Many images uploaded to social networks are related to travel, since people consider traveling to be an important event in their life. However, a significant amount of travel images on the Internet lack proper geographical annotations or tags. In many cases, the images are tagged manually. One way to make this time-consuming manual tagging process more efficient is to propagate tags from a small set of tagged images to the larger set of untagged images automatically. In this paper, we present a system for automatic geotag propagation in images based on the similarity between image content (famous landmarks) and its context (associated geotags). In such scenario, however, a wrong or a spam tag can damage the integrity and reliability of the automated propagation system. Therefore, for reliable geotags propagation, we suggest adopting user trust model based on a social feedback from the users of the photosharing system. We compare this socially-driven approach with other user trust models via experiments and subjective testing on an image database of various famous landmarks. Results demonstrate that relying on a user feedback is more efficient, since number of propagated tags more than doubles without the loss in accuracy compared to using other models or propagating without trust modeling.