• Corpus ID: 5691687

What Drives the Growth of YouTube? Measuring and Analyzing the Evolution Dynamics of YouTube Video Uploads

@inproceedings{Golnari2014WhatDT,
  title={What Drives the Growth of YouTube? Measuring and Analyzing the Evolution Dynamics of YouTube Video Uploads},
  author={Golshan Golnari and Yanhua Li and Zhi-Li Zhang},
  year={2014}
}
We make the first attempt to study the evolution dynamics of YouTube, from the perspectives of uploaded videos and uploaders. Using unbiasedly estimated video statistics, we study how YouTube grows over time, from the inception of YouTube in 2005 up until now. We show that the growth of YouTube videos undergoes several phases: i) an initial growth phase best fitted by a quadratic curve, ii) an exponential growth phase that starts circa late 2009, interrupted by iii) a sudden drop that lasts a… 

A Snapshot of the Depiction of Electronic Cigarettes in YouTube Videos.

Most e-cigarette YouTube videos are non-traditional or covert advertisements featuring young Caucasian men, according to a nationwide sample selected from the top 20 search results for "electronic cigarette," and "e-cig".

Digital Influencers and Portuguese Followers: The Cameron Dallas Case

Since the end of the 21st century, social media have an important role as a media communication method. The created content is spread in a quickly and personalized way and the user is, at the same

The release of Grand Theft Auto V and registered juvenile crime in the Netherlands

Prior research suggests that playing videogames can have a voluntary incapacitating effect on criminal behaviour. The current study investigates whether this negative association between videogames

Klasterisasi Topik Konten Channel Youtube Gaming Indonesia Menggunakan Latent Dirichlet Allocation

Youtube adalah platform untuk saling berbagi video terbesar di internet. Semakin platform ini berkembangan, semakin banyak konten yang tersedia di dalamnya, yang dikarenakan semakin beragam genre

Digraph Spectral Clustering with Applications in Distributed Sensor Validation

A generalized digraph spectral clustering method that takes into consideration the network circulation while clustering the sensors, which outperforms the traditional spectral clustered method by increasing the bad detection ratio from 19% to 41%.

References

SHOWING 1-10 OF 24 REFERENCES

The tube over time: characterizing popularity growth of youtube videos

This work characterize the growth patterns of video popularity on the currently most popular video sharing application, namely YouTube, and shows that copyright protected videos tend to get most of their views much earlier in their lifetimes, often exhibiting a popularity growth characterized by a viral epidemic-like propagation process.

A data-driven analysis of YouTube community features

The authors' analysis shows that users posting videos under a specific category get a better recognition than those actively posting videos belonging to a large variety of categories, and the influence of the community-based features of YouTube on the popularity of content posted online.

YouTube around the world: geographic popularity of videos

It is demonstrated how, despite the global nature of the Web, online video consumption appears constrained by geographic locality of interest: this has a potential impact on a wide range of systems and applications, spanning from delivery networks to recommendation and discovery engines, providing new directions for future research.

YouTube traffic dynamics and its interplay with a tier-1 ISP: an ISP perspective

The surprising fact that YouTube does not consider the geographic locations of its users at all while serving video content is discovered, and a novel method to estimate unseen traffic is developed so as to "complete" the traffic matrix between YouTube data centers and users from the customer ASes of the ISP.

Counting YouTube videos via random prefix sampling

This paper develops a random prefix sampling method to estimate the total number of videos hosted by YouTube, and demonstrates that the estimator based on this method is unbiased, and provides bounds on its variance and confidence interval.

The untold story of the clones: content-agnostic factors that impact YouTube video popularity

A methodology that is able to accurately assess the impacts of various content-agnostic factors on video popularity, including the first-mover advantage, and search bias towards popular videos is developed and applied.

Youtube traffic characterization: a view from the edge

This paper presents a traffic characterization study of the popular video sharing service, YouTube, and finds that as with the traditional Web, caching could improve the end user experience, reduce network bandwidth consumption, and reduce the load on YouTube's core server infrastructure.

What's trending?: mining topical trends in UGC systems with YouTube as a case study

This work develops a standard system for detecting emerging trends in user posts for UGC that contains some form of textual data and makes this system open-source and straightforward to integrate with various UGC systems.

Broadcast yourself: understanding YouTube uploaders

The positive reinforcement between on-line social behavior and uploading behavior is demonstrated and whether YouTube users are truly broadcasting themselves is examined, via characterizing and classifying videos as either user generated or user copied.