Who Is Earning? Understanding and Modeling the Virtual Gifts Behavior of Users in Live Streaming Economy

Tu, Wei; Chen, Yan; Yan, Yiping; Ding, Xu; Sun, Lijuan

doi:10.1109/mipr.2018.00028

Cited by 20 publications

(16 citation statements)

References 6 publications

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“…The subdomains focused on the platform and the transmission are characterized by the use of more heterogeneous methods, although the former stands out for the inclusion of descriptive statistics and techniques for constructing graphs [ 87 , 88 , 89 , 90 , 91 , 92 ], and the latter for compiling information through application programming interfaces (APIs), both for Twitch [ 73 , 93 , 94 , 95 , 96 , 97 ] and other platforms such as Douyu [ 98 ]. The collection of information through public APIs is spreading to other subdomains (Streamer [ 99 ] Riot Games API; Receiver [ 100 ] Twitch API; and Platform [ 87 , 89 , 91 ] Twitch API), opening up future research opportunities if simultaneous information about the streamer, receiver, and platform can be connected.…”

Section: Resultsmentioning

confidence: 99%

“…The link with the first cluster is established through the different motivations that give rise to widely differing behavior [ 85 ]. The topic is extremely complex as it relates to behaviors, for example, the intention to purchase and the sending of virtual gifts [ 100 ], the identification of paying viewers [ 107 ], subscription [ 68 ] and impulse buying [ 66 ], or wishful identification and emotional engagement as a predictor of many of these behaviors [ 70 ]. It also tackles viewers’ information activities [ 18 ], or negative behavior such as online harassment [ 106 ], excessive use of live streaming services [ 67 ], aggressive attitudes in discourse or speech [ 116 ], and even the negative effects of streaming on streamer performance [ 99 ].…”

Section: Resultsmentioning

confidence: 99%

“…Cont. ,23,68,73,74,[77][78][79]85,[87][88][89]92,94,97,[100][101][102][103][106][107][108]110,116,122,124,[128][129][130][131][132]134,135,137,140,143,144,146,147] Journal Citation Report; ** SSCI:Social Sciences Citation Index; SCIE: Science Citation Index Expanded; A&HCI: Arts & Humanities Citation Index; BSCISS&H: Book Citation Index Social Sciences &…”

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confidence: 99%

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Exploring the Emerging Domain of Research on Video Game Live Streaming in Web of Science: State of the Art, Changes and Trends

Cabeza-Ramírez

García

Fernández

2021

IJERPH

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In recent years, interest in video game live streaming services has increased as a new communication instrument, social network, source of leisure, and entertainment platform for millions of users. The rise in this type of service has been accompanied by an increase in research on these platforms. As an emerging domain of research focused on this novel phenomenon takes shape, it is necessary to delve into its nature and antecedents. The main objective of this research is to provide a comprehensive reference that allows future analyses to be addressed with greater rigor and theoretical depth. In this work, we developed a meta-review of the literature supported by a bibliometric performance and network analysis (BPNA). We used the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) protocol to obtain a representative sample of 111 published documents since 2012 and indexed in the Web of Science. Additionally, we exposed the main research topics developed to date, which allowed us to detect future research challenges and trends. The findings revealed four specializations or subdomains: studies focused on the transmitter or streamer; the receiver or the audience; the channel or platform; and the transmission process. These four specializations add to the accumulated knowledge through the development of six core themes that emerge: motivations, behaviors, monetization of activities, quality of experience, use of social networks and media, and gender issues.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Exploring the Emerging Domain of Research on Video Game Live Streaming in Web of Science: State of the Art, Changes and Trends

Cabeza-Ramírez

García

Fernández

2021

IJERPH

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“…For example, Yu et al (2018) found that viewer engagement positively affects the gift-sending decision and amount on the Korean AfreecaTV platform. Data from several studies suggested that the interaction among viewers on the platform plays an important role in prompting paid gifting behaviors (Tu et al , 2018; Zhou et al , 2019; Zhu et al , 2017). However, such studies remain narrow in focus dealing only with the influencing factors from the perspective of customers and platforms.…”

Section: Literature Reviewmentioning

confidence: 99%

“…It is not compulsory for audiences to pay for the released content which is free of charge. Actually, a small fraction of the audiences contributes to a large proportion of the donation (Tu et al , 2018; Zhu et al , 2017). Therefore, understanding the factors that influence the voluntary donation to content creators becomes important for researchers and practitioners to improve the effectiveness of the business strategy.…”

Section: Introductionmentioning

confidence: 99%

Predicting the voluntary donation to online content creators

Zhao

Yao

2020

IMDS

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PurposeThe purpose of this paper is to identify the impact factors that might influence audiences' voluntary donation to content creators on the online platforms, and to build an effective prediction model by considering both content and creator-related features.Design/methodology/approachThis study collected the real-world data of content consumption from Xueqiu.com and extracted both content and creator characteristics from the data set. The best donation prediction model based on such features was determined by evaluating four prevalent classifiers with various performance metrics. Furthermore, three feature selection methods were applied to validate the robustness of the constructed model, and then the predictability of different feature groups was examined. Finally, we conducted an interpretive analysis to identify relatively important predictors.FindingsThe experimental results show that the random classifier with all extracted features outperformed other built models and achieved excellent performance, indicating the usefulness of these factors in predicting the donations. Moreover, the predictability of content features was demonstrated to be relatively better than that of creator ones. Finally, several particularly important predictors were identified such as the number of modal particles in the article.Originality/valueThis study is among the first to investigate what factors might drive customers' voluntary donation to content contributors on social websites. Different from previous studies focusing on live video streaming, we expand the research vision by examining the donations to user-generated text content, calling for attention to other important topics in the burgeoning industry.

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Discovery of behavioral patterns in online social commerce practice

Jia

Wang

Liu

2021

WIREs Data Min & Knowl

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Discovery of behavioral patterns in online social commerce practice becomes important in this digital era. In this article, we propose a systematic approach to behavioral pattern discovery, and apply it in an emerging online social commerce venue: live streaming. We investigate behavioral patterns in gifting encouragement in live streaming to understand online social commerce practice. Our proposed approach is based on multiple triangulation, including data source triangulation (i.e., streamers, viewers, and actual behavior) and data collection method triangulation (i.e., interviews, focus groups, and observations). Through multiple triangulation, four behavioral patterns of gifting encouragement are discovered: (i) requesting a certain gift for providing a particular service, (ii) creating a raffle, (iii) eliciting competition between individuals, and (iv) eliciting competition between groups. This research reveals the special behavioral patterns in live streaming, and thus increases our knowledge of social commerce practices. This research provides a systematic approach to discover online behavioral patterns, and provides practical implications in live streaming platforms, especially in marketing and platform design.

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Who Is Earning? Understanding and Modeling the Virtual Gifts Behavior of Users in Live Streaming Economy

Cited by 20 publications

References 6 publications

Exploring the Emerging Domain of Research on Video Game Live Streaming in Web of Science: State of the Art, Changes and Trends

Exploring the Emerging Domain of Research on Video Game Live Streaming in Web of Science: State of the Art, Changes and Trends

Predicting the voluntary donation to online content creators

Discovery of behavioral patterns in online social commerce practice

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