Skip to Main Content

2024 Election

Fact Checking Sites

Tracks misinformation specifically related to the 2024 election

Critical Reading Tips

One of the key components of evaluating sources for credibility is using critical reading skills. Whether you get your news from a traditional media source or social media, question everything you read while keeping an open mind to learn from trusted sources. Ask questions of the text as you are reading as though you are having a conversation with it. Embrace some skepticism without veering into cynicism. 

  • What are the credentials of the author? Have they written or spoken about the topic previously? When you search their name online, what do others say? Are there any issues with claims made in the past? Why do you think the author wrote this work?
  • Who is the publisher? When you search them online do you find any controversies or complaints?
  • Is the claim being made reliable? Do other reputable sources support the claim? Is it backed up by evidence? Does it seem plausible? Is it up to date? Remember, if it is breaking news, it may take time for all of the facts and evidence to come to be clear. 
  • Are there viewpoints missing from the conversation? If so, find other sources that can provide a full picture of the topic. 
  • Is the source intentionally trying to mislead or cause harm? 

For every source you find, evaluate and investigate the arguments, evidence given to support arguments, opinions, and biases to determine if this is a source you can reliably trust. 

Recognizing Bias

All of us have life experiences and beliefs which shape the way we see the world. As a result, every human has some degree of bias. The key is to be aware of your own bias and understand how it effects your interpretation of information. 

Sources are prone to bias simply because they are written by humans. Systemic bias is baked into many of the digital platforms we use, which can devalue some points of view and cause harm to individuals. 

Algorithms, which power search engines and social media, use data to make predictions about users. They take into account not only the search terms entered and the assumed relevance of sources related to those terms, but also things like your past searches, personal preferences, and location; what other people have searched for and clicked on; and in some cases if a company has paid for their results to show up sooner. Due to the way they were created, algorithms tend to perpetuate the biases of society at large, referred to as algorithmic bias.