Boosting video popularity through keyword suggestion and recommendation systems

Zhou, Renjie; Khemmarat, Samamon; Gao, Lixin; Wan, Jian; Zhang, Jilin; Yin, Yuyu; Yu, Jun

doi:10.1016/j.neucom.2016.05.002

Cited by 21 publications

(14 citation statements)

References 32 publications

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“…Previous research on virality has primarily been drawn from five different fields: psychology (e.g., [9]; [11]; [12]; [13]; [4]), computer science (e.g., [14]; [15]; [16]; [1]; [10]; [17]; [18]; [19]; [20]; [21]; [22]), political science (e.g., [2]; [23]; [24]), marketing (e.g., [25]; [26]; [27]; [28]; [29]; [30]; [31]; [7]; [32]; [33]), and health (e.g., [34]). These studies have been mainly conducted in Western countries, such as the United States, Canada, Germany, Italy, and Australia.…”

Section: Review Of Related Literaturementioning

confidence: 99%

“…These studies have been mainly conducted in Western countries, such as the United States, Canada, Germany, Italy, and Australia. However, there have been a few studies conducted in less developed countries, such as [2] study in South Africa; [29] and [22] studies in China; [1] in South Korea; [18] in Brazil; [4] in Romania; and [21] in India. However, no studies have been conducted in Arab countries or even in the Middle East.…”

Section: Review Of Related Literaturementioning

confidence: 99%

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Intelligent Parallel Mixed Method Approach for Characterising Viral YouTube Videos in Saudi Arabia

Alshanqiti¹,

Bajnaid²,

Rehman³

et al. 2020

IJACSA

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In social networking platforms, comprehending virality, exemplified by YouTube, is of great importance, which helps in understanding what characteristics utilised to create content along with what dynamics involved in contributing to YouTube's strength as a platform for sharing content. The current literature surrounding virality problem appears sparse concerning development theories, investigations regarding empirical facts, and an understanding of what makes videos go viral. The overarching objective is to understand deeply the phenomena of viral YouTube videos in Saudi Arabia, hence we propose an intelligent convergent parallel mixed-methods approach that begins, as an internal step, by a qualitative thematic analyses method and an NLP-based quantitative method independently, followed by training an unsupervised clustering model for integrating the internal analysis outputs for deeper insights. We have empirically analysed some trended YouTube videos along with their contents, for studying such phenomena. One of our main findings revealed that boosting entertainments, traditions, politics, and/or religion issues when making a video, that is associated in somehow with sarcastic or rude remarks, is likely the preeminent impulse for letting a regular video go viral.

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Section: Review Of Related Literaturementioning

confidence: 99%

Section: Review Of Related Literaturementioning

confidence: 99%

Intelligent Parallel Mixed Method Approach for Characterising Viral YouTube Videos in Saudi Arabia

Alshanqiti¹,

Bajnaid²,

Rehman³

et al. 2020

IJACSA

View full text Add to dashboard Cite

show abstract

“…In last decade, quantitative understanding the popularity dynamics of online content has been attracting much attention from academia [1][2][3][4][5]. Popularity dynamics represents many real social phenomena, such as video views on YouTube [6][7][8][9][10][11][12][13], reading volume of tweets and news on social media [14][15][16][17][18][19], and movie views on online system [20][21][22].…”

Section: Modeling and Predicting Popularity Dynamicsmentioning

confidence: 99%

Characterizing popularity dynamics of hot topics using micro-blogs spatio-temporal data

2019

J Big Data

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BackgroundWith the rapid development of mobile Internet technology, human society has entered an era of high interconnection between human and information. Especially the emergence of online social networks, such as Weibo in China, LinkedIn, Twitter, Face-book and so on, because of its high interaction and strong group participation, makes many related information converging and merging, leading to the emergence of hot topics on the Internet. These hot topics are the aggregation of information about current events (e.g., natural disasters, sports news, celebrity news), which have geotags-timestamp information. These metadata (geotags and timestamp) are embedded within the content of the message, so that the analysis of an event can be performed by applying a spacetime classification. In addition, the hot topic is the sprout of the network public opinion. Network public opinion has an important impact on the stability of the country and society. Therefore, the popularity of hot topics is studied from the spatial and temporal dimension can better understand the dissemination of public opinion. This paper uses the data of Sina Weibo, one of the largest micro-blogging system in China (https ://weibo .com/), to study the following two questions: (1) study the classification problem of hot topic on Weibo, cluster the popularity time series by clustering algorithm;(2) study the spatial distribution characteristics of hot topic on Weibo based on location label data. AbstractIn this paper, a quantitative temporal and spatial analysis of the dynamics of hot topics popularity in Micro-blogging system was provided. Firstly, the popularity time series of 1167 hot topics were counted and calculated by Excel. Secondly, based on MAT-LAB software,the popularity time series were clustered into six clusters by K-spectral centroid (K-SC) clustering algorithm. Thirdly, we analyzed temporal patterns and spatial patterns of popularity dynamics of topics by statistical methods. The results show that temporal popularity of micro-blogging topics is rapidly dying, and the distribution of popularity is subject to the power law form. In addition, most of the Micro-blogging topics are global topic. Our results can provide a literature reference for studying the influence of online hot topics and the evolution of public opinion. which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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“…Consequently, there are no duplicated chunks on any UE even if they are received from multiple sources. 17,23 Such an approach is not scalable with the increasing number of UEs requesting the same video content simultaneously.…”

Section: Related Workmentioning

confidence: 99%

Optimal transmission for scalable video coded streaming in cellular wireless networks with the cooperation of local peer-to-peer network

Feng

Lin

Zhao

et al. 2017

International Journal of Distributed Sensor Networks

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We study the problem of transmitting scalable video coded streams in a hybrid scenario including a global cellular network and a local peer-to-peer network. Given desirable channel condition in cellular downlink, some cellular user equipments can fetch the video chunks via the cellular base station directly, and also provide relay service via the local peer-to-peer network for other user equipments unable to meet their basic video quality. To take the advantage of channel diversity gains, the method of random linear coding is adopted to generate linear combinations of the video chunks for transmission in both the cellular and peer-to-peer networks. To optimize the cellular and peer-to-peer transmission arrangement, we first formulate it as a mixed integer nonlinear programming problem, which becomes more complicated when the number of user equipments increases. Then, we convert it to a quasi-convex optimization problem by approximating the indicator function with a continuous step function, and it can be solved by a centralized approach. Furthermore, a primal-dual decomposition approach is developed and a distributed algorithm is proposed accordingly. Simulation results show that the proposed approach achieves a near-optimal solution.

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Boosting video popularity through keyword suggestion and recommendation systems

Cited by 21 publications

References 32 publications

Intelligent Parallel Mixed Method Approach for Characterising Viral YouTube Videos in Saudi Arabia

Intelligent Parallel Mixed Method Approach for Characterising Viral YouTube Videos in Saudi Arabia

Characterizing popularity dynamics of hot topics using micro-blogs spatio-temporal data

Optimal transmission for scalable video coded streaming in cellular wireless networks with the cooperation of local peer-to-peer network

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