Over 1.1 million tweets were collected using the four hashtags (# health, # fitness, # diet, # weightloss) from August 2018 to January 2019 for the purpose of understanding obesity-related image sharing practice in Twitter. Of these tweets, more than 200,000 (17.76%) had images, which were shared by more than 60,000 unique twitter users (22.13%). Over 130,000 unique images were computationally processed by applying a very deep VGG16 model (convolutional neural network) and 967 unique labels were used to describe objects within the images extracted from obesity related tweets. Informational content was most frequently re-shared, followed by images of individuals posing, comical content, commercial content, physical activities, and motivational quotes. Although a general deep learning model provided high level insights into the image sharing activity on Twitter, manual analysis revealed that a tailored model is needed to learn detailed information.