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Improving Post-Click User Engagement on Native Ads via Survival Analysis

Authors:

Nicola Barbieri,

Fabrizio Silvestri,

Mounia LalmasAuthors Info & Claims

WWW '16: Proceedings of the 25th International Conference on World Wide Web

Pages 761 - 770

https://doi.org/10.1145/2872427.2883092

Published: 11 April 2016 Publication History

Abstract

In this paper we focus on estimating the post-click engagement on native ads by predicting the dwell time on the corresponding ad landing pages. To infer relationships between features of the ads and dwell time we resort to the application of survival analysis techniques, which allow us to estimate the distribution of the length of time that the user will spend on the ad. This information is then integrated into the ad ranking function with the goal of promoting the rank of ads that are likely to be clicked and consumed by users (dwell time greater than a given threshold). The online evaluation over live traffic shows that considering post-click engagement has a consistent positive effect on both CTR, decreases the number of bounces and increases the average dwell time, hence leading to a better user post-click experience.

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Cited By

Robinson TTax NMudd RGuy I(2024)Active learning with biased non-response to label requestsData Mining and Knowledge Discovery10.1007/s10618-024-01026-x38:4(2117-2140)Online publication date: 25-May-2024
https://doi.org/10.1007/s10618-024-01026-x
Chen XDutta AErnala SIoannidis SKalyanaraman SNir IWeinsberg U(2023)Gateway Entities in Problematic TrajectoriesProceedings of the ACM Web Conference 202310.1145/3543507.3583283(2840-2851)Online publication date: 30-Apr-2023
https://dl.acm.org/doi/10.1145/3543507.3583283
Liu CWu SJiang DYu ZWong H(2023)View-Aware Collaborative Learning for Survival Prediction and Subgroup IdentificationIEEE Transactions on Biomedical Engineering10.1109/TBME.2022.319005070:1(307-317)Online publication date: Jan-2023
https://doi.org/10.1109/TBME.2022.3190050
Show More Cited By

Index Terms

Improving Post-Click User Engagement on Native Ads via Survival Analysis
1. Information systems
  1. Information systems applications
    1. Computational advertising
  2. World Wide Web
    1. Online advertising
2. Mathematics of computing
  1. Probability and statistics
    1. Statistical paradigms
      1. Survival analysis

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Information & Contributors

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Published In

cover image ACM Other conferences

WWW '16: Proceedings of the 25th International Conference on World Wide Web

April 2016

1482 pages

ISBN:9781450341431

General Chairs:
Jacqueline Bourdeau
Tele-university (TELUQ), Montreal, QC, Canada
,
Jim A. Hendler
Rensselaer Polytechnic Institute, Troy, NY, USA
,
Roger Nkambou Nkambou
Université du Québec à Montréal, Montreal, QC, Canada
,
Program Chairs:
Ian Horrocks
University of Oxford, UK
,
Ben Y. Zhao
University of California at Santa Barbara, CA, USA

Copyright © 2016 Copyright is held by the International World Wide Web Conference Committee (IW3C2).

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IW3C2: International World Wide Web Conference Committee

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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International World Wide Web Conferences Steering Committee

Republic and Canton of Geneva, Switzerland

Publication History

Published: 11 April 2016

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WWW '16

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IW3C2

WWW '16: 25th International World Wide Web Conference

April 11 - 15, 2016

Québec, Montréal, Canada

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WWW '16 Paper Acceptance Rate 115 of 727 submissions, 16%;

Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Citations

Cited By

Robinson TTax NMudd RGuy I(2024)Active learning with biased non-response to label requestsData Mining and Knowledge Discovery10.1007/s10618-024-01026-x38:4(2117-2140)Online publication date: 25-May-2024
https://doi.org/10.1007/s10618-024-01026-x
Chen XDutta AErnala SIoannidis SKalyanaraman SNir IWeinsberg U(2023)Gateway Entities in Problematic TrajectoriesProceedings of the ACM Web Conference 202310.1145/3543507.3583283(2840-2851)Online publication date: 30-Apr-2023
https://dl.acm.org/doi/10.1145/3543507.3583283
Liu CWu SJiang DYu ZWong H(2023)View-Aware Collaborative Learning for Survival Prediction and Subgroup IdentificationIEEE Transactions on Biomedical Engineering10.1109/TBME.2022.319005070:1(307-317)Online publication date: Jan-2023
https://doi.org/10.1109/TBME.2022.3190050
Yao ZKong DLu MBai XYang JXiong H(2023)Multi-View Multi-Task Campaign Embedding for Cold-Start Conversion Rate ForecastingIEEE Transactions on Big Data10.1109/TBDATA.2022.31621509:1(280-293)Online publication date: 1-Feb-2023
https://doi.org/10.1109/TBDATA.2022.3162150
Oubelmouh YFargon FDe Runz CSoulet AVeillon C(2023)Identifying Survival-Changing Sequential Patterns for Employee Attrition Analysis2023 IEEE 10th International Conference on Data Science and Advanced Analytics (DSAA)10.1109/DSAA60987.2023.10302498(1-10)Online publication date: 9-Oct-2023
https://doi.org/10.1109/DSAA60987.2023.10302498
Yang JZhan DKoyejo SMohamed SAgarwal ABelgrave DCho KOh A(2022)Generalized delayed feedback model with post-click information in recommender systemsProceedings of the 36th International Conference on Neural Information Processing Systems10.5555/3600270.3602169(26192-26203)Online publication date: 28-Nov-2022
https://dl.acm.org/doi/10.5555/3600270.3602169
Kitada SIyatomi HSeki Y(2022)Ad Creative Discontinuation Prediction with Multi-Modal Multi-Task Neural Survival NetworksApplied Sciences10.3390/app1207359412:7(3594)Online publication date: 1-Apr-2022
https://doi.org/10.3390/app12073594
Zhang TTan JCai XWang JLi FSun J(2022)SA-LSMProceedings of the VLDB Endowment10.14778/3547305.354732015:10(2161-2174)Online publication date: 1-Jun-2022
https://dl.acm.org/doi/10.14778/3547305.3547320
Liu CCao WWu SShen WJiang DYu ZWong H(2022)Asymmetric Graph-Guided Multitask Survival Analysis With Self-Paced LearningIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2020.302845333:2(654-666)Online publication date: Feb-2022
https://doi.org/10.1109/TNNLS.2020.3028453
Isa A(2022)Computational Intelligence Methods for Cancer Survival PredictionComputational Intelligence in Oncology10.1007/978-981-16-9221-5_7(123-141)Online publication date: 2-Mar-2022
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