Evaluating the use of Instagram images color histograms and hashtags sets for automatic image annotation

Frontiers in Big Data

Big Data

Constantinos Djouvas¹  Stamatios Giannoulakis¹  Nicolas Tsapatsoulis² 

[1] Department of Communication and Internet Studies, Cyprus University of Technology, Limassol, Cyprus;Department of Public Communication, Cyprus University of Technology, Limassol, Cyprus;

关键词: Instagram hashtags;    Instagram images;    histogram;    Bhattacharyya distance;    word embedding;    automatic image annotation;   

DOI  :  10.3389/fdata.2023.1149523

 received in 2023-01-22, accepted in 2023-06-06,  发布年份 2023

来源: Frontiers

【 摘 要 】

Color similarity has been a key feature for content-based image retrieval by contemporary search engines, such as Google. In this study, we compare the visual content information of images, obtained through color histograms, with their corresponding hashtag sets in the case of Instagram posts. In previous studies, we had concluded that less than 25% of Instagram hashtags are related to the actual visual content of the image they accompany. Thus, the use of Instagram images' corresponding hashtags for automatic image annotation is questionable. In this study, we are answering this question through the computational comparison of images' low-level characteristics with the semantic and syntactic information of their corresponding hashtags. The main conclusion of our study on 26 different subjects (concepts) is that color histograms and filtered hashtag sets, although related, should be better seen as a complementary source for image retrieval and automatic image annotation.

【 授权许可】

Unknown   
Copyright © 2023 Giannoulakis, Tsapatsoulis and Djouvas.