Understanding and classifying image tweets

Social media platforms now allow users to share images alongside their textual posts. These image tweets make up a fast-growing percentage of tweets, but have not been studied in depth unlike their text-only counterparts. We study a large corpus of image tweets in order to un-cover what people post about and the correlation between the tweet’s image and its text. We show that an impor-tant functional distinction is between visually-relevant and visually-irrelevant tweets, and that we can successfully build an automated classifier utilizing text, image and social con-text features to distinguish these two classes, obtaining a macro F1 of 70.5%