Micro-Influencer Recommendation by Multi-Perspective Account Representation Learning
IEEE Transactions on Multimedia(2023)
摘要
Influencer marketing is emerging as a new marketing method, changing the marketing strategies of brands profoundly. In order to help brands find suitable micro-influencers as marketing partners, the micro-influencer recommendation is regarded as an indispensable part of influencer marketing. However, previous works only focus on modeling the
individual image
of brands/micro-influencers, which is insufficient to represent the characteristics of brands/micro-influencers over the marketing scenarios. In this case, we propose a micro-influencer ranking joint learning framework which models brands/micro-influencers from the perspective of
individual image
,
target audiences
, and
cooperation preferences
. Specifically, to model accounts’
individual image
, we extract topics information and images semantic information from historical content information, and fuse them to learn the account content representation. We introduce
target audiences
as a new kind of marketing role in the micro-influencer recommendation, in which audiences information of brand/micro-influencer is leveraged to learn the multi-modal account audiences representation. Afterward, we build the attribute co-occurrence graph network to mine
cooperation preferences
from social media interaction information. Based on account attributes, the
cooperation preferences
between brands and micro-influencers are refined to attributes’ co-occurrence information. The attribute node embeddings learned in the attribute co-occurrence graph network are further utilized to construct the account attribute representation. Finally, the global ranking function is designed to generate ranking scores for all brand-micro-influencer pairs from the three perspectives jointly. The extensive experiments on a publicly available dataset demonstrate the effectiveness of our proposed model over the state-of-the-art methods.
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关键词
Influencer marketing,multi-modal,social media information
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