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News articles are extremely time sensitive by nature. There is also intense competition among news items to propagate as widely as possible. Hence, the task of predicting the popularity of news items on the social web is both interesting…

计算机与社会 · 计算机科学 2012-02-07 Roja Bandari , Sitaram Asur , Bernardo A. Huberman

Predicting the popularity of news article is a challenging task. Existing literature mostly focused on article contents and polarity to predict popularity. However, existing research has not considered the users' preference towards a…

社会与信息网络 · 计算机科学 2019-01-29 Roshni Chakraborty , Abhijeet Kharat , Apalak Khatua , Sourav Kumar Dandapat , Joydeep Chandra

Popularity of content in social media is unequally distributed, with some items receiving a disproportionate share of attention from users. Predicting which newly-submitted items will become popular is critically important for both…

计算机与社会 · 计算机科学 2010-04-30 Kristina Lerman , Tad Hogg

Predicting the future popularity of online content is highly important in many applications. Preferential attachment phenomena is encountered in scale free networks.Under it's influece popular items get more popular thereby resulting in…

信息检索 · 计算机科学 2016-04-06 Khushnood Abbas , Shang Mingsheng , Luo Xin

Popularity of content in social media is unequally distributed, with some items receiving a disproportionate share of attention from users. Predicting which newly-submitted items will become popular is critically important for both hosts of…

计算机与社会 · 计算机科学 2010-10-04 Kristina Lerman , Tad Hogg

We here present a simple and effective model to predict the popularity of web content. Our solution, which is the winner of two of the three tasks of the ECML/PKDD 2014 Predictive Analytics Challenge, aims at predicting user engagement…

社会与信息网络 · 计算机科学 2014-09-01 Flavio Figueiredo , Marcos André Gonçalves , Jussara M. Almeida

Today, users are reading the news through social platforms. These platforms are built to facilitate crowd engagement, but not necessarily disseminate useful news to inform the masses. Hence, the news that is highly engaged with may not be…

社会与信息网络 · 计算机科学 2017-11-07 Benjamin D. Horne , Sibel Adali

Can we predict the future popularity of a song, movie or tweet? Recent work suggests that although it may be hard to predict an item's popularity when it is first introduced, peeking into its early adopters and properties of their social…

社会与信息网络 · 计算机科学 2016-04-01 Benjamin Shulman , Amit Sharma , Dan Cosley

We present a method for accurately predicting the long time popularity of online content from early measurements of user access. Using two content sharing portals, Youtube and Digg, we show that by modeling the accrual of views and votes on…

计算机与社会 · 计算机科学 2008-11-06 Gabor Szabo , Bernardo A. Huberman

One of the approaches to the solution of the navigation problem in current information flows is ranking the documents according to their popularity level. The definition of local and global news popularity which is based on the number of…

信息论 · 计算机科学 2008-12-18 D. V. Lande , S. M. Braichevskii , A. T. Darmokhval , A. A. Snarskii

Predicting the popularity of scientific publications has attracted many attentions from various disciplines. In this paper, we focus on the popularity prediction problem of scientific papers, and propose an age-based diffusion (AD) model to…

数字图书馆 · 计算机科学 2020-10-19 Yanbo Zhou , Qu Li , Xuhua Yang , Hongbing cheng

This paper aims to show how some popular topics on social networks can be used to predict online newspaper views, related to the topics. Newspapers site and many social networks, become a good source of data to analyse and explain complex…

Predicting the popularity of items in rating networks is an interesting but challenging problem. This is especially so when an item has first appeared and has received very few ratings. In this paper, we propose a novel approach to…

社会与信息网络 · 计算机科学 2015-09-18 J. Liebig , A. Rao

Predicting popularity of social media videos before they are published is a challenging task, mainly due to the complexity of content distribution network as well as the number of factors that play part in this process. As solving this task…

计算机视觉与模式识别 · 计算机科学 2018-04-27 Adam Bielski , Tomasz Trzcinski

Personalized news recommendation methods are widely used in online news services. These methods usually recommend news based on the matching between news content and user interest inferred from historical behaviors. However, these methods…

信息检索 · 计算机科学 2021-06-11 Tao Qi , Fangzhao Wu , Chuhan Wu , Yongfeng Huang

Social networks offer a ready channel for fake and misleading news to spread and exert influence. This paper examines the performance of different reputation algorithms when applied to a large and statistically significant portion of the…

Several factors influence the popularity of content on social media, including the what, when, and who of a post. Of these factors, the what and when of content are easiest to customize in order to maximize viewership and reach. Further,…

社会与信息网络 · 计算机科学 2021-12-24 Evan Weissburg , Arya Kumar , Paramveer Dhillon

With the ever decreasing attention span of contemporary Internet users, the title of online content (such as a news article or video) can be a major factor in determining its popularity. To take advantage of this phenomenon, we propose a…

计算与语言 · 计算机科学 2017-07-24 Wociech Stokowiec , Tomasz Trzcinski , Krzysztof Wolk , Krzysztof Marasek , Przemyslaw Rokita

Multiple studies have focused on predicting the prospective popularity of an online document as a whole, without paying attention to the contributions of its individual parts. We introduce the task of proactively forecasting popularities of…

计算与语言 · 计算机科学 2023-01-03 Sayar Ghosh Roy , Anshul Padhi , Risubh Jain , Manish Gupta , Vasudeva Varma

With a growing number of social apps, people have become increasingly willing to share their everyday photos and events on social media platforms, such as Facebook, Instagram, and WeChat. In social media data mining, post popularity…

社会与信息网络 · 计算机科学 2019-01-23 Zhongping Zhang , Tianlang Chen , Zheng Zhou , Jiaxin Li , Jiebo Luo
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