TSA: A Truthful Mechanism for Social Advertising

Grubenmann, Tobias; Cheng, Reynold C.K.; Lakshmanan, Laks V.S.

Abstract

Social advertising exploits the interconnectivity of users in social networks to spread advertisement and generate user engagements. A lot of research has focused on how to select the best subset of users in a social network to maximize the number of engagements or the generated revenue of the advertisement. However, there is a lack of studies that consider the advertiser's value-per-engagement, i.e., how much an advertiser is maximally willing to pay for each engagement. Prior work on social advertising is based on the classical framework of influence maximization. In this paper, we propose a model where advertisers compete in an auction mechanism for the influential users within a social network. The auction mechanism can dynamically determine payments for advertisers based on their reported values. The main problem is to find auctions which incentivize advertisers to truthfully reveal their values, and also respect each advertiser's budget constraint. To tackle this problem, we propose a new truthful auction mechanism called TSA. Compared with existing approaches on real and synthetic datasets, TSA performs significantly better in terms of generated revenue.

Citation

Grubenmann, T., Cheng, R. C., & Lakshmanan, L. V. (2020). TSA: A Truthful Mechanism for Social Advertising. In WSDM '20: Proceedings of the 13th International Conference on Web Search and Data Mining (214-222). https://doi.org/10.1145/3336191.3371809

• Conference Name: WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining
• Conference Location: Houston TX USA
• Start Date: Feb 3, 2020
• End Date: Feb 7, 2020
• Online Publication Date: Jan 22, 2020
• Publication Date: 2020-01
• Deposit Date: Jun 8, 2023
• Publisher: Association for Computing Machinery (ACM)
• Pages: 214-222
• Book Title: WSDM '20: Proceedings of the 13th International Conference on Web Search and Data Mining
• ISBN: 9781450368223
• DOI: https://doi.org/10.1145/3336191.3371809