13 Matching Annotations
  1. Feb 2019
    1. Perhaps it was the Monica Lewinsky scandal, the 2000 Florida recount, Sept. 11, 2001, or Hurricane Katrina.

      Possible examples of news being blown out of proportion for entertainment value.

    2. Other news channels followed suit, adding visual pizazz, such as the news ticker that Fox began running after the Sept. 11 attacks. They also gave their journalists more leeway to emote, though none to the degree of Fox.

      A turning point in the entertainment, news relationship.

    1. If a claim is made, expect it to be backed by evidence. Are there statistics? Where did they come from? Was a study done and perhaps replicated?

      Very important to provide evidence behind reasoning once a source makes a claim.

    1. Using Themes To Distinguish Fake News from Satire.

      As stated before, the common objective of each article can also differentiate each source. Which in result, can identify fake news.

    2. American Politics - While fake news is certainly not limited toAmerican politics, we restricted our dataset to that domain toensure a consistency of topics among all articles. This minimizesthe chance that topical differences between fake and satiricalstories could affect a classifier.

      This can be utilized in pairing with the Donald Trump "fake news" claims.

    1. native advertising: paid, sponsored content designed to look like the legitimate content produced by the media outlet

      This runs back to the discussion of news as a business.

    2. confirmation bias

      Important term when discussing the spread of fake news.

    1. urthermore, analysis of all news categories showed that news about politics, urban legends, and science spread to the most people, while news about politics and urban legends spread the fastest and were the most viral

      what the next step is despite the factually negative results.

    2. As the truth never diffused beyond a depth of ten, we saw that falsehood reached a depth of 19 nearly ten times faster than the truth reached a depth of ten. Falsehood also diffused significantly more broadly and was retweeted by more unique users than the truth at every cascade depth

      conclusion from results.

    3. Our results were dramatic: Analysis found that it took the truth approximately six times as long as falsehood to reach 1,500 people and 20 times as long as falsehood to reach a cascade depth of ten

      results.

    4. how to fact-check the tweets.

      what the purpose of the experiment is.

  2. Apr 2016