Analyzing Fake News with Transformers

We were all born thinking that the Earth was flat. As babies, we crawled on flat surfaces. As kindergarten children, we played on flat playgrounds. In elementary school, we sat in flat classrooms. Then, our parents and teachers told us that the Earth was round and that the people on the other side of it were upside down. It took us quite a while to understand why they did not fall off the Earth. Even today, when we see a beautiful sunset, we still see the “sun set,” and not the Earth rotating away from the sun!

It takes time and effort to figure out what is fake news and what isn’t. Like children, we have to work our way through something we perceive as fake news.

This chapter will tackle some of the topics that create tensions. We will check the facts on topics such as climate change, gun control, and Donald Trump’s Tweets. We will analyze Tweets, Facebook posts, and other sources of information.

Our goal...

Emotional reactions to fake news

Human behavior has a tremendous influence on our social, cultural, and economic decisions. Our emotions influence our economy as much as, if not more than, rational thinking. Behavioral economics drives our decision-making process. We buy consumer goods that we physically need and satisfy our emotional desires. We might even buy a smartphone in the heat of the moment, although it exceeds our budget.

Our emotional and rational reactions to fake news depend on whether we think slowly or react quickly to incoming information. Daniel Kahneman described this process in his research and book, Thinking, Fast and Slow (2013).

He and Vernon L. Smith were awarded the Nobel Memorial Prize in Economic Sciences for behavioral economics research. Behavior drives decisions we previously thought were rational. Unfortunately, many of our decisions are based on emotions, not reason.

Let’s translate these concepts into a behavioral flowchart applied...

A rational approach to fake news

Transformers are the most powerful NLP tools ever. This section will first define a method that can take two parties engaged in conflict over fake news from an emotional level to a rational level.

We will then use transformer tools and heuristics. We will run transformer samples on gun control and former President Trump’s Tweets during the COVID-19 pandemic. We will also describe heuristics that could be implemented with classical functions.

You can implement these transformer NLP tasks or other tasks of your choice. In any case, the roadmap and method can help teachers, parents, friends, co-workers, and anybody seeking the truth. Thus, your work will always be worthwhile!

Let’s begin with the roadmap of a rational approach to fake news that includes transformers.

Defining a fake news resolution roadmap

Figure 13.3 defines a roadmap for a rational fake news analysis process. The process contains transformer NLP tasks...

Before we go

This chapter focused more on applying transformers to a problem than finding a silver bullet transformer model, which does not exist.

You have two main options to solve an NLP problem: find new transformer models or create reliable, durable methods to implement transformer models.

We will now conclude the chapter and move on to interpret transformer models.

Summary

Fake news begins deep inside our emotional history as humans. When an event occurs, emotions take over to help us react quickly to a situation. We are hardwired to react strongly when we are threatened.

Fake news spurs strong reactions. We fear that this news could temporarily or permanently damage our lives. Many of us believe climate change could eradicate human life from Earth. Others believe that if we react too strongly to climate change, we might destroy our economies and break society down. Some of us believe that guns are dangerous. Others remind us that the Second Amendment of the United States Constitution gives us the right to possess a gun in the US.

We went through other raging conflicts over COVID-19, former President Trump, and climate change. In each case, we saw that emotional reactions are the fastest ones to build up into conflicts.

We then designed a roadmap to take the emotional perception of fake news to a rational level. We used some transformer...

Questions

1. News labeled as fake news is always fake. (True/False)
2. News that everybody agrees with is always accurate. (True/False)
3. Transformers can be used to run sentiment analysis on Tweets. (True/False)
4. Key entities can be extracted from Facebook messages with a DistilBERT model running NER. (True/False)
5. Key verbs can be identified from YouTube chats with BERT-based models running SRL. (True/False)
6. Emotional reactions are a natural first response to fake news. (True/False)
7. A rational approach to fake news can help clarify one’s position. (True/False)
8. Connecting transformers to reliable websites can help somebody understand why some news is fake. (True/False)
9. Transformers can make summaries of reliable websites to help us understand some of the topics labeled as fake news. (True/False)
10. You can change the world if you use AI for the good of us all. (True/False)

References

• Daniel Kahneman, 2013, Thinking, Fast and Slow
• Hugging Face pipelines: https://huggingface.co/transformers/main_classes/pipelines.html
• The Allen Institute for AI: https://allennlp.org/

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