Tootfinder

Algorithmic Collusion of Pricing and Advertising on E-commerce Platforms
Hangcheng Zhao, Ron Berman
https://arxiv.org/abs/2508.08325 https://arxiv.org/pdf/…

Algorithmic Collusion of Pricing and Advertising on E-commerce Platforms
Online sellers have been adopting AI learning algorithms to automatically make product pricing and advertising decisions on e-commerce platforms. When sellers compete using such algorithms, one concern is that of tacit collusion - the algorithms learn to coordinate on higher than competitive. We empirically investigate whether these concerns are valid when sellers make pricing and advertising decisions together, i.e., two-dimensional decisions. Our empirical strategy is to analyze competition w…

Optimal Boost Design for Auto-bidding Mechanism with Publisher Quality Constraints
Huanyu Yan, Yu Huo, Min Lu, Weitong Ou, Xingyan Shi, Ruihe Shi, Xiaoying Tang
https://arxiv.org/abs/2508.08772

Optimal Boost Design for Auto-bidding Mechanism with Publisher Quality Constraints
Online bidding is crucial in mobile ecosystems, enabling real-time ad allocation across billions of devices to optimize performance and user experience. Improving ad allocation efficiency is a long-standing research problem, as it directly enhances the economic outcomes for all participants in advertising platforms. This paper investigates the design of optimal boost factors in online bidding while incorporating quality value (the impact of displayed ads on publishers' long-term benefits). To a…

Begin oktober kennelijk geen politieke advertenties meer op Facebook, interessant, ook voor de Nederlandse verkiezingen eind oktober, welke partij zou hier het meest last van hebben? (Of maakt het niets uit)
https://about.fb.com/news/2025/07/endi

Ending Political, Electoral and Social Issue Advertising in the EU in Response to Incoming European Regulation
From early October 2025, we will no longer allow political, electoral and social issue ads on our platforms in the EU. This is a difficult decision - one

How candidates evoke identity and issues on TikTok
Sabina Tomkins, Chang Ge, David Rothschild
https://arxiv.org/abs/2509.05310 https://arxiv.org/pdf/2509.0…

How candidates evoke identity and issues on TikTok
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 short-video format and content-driven algorithms, demand unique content. We examine the final six months before the 2024 US Presidential Election to understand how major campaigns used TikTok. We frame our analysis around two political science theories. The fir…

Mobile Gamer Lifetime Value Prediction via Objective Decomposition and Reconstruction
Tianwei Li, Yu Zhao, Yunze Li, Sheng Li
https://arxiv.org/abs/2510.08281 https://

Mobile Gamer Lifetime Value Prediction via Objective Decomposition and Reconstruction
For Internet platforms operating real-time bidding (RTB) advertising service, a comprehensive understanding of user lifetime value (LTV) plays a pivotal role in optimizing advertisement allocation efficiency and maximizing the return on investment (ROI) for advertisement sponsors, thereby facilitating growth of commercialization revenue for the platform. However, the inherent complexity of user LTV distributions induces significant challenges in accurate LTV prediction. Existing state-of-the-ar…

IAB survey: 86% of digital ad buyers use or plan to use generative AI for video ad creation, and expect it will account for 40% of all video ads by 2026 (Matthew Keys/TheDesk.net)
https://thedesk.net/2025/07/iab-generative-ai-ctv-advertising-report/

IAB: Generative AI, connected TV platforms influencing ad production
More than half of advertisers are using generative AI to create spots, the IAB concludes in its latest report.

Smart Fast Finish: Preventing Overdelivery via Daily Budget Pacing at DoorDash
Rohan Garg (Dianxia), Yongjin Xiao (Dianxia), Jason (Dianxia), Yang, Mandar Rahurkar
https://arxiv.org/abs/2509.07929

Smart Fast Finish: Preventing Overdelivery via Daily Budget Pacing at DoorDash
We present a budget pacing feature called Smart Fast Finish (SFF). SFF builds upon the industry standard Fast Finish (FF) feature in budget pacing systems that depletes remaining advertising budget as quickly as possible towards the end of some fixed time period. SFF dynamically updates system parameters such as start time and throttle rate depending on historical ad-campaign data. SFF is currently in use at DoorDash, one of the largest delivery platforms in the US, and is part of its budget pa…

🥠 How candidates evoke identity and issues on TikTok
#media #socialmedia

How candidates evoke identity and issues on TikTok
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 short-video format and content-driven algorithms, demand unique content. We examine the final six months before the 2024 US Presidential Election to understand how major campaigns used TikTok. We frame our analysis around two political science theories. The fir…

Optimal Calibrated Signaling in Digital Auctions
Zhicheng Du, Wei Tang, Zihe Wang, Shuo Zhang
https://arxiv.org/abs/2507.17187 https://arxiv.org/pdf/2507.1…

Optimal Calibrated Signaling in Digital Auctions
In digital advertising, online platforms allocate ad impressions through real-time auctions, where advertisers typically rely on autobidding agents to optimize bids on their behalf. Unlike traditional auctions for physical goods, the value of an ad impression is uncertain and depends on the unknown click-through rate (CTR). While platforms can estimate CTRs more accurately using proprietary machine learning algorithms, these estimates/algorithms remain opaque to advertisers. This information as…

Characterizing and Minimizing Divergent Delivery in Meta Advertising Experiments
Gordon Burtch, Robert Moakler, Brett R. Gordon, Poppy Zhang, Shawndra Hill
https://arxiv.org/abs/2508.21251

Characterizing and Minimizing Divergent Delivery in Meta Advertising Experiments
Many digital platforms offer advertisers experimentation tools like Meta's Lift and A/B tests to optimize their ad campaigns. Lift tests compare outcomes between users eligible to see ads versus users in a no-ad control group. In contrast, A/B tests compare users exposed to alternative ad configurations, absent any control group. The latter setup raises the prospect of divergent delivery: ad delivery algorithms may target different ad variants to different audience segments. This complicates ca…

Data-Driven Analysis of Text-Conditioned AI-Generated Music: A Case Study with Suno and Udio
Luca Casini, Laura Cros Vila, David Dalmazzo, Anna-Kaisa Kaila, Bob L. T. Sturm
https://arxiv.org/abs/2509.11824

Data-Driven Analysis of Text-Conditioned AI-Generated Music: A Case Study with Suno and Udio
Online AI platforms for creating music from text prompts (AI music), such as Suno and Udio, are now being used by hundreds of thousands of users. Some AI music is appearing in advertising, and even charting, in multiple countries. How are these platforms being used? What subjects are inspiring their users? This article answers these questions for Suno and Udio using a large collection of songs generated by users of these platforms from May to October 2024. Using a combination of state-of-the-ar…

SUMMA: A Multimodal Large Language Model for Advertisement Summarization
Weitao Jia, Shuo Yin, Zhoufutu Wen, Han Wang, Zehui Dai, Kun Zhang, Zhenyu Li, Tao Zeng, Xiaohui Lv
https://arxiv.org/abs/2508.20582

SUMMA: A Multimodal Large Language Model for Advertisement Summarization
Understanding multimodal video ads is crucial for improving query-ad matching and relevance ranking on short video platforms, enhancing advertising effectiveness and user experience. However, the effective utilization of multimodal information with high commercial value still largely constrained by reliance on highly compressed video embeddings-has long been inadequate. To address this, we propose SUMMA (the abbreviation of Summarizing MultiModal Ads), a multimodal model that automatically proc…