Combining propensity and influence models for product adoption prediction
Verenich, Ilya, Kikas, Riivo, Dumas, Marlon, & Melnikov, Dmitri (2015) Combining propensity and influence models for product adoption prediction. In Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ACM, Paris, France, pp. 49-56.
This paper studies the problem of selecting users in an online social network for targeted advertising so as to maximize the adoption of a given product. In previous work, two families of models have been considered to address this problem: direct targeting and network-based targeting. The former approach targets users with the highest propensity to adopt the product, while the latter approach targets users with the highest influence potential – that is users whose adoption is most likely to be followed by subsequent adoptions by peers. This paper proposes a hybrid approach that combines a notion of propensity and a notion of influence into a single utility function. We show that targeting a fixed number of high-utility users results in more adoptions than targeting either highly influential users or users with high propensity.
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|Item Type:||Conference Paper|
|Subjects:||Australian and New Zealand Standard Research Classification > LANGUAGES COMMUNICATION AND CULTURE (200000) > COMMUNICATION AND MEDIA STUDIES (200100) > Communication Studies (200101)|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology
Current > Schools > School of Information Systems
|Copyright Owner:||Copyright 2015 ACM|
|Deposited On:||11 Dec 2015 02:50|
|Last Modified:||14 Dec 2015 00:21|
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