I want to know about recently available datasets for fake news analysis
Buzzfeed News has been doing work on this, and has published data related to fake news, news patterns, and social media patterns on their Github: https://github.com/BuzzFeedNews/everything. Might be a good repo to browse.
Here are some of the datasets available for fake news detection:
LIAR dataset: https://www.cs.ucsb.edu/william/data/liar_dataset.zip
BS Detector: https://github.com/bs-detector/bs-detector
You should check out the Observatory on Social Media (OSoMe) at Indiana University. The team have been been archiving 10% of public activity on Twitter for the last 10 years. The data isn't directly available to people not affiliated with the University they have a number of algorithms and visualization tools that you can run against the data.
- They have a service called 'BotSlayer' which you can set up yourself on a free AWS instance and track certain hashtags and key phrases.
- There is also 'Botometer'which will assess any twitter user name and socre it based on how 'bot-like' it is.
- Finally, they have a tool called 'Hoaxy' which allows you to visualize the spread of a news or fake-news story across twitter to see which accounts are sharing/re-tweeting it.
Kaggle hosts a dataset where the CSV has URL, title, text, and a flag "reliable" or "unreliable"
id: unique id for a news article
title: the title of a news article
author: author of the news article text: the text of the article; could be incomplete
label: a label that marks the article as potentially unreliable
accessing the data requires registration