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Each of us has deeply held perspectives based on our lived experiences, our education, our belief system, and so on. That's OK! But college-level research requires us to hold some of these opinions at bay. Otherwise, bias - defined by the Penguin Dictionary of Psychology as "an inclination toward a position or conclusion" - can cloud our judgment and ability to find quality resources.
One of the most common instances of bias occurs when we seek out information or research that will supporting our predetermined ideas and opinions, or when we ignore facts that contradict our hypotheses. This is known as confirmation bias.
Most major news organizations make an effort to deliver news in an unbiased manner. Still, the stories they choose to cover (or not) and the questions they ask may reflect the organization's bias. If the owner of a media organization has a political or economic agenda, they may have an influence on coverage.
Most news outlets fall onto a spectrum of political bias. As more of us receive news through social media, the source of news can be harder to detect and evaluate. News and media bias impacts how we receive news information. Depending on the source of the content, there is a spectrum of bias that needs to be evaluated and understood before a source can be used for academic research.
Below is a Media Bias Chart from Ad Fontes media, which analyzes coverage of different media outlets (TV networks, websites, podcasts) and determines where they fall on a spectrum of reliability and political persuasion.

While media bias charts can be an introduction to an organization's political coverage, they should be used with limits and caution.
Here are some important points to consider:
Remember that political bias isn't the sole factor to consider when evaluating a source. In many cases, it isn't even the most important. This is why we encourage using the SIFT Method to assess information more holistically.
Would it surprise you to learn that:
And yet:
The rise of social media since the start of the century has coincided with a decreasing trust in legacy news media sources, such as radio, TV and news publications (print and online). Biases in social media algorithms are well documented, leading to many instances of confirmation bias. It has also given rise to what activist Eli Pariser has coined "filter bubbles," in which many internet users are less likely to encounter or interact with different people, ideas, and beliefs. The more you "like," "heart," click or comment on content with certain themes, you're less likely to come across content that counters what you've already seen and interacted with.
Find a friend, and Google the exact same term. Do you get the same set of results? If not, what may have influenced the results in each of your searches?
There are many ways you can avoid letting your biases influences your research process.