Identifying user profile using facebook photos

Abstract

Apart from text messages, photo posting is a popular function of Facebook. The uploaded photos are of various natures, including selfie, outdoor scenes, food, etc. In this paper, we employ state-ofthe-art computer vision techniques to analyze image content and establish the relationship between user profile and the type of photos posted. We collected photos from 32 Facebook users. We then applied techniques such as face detection, scene understanding and saliency map identification to gather information for automatic image tagging and classification. Grouping of users can be achieved either by tag statistics or photo classes. Characteristics of each group can be further investigated based on the results of hierarchical clustering. We wish to identify profiles of different users and respond to questions such as the type of photos most frequently posted, gender differentiation in photo posting behavior and user classification according to image content, which will promote our understanding of photo uploading activities on Facebook. © 2017 ACM.