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Understanding what drives popularity is critical in today's digital service economy, where content creators compete for consumer attention. Prior studies have primarily emphasized the role of content features, yet creators often misjudge…

Computation and Language · Computer Science 2025-10-14 Jingyi Wu , Junying Liang

Recognising human activities from streaming videos poses unique challenges to learning algorithms: predictive models need to be scalable, incrementally trainable, and must remain bounded in size even when the data stream is arbitrarily…

Machine Learning · Statistics 2016-10-06 Rocco De Rosa , Ilaria Gori , Fabio Cuzzolin , Barbara Caputo , Nicolò Cesa-Bianchi

The ability to predict the size of information cascades in online social networks is crucial for various applications, including decision-making and viral marketing. However, traditional methods either rely on complicated time-varying…

Social and Information Networks · Computer Science 2023-06-22 Wu Leilei , Yi Lingling , Ren Xiao-Long , {Lü} Linyuan

Access to online contents represents a large share of the Internet traffic. Most such contents are multimedia items which are user-generated, i.e., posted online by the contents' owners. In this paper we focus on how those who provide…

Social and Information Networks · Computer Science 2013-12-04 Francesco De Pellegrini , Alexandre Reiffers , Eitan Altman

The recent proliferation of short form video social media sites such as TikTok has been effectively utilized for increased visibility, communication, and community connection amongst trans/nonbinary creators online. However, these same…

Human-Computer Interaction · Computer Science 2025-01-29 Maxyn Leitner , Rebecca Dorn , Fred Morstatter , Kristina Lerman

We study how TikTok affects demand for music on paid streaming platforms. We use Universal Music Group's (UMG) global withdrawal of its catalog from TikTok as a quasi-natural experiment. Recent work using this setting reaches mixed…

General Economics · Economics 2026-05-26 Daniel Winkler , Christian Hotz-Behofsits , Nils Wlömert , Dominik Papies , Jūra Liaukonytė

Constrained $k$-submodular maximization is a general framework that captures many discrete optimization problems such as ad allocation, influence maximization, personalized recommendation, and many others. In many of these applications,…

Data Structures and Algorithms · Computer Science 2023-05-26 Fabian Spaeh , Alina Ene , Huy L. Nguyen

It remains unknown whether personalized recommendations increase or decrease the diversity of content people consume. We present results from a randomized field experiment on Spotify testing the effect of personalized recommendations on…

Social and Information Networks · Computer Science 2020-03-19 David Holtz , Benjamin Carterette , Praveen Chandar , Zahra Nazari , Henriette Cramer , Sinan Aral

Social media platforms are increasingly central to campaign communication, with both paid (advertising) and earned (organic) posts used for fundraising, mobilization, and persuasion. TikTok, and other short-form video platforms, with its…

Computers and Society · Computer Science 2025-09-09 Sabina Tomkins , Chang Ge , David Rothschild

Video watching had emerged as one of the most frequent media activities on the Internet. Yet, little is known about how users watch online video. Using two distinct YouTube datasets, a set of random YouTube videos crawled from the Web and a…

Human-Computer Interaction · Computer Science 2017-05-18 Minsu Park , Mor Naaman , Jonah Berger

We propose a novel framework for predicting the factuality of reporting of news media outlets by studying the user attention cycles in their YouTube channels. In particular, we design a rich set of features derived from the temporal…

Computation and Language · Computer Science 2021-08-31 Krasimira Bozhanova , Yoan Dinkov , Ivan Koychev , Maria Castaldo , Tommaso Venturini , Preslav Nakov

Personalization, including both self-selected and pre-selected, is inevitable when tremendous amounts of media content are available. Personalization, which is believed to cause people to consume fewer diverse contents, can lead to…

Computers and Society · Computer Science 2018-11-01 Kota Kakiuchi , Fujio Toriumi , Masanori Takano , Kazuya Wada , Ichiro Fukuda

Recommendation algorithms are known to suffer from popularity bias; a few popular items are recommended frequently while the majority of other items are ignored. These recommendations are then consumed by the users, their reaction will be…

Information Retrieval · Computer Science 2020-07-28 Masoud Mansoury , Himan Abdollahpouri , Mykola Pechenizkiy , Bamshad Mobasher , Robin Burke

With the uptake of algorithmic personalization in the news domain, news organizations increasingly trust automated systems with previously considered editorial responsibilities, e.g., prioritizing news to readers. In this paper we study an…

Information Retrieval · Computer Science 2020-04-22 Feng Lu , Anca Dumitrache , David Graus

With the increasing use of social media data for health-related research, the credibility of the information from this source has been questioned as the posts may originate from automated accounts or "bots". While automatic bot detection…

Computation and Language · Computer Science 2019-10-01 Anahita Davoudi , Ari Z. Klein , Abeed Sarker , Graciela Gonzalez-Hernandez

Multimedia online platforms (e.g., Amazon, TikTok) have greatly benefited from the incorporation of multimedia (e.g., visual, textual, and acoustic) content into their personal recommender systems. These modalities provide intuitive…

Information Retrieval · Computer Science 2024-03-12 Wei Wei , Jiabin Tang , Yangqin Jiang , Lianghao Xia , Chao Huang

Multi-media increases engagement and is increasingly prevalent in online content including news, web blogs, and social media, however, it may not always be beneficial to users. To determine what types of media users actually wanted, we…

Human-Computer Interaction · Computer Science 2023-04-25 Hayeong Song , Jennifer Healey , Alexa Siu , Curtis Wigington , John Stasko

The rise of a trending topic on Twitter or Facebook leads to the temporal emergence of a set of users currently interested in that topic. Given the temporary nature of the links between these users, being able to dynamically identify…

Social and Information Networks · Computer Science 2017-07-28 Lorena Recalde , David F. Nettleton , Ricardo Baeza-Yates , Ludovico Boratto

Accurately estimating how users respond to moderation interventions is paramount for developing effective and user-centred moderation strategies. However, this requires a clear understanding of which user characteristics are associated with…

Computers and Society · Computer Science 2025-10-24 Benedetta Tessa , Alejandro Moreo , Stefano Cresci , Tiziano Fagni , Fabrizio Sebastiani

Short form content has permeated into the video creator space over the past few years, led by industry leading products such as TikTok, YouTube Shorts and Instagram Reels. YouTube in particular was previously synonymous with being the main…

Social and Information Networks · Computer Science 2024-04-09 Prajit T. Rajendran , Kevin Creusy , Vivien Garnes
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