TY - JOUR
T1 - Creating, Metavoicing, and Propagating
T2 - A Road Map for Understanding User Roles in Computational Advertising
AU - Liu-Thompkins, Yuping
AU - Maslowska, Ewa
AU - Ren, Yuqing
AU - Kim, Hyejin
N1 - Publisher Copyright:
© 2020 The Author(s). Published with license by Taylor and Francis Group, LLC.
PY - 2020/8/7
Y1 - 2020/8/7
N2 - Over the past two decades, everyday users have become a prominent force in the advertising landscape. They actively participate in conversations with and about brands by creating, amplifying, and interacting with brand-related messages. These user activities generate large volumes of structured and unstructured data that advertisers can mine to understand consumer interests and preferences. In this article, we survey insights from the user-generated content literature through the computational advertising lens to offer a road map for future research. Specifically, we discuss three roles that users play—as creators, metavoicers, and propagators. For each role, we present key research areas that can benefit from a computational approach, identify the opportunities and challenges, and propose questions for future research. We also discuss the practical implications of applying computational methods to study users and user-generated content for advertisers.
AB - Over the past two decades, everyday users have become a prominent force in the advertising landscape. They actively participate in conversations with and about brands by creating, amplifying, and interacting with brand-related messages. These user activities generate large volumes of structured and unstructured data that advertisers can mine to understand consumer interests and preferences. In this article, we survey insights from the user-generated content literature through the computational advertising lens to offer a road map for future research. Specifically, we discuss three roles that users play—as creators, metavoicers, and propagators. For each role, we present key research areas that can benefit from a computational approach, identify the opportunities and challenges, and propose questions for future research. We also discuss the practical implications of applying computational methods to study users and user-generated content for advertisers.
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U2 - 10.1080/00913367.2020.1795758
DO - 10.1080/00913367.2020.1795758
M3 - Article
AN - SCOPUS:85089108522
SN - 0091-3367
VL - 49
SP - 394
EP - 410
JO - Journal of Advertising
JF - Journal of Advertising
IS - 4
ER -