social networking service
Recently Published Documents





2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Hee-Tae Lee ◽  
Moon-Kyung Cha

PurposeThis paper aims to identify the effect of social structure variables on the purchase of virtual goods. Using field data, it also tests whether their effects on a social networking service are dynamic.Design/methodology/approachTo achieve the research objectives, the authors have applied the random effects panel Tobit model with actual time-series corporate data to explain a link between network structure factors and actual behavior on social networking services.FindingsThe authors have found that various network structure variables such as in-degree, in-closeness centrality, out-closeness centrality and clustering coefficients are significant predictors of virtual item sales; while the constraint is marginally significant, out-degree is not significant. Furthermore, these variables are time-varying, and the dynamic model performs better in a model fit than the static one.Practical implicationsThe findings will help social networking service (SNS) operators realize the importance of understanding network structure variables and personal motivations or the behavior of consumers.Originality/valueThis study provides implications in that it uses various and dynamic network structure variables with panel data.

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
YooJung Kim ◽  
Yejung Seo

Purpose This study aims to investigate the relationship between environmental activities and consumer engagement on firm performance according to supply-and-demand perceptions, and further examines the moderating role of internationalization to demonstrate the effects of environmental activities more comprehensively. Design/methodology/approach Three panel regression models have been used. In total, 510 environmental activities and consumers’ negative engagement collected from the official Facebook brand page are analyzed to examine the study’s models for a period of 13-years (2008–2020). The findings persist when this study compares the estimates resulted from different econometrics methods. Findings The study’s results indicate an insignificant effect of environmental activities and consumer engagement on firm performance, respectively, while the interaction effect on firm performance is significant and negative. However, when internationalization plays the moderating role, this study provides new evidence that such negativity impact is no longer effective in the lodging industry as firms expand internationally. Practical implications This study offers strategic insights to managers who are concerned about the detrimental effect of negative consumer engagement that the firm-consumer relationship mitigates the negativity bias in negative engagement. Hotels should actively implement internationalization as a key strategy while practicing environmental activities with integrity. Originality/value Despite the importance of green management in the social networking service context, little is known about its effect and value on firm performance. This study provides new evidence for the real effectiveness of internationalization by demonstrating its role in the lodging industry.

Ragu G

Abstract: With the development of the Internet and social networking service, the micro-video is becoming more popular, especially for youngers. However, for many users, they spend a lot of time to get their favourite micro-videos from amounts videos on the Internet; for the micro-video producers, they do not know what kinds of viewers like their products. Therefore, we propose a micro-video recommendation system. The recommendation algorithms are the core of this system. Traditional recommendation algorithms include content-based recommendation, collaboration recommendation algorithms, and so on. At the Big Data times, the challenges what we meet are data scale, performance of computing, and other aspects. Thus, we improve the traditional recommendation algorithms, using the popular parallel computing framework to process the Big Data. Slope one recommendation algorithm is a parallel computing algorithm based on MapReduce and Hadoop framework which is a high-performance parallel computing platform. The other aspect of this system is data visualization. Only an intuitive, accurate visualization interface, the viewers and producers can find what they need through the micro-video recommendation system. Keywords: Short, video, recommendation , machine learning

Christopher James Wells

Whereas bisexuality, as it existed in modernity, has been described as a ‘floating signifier', one that was problematically conflated with gender and intersex bodies, the articulation of bisexuality is now experiencing a discursive resurgence in spaces and platforms online. Through a deliberately disparate comparison between Virginia Woolf’s modernist writing and the discussions of bisexuality on the video-sharing social networking service TikTok, this essay presents a reflective reassessment of how far bisexual representation in the popular imagination has progressed and by extension, evaluate extant limitations. To realize these ambitions, I compare the reception of sexology (the new science of sexuality) in ‘high’ modernist literature with a post-modern demographic whose bisexuality is articulated in the 2020s online via TikTok’s towards what I would demarcate as a post-queer theory user base. This essay is not intended as an overview of the advancements made in psychoanalytic institutions about bisexuality nor does it set out to comment on the refinement of bisexuality’s aestheticization through time. Instead, it uses these two temporally specific moments in the cultural zeitgeist to compare and contrast how differently two different demographics articulate bisexuality, both as a written mode in modernism and as a visual apparatus online. This is less a critique of bi-erasure, but an interrogation of why and how bisexual representation, as an aestheticized subjectivity that compromises romantic, spiritual, and erotic desires for bodies of all genders, continues to be problematically restrictive.

2021 ◽  
Toru Nishita ◽  
Masaaki Sato ◽  
Jun Murai ◽  
Hiro Harada ◽  
Seiya Kaneko ◽  

SAGE Open ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 215824402110615
Wei Zhang ◽  
Jie Mei ◽  
Weifang Song ◽  
Richard Evans ◽  
Yaqian Xiang

Chinese public hospitals have increased usage of TikTok to communicate with citizens on health-related matters. This study aims to investigate the engagement of citizens with the official TikTok accounts of public hospitals, and identify the major characters of the videos with the highest public engagement level, as well as underlying factors that make them successful. A comprehensive search on TikTok, a video-sharing social networking service, was completed to identify all official accounts of public hospitals in Mainland China. Data was collected from 40 public hospitals with the top 100 TikTok videos being identified for content analysis. The majority of them were created by public hospitals located in the Central and Western regions of China. The common features of the top 100 identified videos include: low message sensation value and short video length, and are typically accompanied by background music, subtitles, and an introduction at the beginning of the video. The most frequently viewed video type is film clips which are used to disseminate knowledge of diseases and promote healthcare professionals. Health communication via the official TikTok accounts of public hospitals in China offers significant potential. Hospitals are encouraged to engage citizens in health-related conversations to build their credibility and professional image online. Among the popular short-videos, the message sensation value is not largely connected to video popularity, while the content of videos seems more important. This requires skills in video creation or procurement, and editing, while rhetoric should be cautiously applied. The content of videos should provide education and positive energy.

Michelle Sylvia Weintraub ◽  
David R W Sears

ABSTRACT The Do-It-Yourself (DIY) community is currently one of the largest creative content communities on Pinterest (Hall et al., 2018), a social networking service (SNS) that encourages users to both share information about creative processes and attempt projects in real life (IRL). Pinterest users share ongoing projects by creating Project “Pins”, which consist of images, videos, and text descriptions of creative content. And yet, while several studies have investigated user behavior in relation to everyday ideation and creativity on the site (Linder et al., 2014, Hu et al., 2018, Mull and Lee, 2014), little is known about the characteristics that lead users to prefer some DIY projects over others. Thus, this paper introduces the Pinterest-DIY data set, which consists of text data mined from 500 DIY project Pins on Pinterest. Using a custom sampling approach, we created a taxonomy of DIY characteristics related to each Pin’s project type, function, materials, and complexity. To measure user preferences on the site, we also conducted a sentiment analysis on user comments for each DIY project Pin. This paper introduces the data set and presents two use cases for the internet research community using both exploratory and confirmatory statistical methods. In our view, the Pinterest-DIY data set will provide further opportunities to examine whether, and to what degree, participation in online DIY communities promotes everyday creativity and increases engagement with physical matter.

Sign in / Sign up

Export Citation Format

Share Document