_Poster: Adaptive Ad SequencingMar 12, 2020 Omid Rafieian, University of Washington
_Poster: Brand Suitability: Understanding the Unintended Consequences of Adjacent Content on Brands in Digital EnvironmentsMar 12, 2020 Lauren Grewal, Dartmouth College
Lauren Grewal, Andrew T. Stephen, and Prasad Vana examine whether brands experience negative spillover effects from “unsafe” or “unsuitable” content that ends up being adjacent to their ads across various digital platforms (and if so, why this spillover occurs).
_Poster: Optimal Bidding and Pricing in Display Advertising MarketsMar 12, 2020 Hana Choi, University of Rochester
Hana Choi studies advertisers’ ad demand responses to the changes in reserve prices (floors) when ad impressions are sold and bought through real-time auctions.
A Natural Language Processing Approach to Predicting the Persuasiveness of Marketing CommunicationsFeb 21, 2020 Siham El Kihal, A. Selin Atalay, and Florian Ellsaesser, 2020, 20-104
This study uses a natural language processing approach (convolutional neural networks) to measure content and synactic complexity and predict persuasiveness of messaging. Dataset includes 134 debates (with 129,480 sentences on different topics), attitude polls from the audience before and after debates, and a follow-up experiment.
Generalizable and Robust TV Advertising EffectsJan 3, 2020 Bradley T. Shapiro, Günter J. Hitsch, and Anna E. Tuchman, 2020, 20-100
How much does advertising generally work? Less than the published literature shows, according to this study. Researchers used Nielsen data to estimate advertising elasticities brand by brand, carefully controlling for confounding factors. Their findings offer an important caution to decision makers.
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