Automatically Mapping Ad Targeting Criteria between Online Ad Platforms
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2021-01-05
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940
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Targeting criteria in online advertising differ across platforms and frequently change. Because advertisers are increasingly taking a multi-channel approach to online marketing, there is a need to automatically map the targeting criteria between ad platforms. In this research, we test two algorithmic approaches Word2Vec and WordNet for mapping ad targeting criteria between Google Ads and Facebook Ads. The results show that Word2Vec outperforms WordNet in finding matches (97.5% vs. 63.6%), covering different criteria (20.0% vs. 13.5%), and having higher similarity scores. However, WordNet outperforms Word2Vec in expert evaluation (Mean Opinion Score = 3.05 vs. 2.46), implying that algorithmic performance metrics may not correlate with expert ratings. Overall, due to specific requirements for mapping ad targeting criteria, automatic means do not (at least yet) offer a satisfactory solution for replacing human judgment.
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Big Data and Analytics: Pathways to Maturity, automation, online advertising, targeting
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9 pages
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Proceedings of the 54th Hawaii International Conference on System Sciences
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Attribution-NonCommercial-NoDerivatives 4.0 International
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