in the linear regression models were 0.28 and 0.27, whereas in the fixed-effect model, it was .30. Both the linear regression and fixed-effect models yielded a good fit. A positive effect of physicians’ effort on the aggregated number of online patients was identified in all models (R2=0.30 and R2=0.37 in 2 regression models; R2=0.23 in fixed effect model; P<.001). The proxies of physicians’ reputations indicated different results, with total number of page views of physicians’ homepages (R2=0.43 and R2=0.46; R2=0.16; P<.001) and number of votes received (R2=0.33 and R2=0.27; R2=0.43; P<.001) being seen as positive. Virtual gifts were not significant in all models, whereas thank-you messages were only significant in the fixed-effect model (R2=0.11; P=.02). The effort made by physicians online is positively associated with their aggregated number of patients consulted, whereas the effect of a physician’s reputation remains uncertain. The control effect of a physician’s title and hospital’s level was not significant in all linear regressions.ConclusionsBoth the effort and reputation of physicians online contribute to the increased number of online patients’ consultation; however, the influence of a physician’s reputation varies. This may imply that physicians’ online effort and reputation are critical in attracting patients and that strategic manipulation of physician profiles is worthy of study. Practical insights are also discussed.

Sports lottery game prediction system development and evaluation on social networks

Purpose – The purpose of this paper is to establish a social-network sp.orts lottery system to support users in predicting and simulating sports lottery betting. The community data were generated to support user decision and featured instant game records and odds data synchronisation. Furthermore, the next development cycle were evaluated through a questionnaire. Design/methodology/approach – An extended prototype website development methodology was applied to develop the system. An online sample was collected to evaluate the function, interface, operation, and prediction designs. The χ2 test and variance analysis were used to determine the association between facets and basic demographics. Finally, the regression model was used to identify the potentially essential predictors that influence the measurement facets. Findings – The high frequency of Facebook users, sports lottery purchases, and sports game viewers prefer the ability to predict the results of future sports games as advanced decision-making functions. However, the agent-based virtual gift presentation function was the least preferred function. Research limitations/implications – The study sample was limited only to users: who used PTT and Facebook; were of uneven age, education, and gender; and none segment groups. The study sample primarily comprised Taiwanese respondents. These differences might influence the practicality and prediction bias of the designed website and related models. Practical implications – The proposed method integrates social-network messages with real-time data access by using APIs, crawler schemes, and prediction mechanisms that enable developers to devise strategies for obtaining high system satisfaction. The system can be improved by adding the results of future sports games and excluding authorised Facebook message posts. Originality/value – A social-network-based sports lottery and prediction prototyping website was evaluated through a user-preference survey regarding design functions. The measurement results indicated that users share their opinions, predictions, and personal betting results and interact with their friends.

Understanding the Design of Mobile Social Networking

Understanding the Design of Mobile Social Networking