The double-edged sword of the Internet is that almost anything can be posted on it. While that means we can access billions of words worth of information with a few key presses, it also means that not all that information is accurate, up to date, or in good faith. With the increasing rise in misinformation campaigns and generative artificial intelligence, it's important that you take precautions in making sure that the sources you are using are reputable and contain real information.
Bias refers to the favour of a certain idea, side, or thing. It is present in many kinds of writing on many different kinds of sites, sometimes unconsciously. We often gravitate towards news and articles that appeal to our own beliefs, but this is not the best way to research.
Why does bias matter?
Being too biased towards a side will affect your research. You must be able to be objective and apply critical thinking towards various perspectives. Learning requires you to be able to be open to new ideas and information.
Signs that a source may be biased:
Types of Bias (infographic from Business Insider)

Bias Checkers
Credibility refers to whether or not a source can be reliably assumed to be trustworthy and accurate. For example, Wikipedia is not considered a credible source because anyone is able to edit it. However, a peer-reviewed journal article can generally be assumed to be credible because it has been written by experts and has passed multiple rounds of inspection by other experts. That said, you should take the time to examine your sources regardless of where you found them to be sure that they're credible.
There are four major criteria to think about when determining whether or not a source is credible:
Spotting Fake News & Misinformation (infographic from the International Federation of Library Associations and Institutions)
Filter bubbles refer to the 'bubble' that algorithms create around us on the web. The way that you search and use the web based on your preferences is collected and sold to other companies, which is then applied to advertising and search results. Think about something like Facebook -- if you repost or like a lot of things about cats, then it's more likely that it will recommend posts about cats to you or show you advertisements for cat food.
While this isn't necessarily bad when it comes to your day-to-day personal interests and habits, it can affect your ability to research. To avoid filter bubbles, try the following tricks: