There are a lot of research going on tweets like fake news, event detection, sarcasm detection etc., So depending upon situation, people may leverage a common observable pattern to filter relevant tweets from the tweet stream.
Tags: analytics, filtering, research, text analytics, tweet, twitter
We have posted a few articles on this topic, see here. One way to handle it is to
Eventually, you want to attach a trustworthiness score to each post, and make those with a low score less visible.
I am mainly focusing on researches/fields that are being done by filtering tweets or things that have been achieved by filtering tweets. So here, I want to know about filtering of tweets and it's various uses and implications.But your suggestion is towards different aspects and procedures of "fake news detection".
Vincent Granville said:
We have posted a few articles on this topic, see here. One way to handle it is to
- Automatically crawl the web to see if the same article is also posted in trustworthy outlets
- Has the media source in question been flagged in the past for posting news that might be fake?
- Does the source domain contain words such as "viral", e.g. viralnews.com?
- Is the source domain a new website, or has it been around for a while?
Eventually, you want to attach a trustworthiness score to each post, and make those with a low score less visible.
IMO this is an excellent podcast series. The one on sarcasm is episode 48 is particularly good.
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