# Detecting Changes in Crowdsourced Social Media Images

arXiv: https://arxiv.org/abs/2310.16848 · HTML: https://mlsanity.com/paper/2310.16848/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Oct 2023.

## Built on by (most cited first, 1 of 1)

- [Determining Intent of Changes to Ascertain Fake Crowdsourced Image Services](https://mlsanity.com/paper/2403.12045/) (2023)

## Abstract (arXiv)

We propose a novel service framework to detect changes in crowdsourced images. We use a service-oriented approach to model and represent crowdsourced images as image services. Non-functional attributes of an image service are leveraged to detect changes in an image. The changes are reported in form of a version tree. The version tree is constructed in a way that it reflects the extent of changes introduced in different versions. Afterwards, we find semantic differences in between different versions to determine the extent of changes introduced in a specific version. Preliminary experimental results demonstrate the effectiveness of the proposed approach.