FakeHealth

Our repository consists of two datasets: HealthStory and HealthRelease. Due to the twitter policy of protecting user privacy, the full contents of user social engagements and network are not allowed to directly publish. Instead, we store the IDs of all social engagements and related user network into json files, and supplement them with an API to trivially attain the social engagements and user network from twitter. The IDs are stored in `./dataset/engagements/HealthRelease.json` , `./dataset/engagements/HealthStory.json` , `./dataset/user_network/followers/` , and `./dataset/user_network/following/`. We will also keep updating the code of FakeHealth in https://github.com/EnyanDai/FakeHealth. This version further supplies the collected follower and friends IDs.

Related Organizations

Pennsylvania State University
United States

Keywords

Fake news detection, Health

Impact byBIP!

	selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	2
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average