Related papers: A Data-driven Study of View Duration on YouTube
Sentiment Analysis is currently a vital area of research. With the advancement in the use of the internet, the creation of social media, websites, blogs, opinions, ratings, etc. has increased rapidly. People express their feedback and…
YouTube, a world-famous video sharing website, maintains a list of the top trending videos on the platform. Due to its huge amount of users, it enables researchers to understand people's preference by analyzing the trending videos. Trending…
The relationship between content production and consumption on algorithm-driven platforms like YouTube plays a critical role in shaping ideological behaviors. While prior work has largely focused on user behavior and algorithmic…
Sentiment analysis or opinion mining is the field of study related to analyze opinions, sentiments, evaluations, attitudes, and emotions of users which they express on social media and other online resources. The revolution of social media…
Consumption of YouTube news videos significantly shapes public opinion and political narratives. While prior works have studied the longitudinal dissemination dynamics of YouTube News videos across extended periods, limited attention has…
The vast majority of YouTube videos never become popular, languishing in obscurity with few views, no likes, and no comments. We use information theoretical measures based on entropy to examine how time series distributions of common…
Energy production and management face significant political, economic, and environmental challenges, yet the rise in information consumption through social media undermines the availability of reliable knowledge to the general public. This…
As a YouTube channel grows, each video can potentially collect enormous amounts of comments that provide direct feedback from the viewers. These comments are a major means of understanding viewer expectations and improving channel…
Influencer marketing has become a widely used strategy for reaching customers. Despite growing interest among influencers and brand partners in predicting engagement with influencer videos, there has been little research on the relative…
In the video recommendation, watch time is commonly adopted as an indicator of user interest. However, watch time is not only influenced by the matching of users' interests but also by other factors, such as duration bias and noisy…
YouTube, a widely popular online platform, has transformed the dynamics of con-tent consumption and interaction for users worldwide. With its extensive range of content crea-tors and viewers, YouTube serves as a hub for video sharing,…
YouTube introduced the Shorts video format in 2021, allowing users to upload short videos that are prominently displayed on its website and app. Despite having such a large visual footprint, there are no studies to date that have looked at…
Web video is often used as a source of data in various fields of study. While specialized subsets of web video, mainly earmarked for dedicated purposes, are often analyzed in detail, there is little information available about the…
Short-form video platforms such as YouTube Shorts increasingly shape how information is consumed, yet the effects of engagement-driven algorithms on content exposure remain poorly understood. This study investigates how different viewing…
Understanding and modeling the popularity of User Generated Content (UGC) short videos on social media platforms presents a critical challenge with broad implications for content creators and recommendation systems. This study delves deep…
This study explores the interplay between YouTube engagement metrics and the academic impact of cited publications within video descriptions, amid declining trust in traditional journalism and increased reliance on social media for…
The rapid growth of YouTube Shorts, now serving over 2 billion monthly users, reflects a global shift toward short-form video as a dominant mode of online content consumption. This study investigates algorithmic bias in YouTube Shorts'…
Short-format videos have exploded on platforms like TikTok, Instagram, and YouTube. Despite this, the research community lacks large-scale empirical studies into how people engage with short-format videos and the role of recommendation…
With the continuous increase of internet usage in todays time, everyone is influenced by this source of the power of technology. Due to this, the rise of applications and games Is unstoppable. A major percentage of our population uses these…
In this work, we propose a regression method to predict the popularity of an online video based on temporal and visual cues. Our method uses Support Vector Regression with Gaussian Radial Basis Functions. We show that modelling popularity…