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.

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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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ID Code: 91191
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
DOI: 10.1145/2808797.2808851
ISBN: 9781450338547
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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