Chapter 12, Analyzing Fake News with Transformers

1. News labeled as "fake news" is always fake. (True/False)

   False.

2. News that everybody agrees with is always accurate. (True/False)

   False.

3. Transformers can be used to run sentiment analysis on Tweets. (True/False)

   True.

4. Key entities can be extracted from Facebook messages with a DistilBERT model running NER. (True/False)

   True.

5. Key verbs can be identified from YouTube chats with BERT-based models running SRL. (True/False)

   True.

6. Emotional reactions are a natural first response to fake news. (True/False)

   True.

7. A rational approach to fake news can help clarify one's position. (True/False)

   True.

8. Connecting transformers to reliable websites can help somebody understand why some news is fake. (True/False)

   True.

9. Transformers can make summaries of reliable websites to help us understand some of the topics labeled as fake news...