On the Dynamics of Social Media Popularity

Figueiredo, Flávio; Almeida, Jussara M.; Gonçalves, Marcos André; Benevenuto, Fabrí­cio

doi:10.1145/2665065

Cited by 83 publications

(66 citation statements)

References 51 publications

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“…In this context of trending, Figueiredo et al (2014) had presented the following questions in their research, "What makes one particular object become hugely popular while the majority receives very little attention? Which factors affect how the popularity of an object will evolve over time?"…”

Section: Trend Analysismentioning

confidence: 99%

Long tail vs. blockbusters - a data-driven approach

Ranjani

Kumar

2017

IJBSR

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Business revenue generation can be typically represented as a power law distribution curve where the head of the distribution represents the 'blockbusters' (maximum revenue generation) and a 'tail' that represents products that account for a small percentage of total revenue. Traditionally, brick-and-mortar businesses have allocated their sizeable resources and attention to the blockbusters and have largely ignored the tail. In the present internet-driven era and markets, the concept of 'long tail' has emerged that, effectively demonstrates that companies can make the products, in the niche segment, profitable as well however, in practice, this concept is still limited to the digital products marketed online, and in the academic literature, this concept has received little attention. The aim of this paper is to highlight the relevance and importance of a data-driven strategy to manage both the 'blockbusters' and 'long tail', through illustrative cases drawn from the Indian SME food sector. It, then, proposes a conceptual framework that the practitioners can utilise effectively to make informed decisions, driven by data, to maintain a wide product portfolio.

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Section: Trend Analysismentioning

confidence: 99%

Long tail vs. blockbusters - a data-driven approach

Ranjani

Kumar

2017

IJBSR

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“…11 The most recent 1,000 tweets are downloaded for each Twitter user. 12 Avg.|U f ollowee u | is the average number of followees over all the examined Twitter users, |U tweet | is the total number of tweets downloaded.…”

Section: A Datasetmentioning

confidence: 99%

YouTube Video Promotion by Cross-Network Association: @Britney to Advertise Gangnam Style

Yan

Sang

et al. 2015

IEEE Trans. Multimedia

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The emergence and rapid proliferation of various social media networks have reshaped the way how video contents are generated, distributed and consumed in traditional video sharing portals. Nowadays, online videos can be accessed from far beyond the internal mechanisms of the video sharing portals, such as internal search and front page highlight. Recent studies have found that external referrers, such as external search engines and other social media websites, arise to be the new and important portals to lead users to online videos. In this paper, we introduce a novel cross-network collaborative application to help drive the online traffic for given videos in traditional video portal YouTube by leveraging the high propagation efficiency of the popular Twitter followees. Since YouTube videos and Twitter followees IEEE TRANSACTIONS ON MULTIMEDIA, VOL. X, NO. XX, MONTH YEAR 2 distribute on heterogeneous spaces, we present a cross-network association-based solution framework. In this framework, we first represent YouTube videos and Twitter followees in the corresponding topic spaces separately by employing generative topic models. Then, the cross-network topic spaces are associated from both semantic-based and network-based perspectives through the collective intelligence of the observed overlapped users. Based on the derived cross-network association, we finally match the query YouTube videos and candidate Twitter followees in the same topic space with a unified ranking method.The experiments on a real-world large-scale dataset of more than 2.2 million YouTube videos and 31.8 million tweets from 38,540 YouTube users and 39,400 Twitter users demonstrate the effectiveness and superiority of our solution in which network-based and semantic-based association are integrated.

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“…(5) and λ3, λ4, λ5 in Eqn. (7) are selected by a combined line-search strategy according to the minimal objective energy after converge. As a result, the parameters are set as λ1 = 0.1, λ2 = 0.2, λ3 = 0.1, λ4 = 0.01, λ5 = 0.01.…”

Section: Experimental Settingmentioning

confidence: 99%

“…However, essentially as a content repository, YouTube exhibits limited promotion efficiency with the internal mechanisms. Very recent research shows that external referrers, such as external search engines and other social media websites, arise to be important sources to lead users to YouTube videos [7]. Among the social media websites, Twitter has been quickly growing as the top referrer source for web video discovery 3 .…”

Section: Introductionmentioning

confidence: 99%

Mining Cross-network Association for YouTube Video Promotion

Yan

Sang

2014

Proceedings of the 22nd ACM International Conference on Multimedia

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We introduce a novel cross-network collaborative problem in this work: given YouTube videos, to find optimal Twitter followees that can maximize the video promotion on Twitter. Since YouTube videos and Twitter followees distribute on heterogeneous spaces, we present a cross-network association-based solution framework. Three stages are addressed: (1) heterogeneous topic modeling, where YouTube videos and Twitter followees are modeled in topic level; (2) cross-network topic association, where the overlapped users are exploited to conduct cross-network topic distribution transfer; and (3) referrer identification, where the query YouTube video and candidate Twitter followees are matched in the same topic space. Different methods in each stage are designed and compared by qualitative as well as quantitative experiments. Based on the proposed framework, we also discuss the potential applications, extensions, and suggest some principles for future heterogeneous social media utilization and cross-network collaborative applications.

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On the Dynamics of Social Media Popularity

Cited by 83 publications

References 51 publications

Long tail vs. blockbusters - a data-driven approach

Long tail vs. blockbusters - a data-driven approach

YouTube Video Promotion by Cross-Network Association: @Britney to Advertise Gangnam Style

Mining Cross-network Association for YouTube Video Promotion

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