User Generated Content Consumption and Social Networking in Knowledge-Sharing OSNs

Lussier, Jake T.; Raeder, Troy; Chawla, Nitesh V.

doi:10.1007/978-3-642-12079-4_29

Cited by 9 publications

(3 citation statements)

References 21 publications

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“…This information will reveal how contents (tweets) receive attention in different topics regarding their content generators. The motivation for content generators in twitter profile categorization stems largely from the fact that humans as intelligent individuals impose complex factors on the consumption and dissemination of information on SNSs [72,73]. Therefore, as the different profile types have different purposes and cater to different needs, the categorization of content generators in each of the six topical discussions will be helpful in measuring the impact and influence each category makes.…”

Section: Content Type Categorizationmentioning

confidence: 99%

Impact of Entrepreneurial Ecosystem Discussions in Smart Cities: Comprehensive Assessment of Social Media Data

Hajikhani

2020

Smart Cities

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Discussions on “smart cities” are gaining in popularity in the past two decades and has shown potential in tackling the cities’ environmental, social, and economic challenges. Smart cities are known as a system of physical infrastructure, the information and communications technology (ICT) infrastructure, and the social infrastructure that exchange information that flows between its many different subsystems. The “smart cities” concept has been introduced with various dimensions, among those, the embedded ICT infrastructure in smart cities is playing a decisive role between the functions of the system. One of the important derivatives of ICT is the new communication mediums known as social network services (SNSs), which is emergent and introduces additional functionalities to “smart cities”. This paper seeks to advance the understanding of SNSs in smart cities to evaluate the effects on the innovation and entrepreneurial ecosystem. This agenda has been tackled by a rigorous methodological approach in order to capture and evaluate the presence of entrepreneurially concerned discussions in a popular SNS intermediate (Twitter). Beyond the methodological contribution on handling big data in SNSs for gaining insights on innovation and entrepreneurial aspects in smart cities, the findings distinguished the influence of a certain category of content generators (professionals) that drive the biggest motives of the interactions in SNSs.

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Section: Content Type Categorizationmentioning

confidence: 99%

Impact of Entrepreneurial Ecosystem Discussions in Smart Cities: Comprehensive Assessment of Social Media Data

Hajikhani

2020

Smart Cities

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“…Driven by personal and social factors, Internet users usually engage in online content consumption in three motives: information acquisition, entertainment and communication (Khan, 2017; Lussier et al , 2010; Moon et al , 2014). Online content can be broadly divided into two categories: professionally generated content (PGC) and UGC.…”

Section: Literature Reviewmentioning

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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“…Memungkinkan untuk berbagi informasi halus dan berkelanjutan dalam dunia maya (Lussier et al, 2010).…”

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Information Sharing Behaviour Di Media Sosial

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Ardyawin²,

Saleh³

2020

jiper

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Media sosial saat ini telah mengubah cara orang berkomunikasi, berbagi konten, berinteraksi, dan berkolaborasi. Saat ini, media sosial menjadi platform yang berharga untuk memfasilitasi berbagi informasi dan komunikasi, tidak hanya pada tingkat pribadi atau individu, tetapi juga organisasi. Tren ini telah menarik perhatian secara signifikan dibidang profesional dan akademis. Namun, terlepas dari pertumbuhan penelitian yang cepat di bidang ini, beberapa upaya telah dilakukan untuk meninjau secara sistematis dan menggabungkan temuan-temuan dari survei sebelumnya, dan untuk menilai kondisi penelitian saat ini terkait prilaku berbagi informasi di media sosial. Tujuan utama dari makalah ini adalah untuk memberikan pemahaman yang lebih baik, dan tinjauan rinci, dari keadaan penelitian saat ini mengenai prilaku berbagi informasi dimedia sosial. Pada makalah ini melakukan pendekatan kajian literatur untuk mengumpulkan, menganalisis, dan menyintesis data mengenai keakuratan dan nilai artikel sebelumnya yang difokuskan pada bidang ini. Hasil dari makalah ini melihat penggunaan media sosial, aktivitas berbagi informasidi media sosial dan faktor-faktor dalam prilaku berbagai informasi di media sosial. Faktor pribadi dan faktor lingkungan sangat mempengaruhi dalam prilaku berbagai informasi di media sosial. Pada makalah ini sebagian besar studi difokuskan pada perilaku berbagi informasi di media sosial. Tinjauan literatur menunjukkan bahwa, berbagi informasi pada media sosial semakin banyak dilakukan oleh masyarakat sehingga memberikan area untuk penelitian penelitian lebih lanjut.

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User Generated Content Consumption and Social Networking in Knowledge-Sharing OSNs

Cited by 9 publications

References 21 publications

Impact of Entrepreneurial Ecosystem Discussions in Smart Cities: Comprehensive Assessment of Social Media Data

Impact of Entrepreneurial Ecosystem Discussions in Smart Cities: Comprehensive Assessment of Social Media Data

Predicting the voluntary donation to online content creators

Information Sharing Behaviour Di Media Sosial

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