Who is the Mr. Right for your brand? - Discovering brand key assets via multi-modal asset-aware projection

Yang LIU, Tobey H. Ko, Zhonglei Gu

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

Following the rising prominence of online social networks, we observe an emerging trend for brands to adopt influencer marketing, embracing key opinion leaders (KOLs) to reach potential customers (PCs) online. Owing to the growing strategic importance of these brand key assets, this paper presents a novel feature extraction method named Multi-modal Asset-aware Projection (M2A2P) to learn a discriminative subspace from the high-dimensional multi-modal social media data for effective brand key asset discovery. By formulating a new asset-aware discriminative information preserving criterion, M2A2P differentiates with the existing multi-model feature extraction algorithms in two pivotal aspects: 1) We consider brand's highly imbalanced class interest steering towards the KOLs and PCs over the irrelevant users; 2) We consider a common observation that a user is not exclusive to a single class (e.g. a KOL can also be a PC). Experiments on a real-world apparel brand key asset dataset validate the effectiveness of the proposed method.

Original languageEnglish
Title of host publication41st International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018
PublisherAssociation for Computing Machinery, Inc
Pages1113-1116
Number of pages4
ISBN (Electronic)9781450356572
DOIs
Publication statusPublished - 27 Jun 2018
Event41st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018 - Ann Arbor, United States
Duration: 8 Jul 201812 Jul 2018

Publication series

Name41st International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018

Conference

Conference41st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018
Country/TerritoryUnited States
CityAnn Arbor
Period8/07/1812/07/18

Scopus Subject Areas

  • Software
  • Computer Graphics and Computer-Aided Design
  • Information Systems

User-Defined Keywords

  • Brand key asset discovery
  • Key opinion leader
  • Multi-modal asset-aware projection
  • Potential customer

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