Related papers: Behavioral On-Line Advertising
The problem of detecting terms that can be interesting to the advertiser is considered. If a company has already bought some advertising terms which describe certain services, it is reasonable to find out the terms bought by competing…
Choice decisions made by users of online applications can suffer from biases due to the users' level of engagement. For instance, low engagement users may make random choices with no concern for the quality of items offered. This biased…
Predicting the probability that a user will click on a specific advertisement has been a prevalent issue in online advertising, attracting much research attention in the past decades. As a hot research frontier driven by industrial needs,…
Privacy regulations have led to many websites showing cookie banners to their users. Usually, cookie banners present the user with the option to "accept" or "reject" cookies. Recently, a new form of paywall-like cookie banner has taken hold…
Consumer spending accounts for a large fraction of the US economic activity. Increasingly, consumer activity is moving to the web, where digital traces of shopping and purchases provide valuable data about consumer behavior. We analyze…
While the daily user of digital, Internet-enabled devices has some explicit control over what they read and see, the providers fulfilling searches, offering options, and presenting material are using increasingly sophisticated real-time…
Modeling what makes an advertisement persuasive, i.e., eliciting the desired response from consumer, is critical to the study of propaganda, social psychology, and marketing. Despite its importance, computational modeling of persuasion in…
With the rapid proliferation of multimedia data in the internet, there has been a fast rise in the creation of videos for the viewers. This enables the viewers to skip the advertisement breaks in the videos, using ad blockers and 'skip ad'…
We consider a network of agents. Associated with each agent are her covariate and outcome. Agents influence each other's outcomes according to a certain connection/influence structure. A subset of the agents participate on a platform, and…
Ranking is at the core of many artificial intelligence (AI) applications, including search engines, recommender systems, etc. Modern ranking systems are often constructed with learning-to-rank (LTR) models built from user behavior signals.…
We introduce a new model for online ranking in which the click probability factors into an examination and attractiveness function and the attractiveness function is a linear function of a feature vector and an unknown parameter. Only…
This paper presents models for predicted click-through rates in position auctions that take into account two possibilities that are not normally considered---that the identities of ads shown in other positions may affect the probability…
We study online Bayesian persuasion problems in which an informed sender repeatedly faces a receiver with the goal of influencing their behavior through the provision of payoff-relevant information. Previous works assume that the sender has…
The development of an automatic way to extract user opinions about products, movies, and foods from online social network (OSN) interactions is among the main interests of sentiment analysis and opinion mining studies. Existing approaches…
Forecasting click volume is a key task in digital advertising, influencing both revenue and campaign strategy. Traditional time series models rely solely on numerical data, often overlooking rich contextual information embedded in textual…
Online social networks usage has increased significantly in the last decade and continues to grow in popularity. Multiple social platforms use volunteers as a central component. The behavior of volunteers in volunteer-based networks has…
Online auctions are one of the most fundamental facets of the modern economy and power an industry generating hundreds of billions of dollars a year in revenue. Auction theory has historically focused on the question of designing the best…
Social media have substantially altered the way brands and businesses advertise: Online Social Networks provide brands with more versatile and dynamic channels for advertisement than traditional media (e.g., TV and radio). Levels of…
In this paper, we propose a novel discriminative model for online behavioral analysis with application to emotion state identification. The proposed model is able to extract more discriminative characteristics from behavioral data…
Perceptual ad-blocking is a novel approach that detects online advertisements based on their visual content. Compared to traditional filter lists, the use of perceptual signals is believed to be less prone to an arms race with web…