Protest Image Dataset

Stefan Scholz -

To advance the state of research of political movements and protests, we aim to study them through images and videos. A fundamental task is to recognize the visual features of protest. This task can already be accomplished by image processing algorithms being developed in the field of computer vision. They need a large set of annotated images to learn, for example, to distinguish a protest image from a non-protest image. Two datasets already exist for protest images, but unfortunately they are not suitable for our analyses because they either only contain images from a single country, do not match the images to any country, or do not contain any non-protest images.

For this reason, we decided that we needed to collect our own dataset. In order to do this, we first collected images from social media from different parts of the world. Secondly, we coded these images as protest images and non-protest images according to predefined criteria. Our dataset contains 141,538 protest images from 10 countries. We believe that this is the first dataset that contains protest images from a variety of regions. In addition, it is the first that allows to determine for each image if it shows a protest or not and from which country it originates.

Research Article

Further information on the collection of the dataset can be found in the following research article.

Scholz, S., Weidmann, N. B., Steinert-Threlkeld, Z. C., Keremoglu, E., & Goldlücke, B. (2025). Improving Computer Vision Interpretability: Transparent Two-Level Classification for Complex Scenes. Political Analysis, 33 (2), 107–121.

Release

We have released the first version of the dataset, which includes tabular data on the images and the detected segments within these images. You can download this dataset from the Harvard Dataverse.

We unfortunately cannot make the images themselves publicly available.This is due to data protection and copyright reasons. However, we will make the image archive available to colleagues in political and computer science upon request. For most research projects, however, the tabular data of the images and segments ought to be sufficient. If you believe you still require the archive of images and are eligible for it, please email the corresponding author.