id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-162326-z7ta3pp9	Shahi, Gautam Kishore	AMUSED: An Annotation Framework of Multi-modal Social Media Data	2020-10-01		.txt	text/plain	6452	439	62	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. To present a use case, we apply the proposed framework to gather data on COVID-19 misinformation on multiple social media platforms. In the following sections, we discuss the related work, different types of data circulated and its restrictions on social media platforms, current annotation techniques, proposed methodology and possible application domain; then we discuss the implementation and result. Nowadays, the journalists cover some of the common issues like misinformation, mob lynching, hate speech, and they also link the social media post in the news articles Cui and Liu (2017) . Step 5: Social Media Link From the crawled data, we fetch the anchor tag( a ) mentioned in the news content, then we filter the hyperlinks to identify social media platforms like Twitter and YouTube.	./cache/cord-162326-z7ta3pp9.txt	./txt/cord-162326-z7ta3pp9.txt