Event photo mining from Twitter using keyword bursts and image clustering

Twitter is a unique microblogging service which enables people to post and read not only short messages but also photos from anywhere. Since microblogs are different from traditional blogs in terms of timeliness and on-thespot-ness, they include much information on various events over the world. Especially, photos posted to microblogs are useful to understand what happens in the world visually and intuitively. In this paper, we propose a system to discover events and related photos from the Twitter stream. We make use of “geo-photo tweets” which are tweets including both geotags and photos in order to mine various events visually and geographically. Some works on event mining which utilize geotagged tweets have been proposed so far. However, they used no images but only textual analysis of tweet message texts. In this work, we detect events using visual information as well as textual information. In the experiments, we analyzed 17 million geo-photo tweets posted in the United States and 3 million geo-photo tweets posted in Japan with the proposed method, and evaluated the results. We show some examples of detected events and their photos such as “rainbow”, “fireworks” “Tokyo firefly festival” and “Halloween”.