# AMUSED: An Annotation Framework of Multi-modal Social Media Data

arXiv: https://arxiv.org/abs/2010.00502 · HTML: https://mlsanity.com/paper/2010.00502/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Oct 2020.

## Built on by (most cited first, 7 of 7)

- [Overview of the HASOC track at FIRE 2020: Hate Speech and Offensive Content Identification in Indo-European Languages](https://mlsanity.com/paper/2108.05927/) (2021)
- [Overview of the CLEF--2021 CheckThat! Lab on Detecting Check-Worthy Claims, Previously Fact-Checked Claims, and Fake News](https://mlsanity.com/paper/2109.12987/) (2021)
- [Overview of the HASOC Subtrack at FIRE 2021: Hate Speech and Offensive Content Identification in English and Indo-Aryan Languages](https://mlsanity.com/paper/2112.09301/) (2021)
- [Matching Tweets With Applicable Fact-Checks Across Languages](https://mlsanity.com/paper/2202.07094/) (2022)
- [NoFake at CheckThat! 2021: Fake News Detection Using BERT](https://mlsanity.com/paper/2108.05419/) (2021)
- [Tiplines to Combat Misinformation on Encrypted Platforms: A Case Study of the 2019 Indian Election on WhatsApp](https://mlsanity.com/paper/2106.04726/) (2021)
- [A Proposed Bi-LSTM Method to Fake News Detection](https://mlsanity.com/paper/2206.13982/) (2022)

## Abstract (arXiv)

In this paper, we present a semi-automated framework called AMUSED for gathering multi-modal annotated data from the multiple social media platforms. The framework is designed to mitigate the issues of collecting and annotating social media data by cohesively combining machine and human in the data collection process. From a given list of the articles from professional news media or blog, AMUSED detects links to the social media posts from news articles and then downloads contents of the same post from the respective social media platform to gather details about that specific post. The framework is capable of fetching the annotated data from multiple platforms like Twitter, YouTube, Reddit. The framework aims to reduce the workload and problems behind the data annotation from the social media platforms. AMUSED can be applied in multiple application domains, as a use case, we have implemented the framework for collecting COVID-19 misinformation data from different social media platforms.