@inbook{addd2700ef3b47f2b6ffa209f3c8cdac,
title = "Using big data and AI to examine product engagement in social media influencer posts",
abstract = "In this paper we explore the recent phenomenon of influencer marketing in social media. Posts of the top-75 social media influencers on Instagram were analyzed over a 12-month period. The types of products in posts were identified for 226, 801 images using an Inception V3 convolutional neural network (CNN). Products were then compared by level of engagement achieved to explore efficiency of engagement by product and influencer type. Results indicated that general influencers performed best, while travel influencers achieved greater overall engagement independent across product types, and specific types of influencers achieved better engagement for particular product types. The research points to the importance of fit between a product and influencer type in achieving impact via influencer marketing. Our findings offer help to brands in selecting influencers to endorse their products.",
keywords = "Big data, Convolutional neural network, Engagement, Influencer, Products, Social media",
author = "Stuart Barnes and Richard Rutter",
year = "2019",
month = nov,
doi = "10.1109/ICITISEE48480.2019.9003991",
language = "English",
series = "2019 4th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "35--39",
booktitle = "2019 4th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2019",
address = "United States",
note = "4th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2019 ; Conference date: 20-11-2019 Through 21-11-2019",
}