35 Media Bias Examples for Students

media bias example types definition

Media bias examples include ideological bias, gotcha journalism, negativity bias, and sensationalism. Real-life situations when they occur include when ski resorts spin snow reports to make them sound better, and when cable news shows like Fox and MSNBC overtly prefer one political party over another (republican and democrat, respectively).

No one is free of all bias. No one is perfectly objective. So, every book, research paper, and article (including this one) is bound to have some form of bias.

The media is capable of employing an array of techniques to modify news stories in favor of particular interests or groups.

While bias is usually seen as a bad thing, and good media outlets try to minimize it as much as possible, at times, it can also be seen as a good thing. For example, a reporter’s bias toward scholarly consensus or a local paper’s bias toward reporting on events relevant to local people makes sense.

Media Bias Definition

Media bias refers to the inherently subjective processes involved in the selection and curation of information presented within media. It can lead to incorrect, inaccurate, incomplete, misleading, misrepresented, or otherwise skewed reporting.

Media bias cannot be fully eliminated. This is because media neutrality has practical limitations, such as the near impossibility of reporting every single available story and fact, the requirement that selected facts must form a coherent narrative, and so on (Newton, 1996).

Types of Media Bias

In a broad sense, there are two main types of media bias. 

  1. Ideological bias reflects a news outlet’s desire to move the opinions of readers in a particular direction.
  2. Spin bias reflects a news outlet’s attempt to create a memorable story (Mullainathan & Shleifer, 2002).

These two main types can be divided into many subcategories. The following list offers a more specific classification of different types of media bias:

  • Advertising bias occurs when stories are selected or slanted to please advertisers (Eberl et al., 2018).
  • Concision bias occurs when conciseness determines which stories are reported and which are ignored. News outlets often report views that can be summarized succinctly, thereby overshadowing views that are more unconventional, difficult to explain, and complex.
  • Confirmation bias occurs when media consumers tend to believe those stories, views, and research that confirms their current views and ignore everything else (Groseclose & Milyo, 2005).
  • Content bias occurs when two political parties are treated differently and news is biased towards one side (Entman, 2007).
  • Coverage bias occurs when the media chooses to report only negative news about one party or ideology (Eberl et al., 2017 & D’Alessio & Allen, 2000)
  • Decision-making bias occurs when the motivations, beliefs, and intentions of the journalists have an impact on what they write and how (Entman, 2007).
  • Demographic bias occurs when demographic factors, such as race, gender, social status, income, and so on are allowed to influence reporting (Ribeiro et al., 2018).
  • Gatekeeping bias occurs when stories are selected or dismissed on ideological grounds (D’Alessio & Allen, 2000). This is sometimes also referred to as agenda bias, selectivity bias (Hofstetter & Buss, 1978), or selection bias (Groeling, 2013). Such bias is often focused on political actors (Brandenburg, 2006).
  • Layout bias occurs when an article is placed in a section that is less read so that it becomes less important, or when an article is placed first so that more people read it. This can sometimes be called burying the lead.
  • Mainstream bias occurs when a news outlet only reports things that are safe to report and everyone else is reporting. By extension, the news outlet ignores stories and views that might offend the majority.
  • Partisan bias occurs when a news outlet tends to report in a way that serves a specific political party (Haselmayer et al., 2017).
  • Sensationalism bias occurs when the exceptional, the exciting, and the sensational are given more attention because it is rarer.
  • Statement bias occurs when media coverage is slanted in favor of or against specific actors or issues (D’Alessio & Allen, 2000). It is also known as tonality bias (Eberl et al., 2017) or presentation bias (Groeling, 2013).
  • Structural bias occurs when an actor or issue receives more or less favorable coverage as a result of newsworthiness instead of ideological decisions (Haselmayer et al., 2019 & van Dalen, 2012).
  • Distance bias occurs when a news agency gives more coverage to events physically closer to the news agency than elsewhere. For example, national media organizations like NBC may be unconsciously biased toward New York City news because that is where they’re located.
  • Negativity bias occurs because negative information tends to attract more attention and is remembered for a longer time, even if it’s disliked in the moment.
  • False balance bias occurs when a news agency attempts to appear balanced by presenting a news story as if the data is 50/50 on the topic, while the data may in fact show one perspective should objectively hold more weight. Climate change is the classic example.

Media Bias Examples

  • Ski resorts reporting on snowfall: Ski resorts are biased in how they spin snowfall reporting. They consistently report higher snowfall than official forecasts because they have a supply-driven interest in doing so (Raymond & Taylor, 2021).
  • Moral panic in the UK: Cohen (1964) famously explored UK media’s sensationalist reporting about youth subcultural groups as “delinquents”, causing panic among the general population that wasn’t representative of the subcultural groups’ true actions or impact on society.
  • Murdoch media in Australia: Former Prime Minister Kevin Rudd consistently reports on media bias in the Murdoch media, highlighting for example, that Murdoch’s papers have endorsed the conservative side of politics (ironically called the Liberals) in 24 out of 24 elections.
  • Fox and MSNBC: In the United States, Fox and MSNBC have niched down to report from a right- and left-wing bias, respectively.
  • Fog of war: During wartime, national news outlets tend to engage in overt bias against the enemy by reporting extensively on their war crimes while failing to report on their own war crimes.
  • Missing white woman syndrome: Sensationalism bias is evident in cases such as missing woman Gabby Petito. The argument of this type of bias is that media tends only to report on missing women when they are white, and neglect to make as much of a fuss about missing Indigenous women.
  • First-World Bias in Reporting on Natural Disasters: Scholars have found that news outlets tend to have bias toward reporting on first-world nations that have suffered natural disasters while under-reporting on natural disasters in developing nations, where they’re seen as not newsworthy (Aritenang, 2022; Berlemann & Thomas, 2018).
  • Overseas Reporting on US Politics: Sensationalism bias has an effect when non-US nations report on US politics. Unlike other nations’ politics, US politics is heavily reported worldwide. One major reason is that US politics tends to be bitterly fought and lends itself to sensational headlines.
  • Click baiting: Media outlets that have moved to a predominantly online focus, such as Forbes and Vice, are biased toward news reports that can be summed up by a sensational headline to ensure they get clicked – this is called “click baiting”.
  • Google rankings and mainstream research bias: Google has explicitly put in its site quality rater guidelines a preference for sites that report in ways that reflect “expert consensus”. While this may be seen as a positive way to use bias, it can also push potentially valid alternative perspectives and whistleblowers off the front page of search results.
  • False Balance on climate change: Researchers at Northwestern University have highlighted the prevalence of false balance reporting on climate change. They argue that 99% of scientists agree that it is man-made, yet often, news segments have one scientist arguing one side and another arguing another, giving the reporting a perception that it’s a 50-50 split in the scientific debate. In their estimation, an unbiased report would demonstrate the overwhelming amount of scientific evidence supporting one side over the other.
  • Negative Unemployment Reports: Garz found that media tend to over-report negative unemployment statistics while under-reporting when unemployment statistics are positive (Garz, 2013).
  • Gotcha Journalism: Gotcha journalism involves having journalists go out and actively seek out “gotcha questions” that will lead to sensational headlines. It is a form of bias because it often leads to less reporting on substantive messaging and an over-emphasis on gaffes and disingenuous characterizations of politicians.
  • Citizenship bias: When a disaster happens overseas, reporting often presents the number deceased, followed by the number from the news outlet’s company. For example, they might say: “51 dead, including 4 Americans.” This bias, of course, is to try to make the news appear more relevant to their audience, but nonetheless shows a bias toward the audience’s in-group.
  • Online indie media bias: Online indie media groups that have shot up on YouTube and social media often have overt biases. Left-wing versions include The Young Turks and The David Pakman Show, while right-wing versions include The Daily Wire and Charlie Kirk.
  • Western alienation: In Canada, this phenomenon refers to ostensibly national media outlets like The Globe and Mail having a bias toward news occurring in Toronto and ignoring western provinces, leading to “western alienation”.

The Government’s Role in Media Bias

Governments also play an important role in media bias due to their ability to distribute power.

The most obvious examples of pro-government media bias can be seen in totalitarian regimes, such as modern-day North Korea (Merloe, 2015). The government and the media can influence each other: the media can influence politicians and vice versa (Entman, 2007).

Nevertheless, even liberal democratic governments can affect media bias by, for example, leaking stories to their favored outlets and selectively calling upon their preferred outlets during news conferences.

In addition to the government, the market can also influence media coverage. Bias can be the function of who owns the media outlet in question, who are the media staff, what is the intended audience, what gets the most clicks or sells the most newspapers, and so on. 

Conclusion

Media bias refers to the bias of journalists and news outlets in reporting events, views, stories, and everything else they might cover.

The term usually denotes a widespread bias rather than something specific to one journalist or article.

There are many types of media bias. It is useful to understand the different types of biases, but also recognize that while good reporting can and does exist, it’s almost impossible to fully eliminate biases in reporting.

References

Aritenang, A. (2022). Understanding international agenda using media analytics: The case of disaster news coverage in Indonesia. Cogent Arts & Humanities9(1), 2108200.

Brandenburg, H. (2006). Party Strategy and Media Bias: A Quantitative Analysis of the 2005 UK Election Campaign. Journal of Elections, Public Opinion and Parties, 16(2), 157–178. https://doi.org/10.1080/13689880600716027

D’Alessio, D., & Allen, M. (2000). Media Bias in Presidential Elections: A Meta-Analysis. Journal of Communication, 50(4), 133–156. https://doi.org/10.1111/j.1460-2466.2000.tb02866.x

Eberl, J.-M., Boomgaarden, H. G., & Wagner, M. (2017). One Bias Fits All? Three Types of Media Bias and Their Effects on Party Preferences. Communication Research, 44(8), 1125–1148. https://doi.org/10.1177/0093650215614364

Eberl, J.-M., Wagner, M., & Boomgaarden, H. G. (2018). Party Advertising in Newspapers. Journalism Studies, 19(6), 782–802. https://doi.org/10.1080/1461670X.2016.1234356

Entman, R. M. (2007). Framing Bias: Media in the Distribution of Power. Journal of Communication, 57(1), 163–173. https://doi.org/10.1111/j.1460-2466.2006.00336.x

Garz, M. (2014). Good news and bad news: evidence of media bias in unemployment reports. Public Choice161(3), 499-515.

Groeling, T. (2013). Media Bias by the Numbers: Challenges and Opportunities in the Empirical Study of Partisan News. Annual Review of Political Science, 16(1), 129–151. https://doi.org/10.1146/annurev-polisci-040811-115123

Groseclose, T., & Milyo, J. (2005). A measure of media bias. The Quarterly Journal of Economics, 120(4), 1191-1237.

Groseclose, T., & Milyo, J. (2005). A Measure of Media Bias. The Quarterly Journal of Economics, 120(4), 1191–1237. https://doi.org/10.1162/003355305775097542

Haselmayer, M., Meyer, T. M., & Wagner, M. (2019). Fighting for attention: Media coverage of negative campaign messages. Party Politics, 25(3), 412–423. https://doi.org/10.1177/1354068817724174

Haselmayer, M., Wagner, M., & Meyer, T. M. (2017). Partisan Bias in Message Selection: Media Gatekeeping of Party Press Releases. Political Communication, 34(3), 367–384. https://doi.org/10.1080/10584609.2016.1265619

Hofstetter, C. R., & Buss, T. F. (1978). Bias in television news coverage of political events: A methodological analysis. Journal of Broadcasting, 22(4), 517–530. https://doi.org/10.1080/08838157809363907

Mackey, T. P., & Jacobson, T. E. (2019). Metaliterate Learning for the Post-Truth World. American Library Association.

Merloe, P. (2015). Authoritarianism Goes Global: Election Monitoring Vs. Disinformation. Journal of Democracy, 26(3), 79–93. https://doi.org/10.1353/jod.2015.0053

Mullainathan, S., & Shleifer, A. (2002). Media Bias (No. w9295; p. w9295). National Bureau of Economic Research. https://doi.org/10.3386/w9295

Newton, K. (1996). The mass media and modern government. Wissenschaftszentrum Berlin für Sozialforschung.

Raymond, C., & Taylor, S. (2021). “Tell all the truth, but tell it slant”: Documenting media bias. Journal of Economic Behavior & Organization, 184, 670–691. https://doi.org/10.1016/j.jebo.2020.09.021

Ribeiro, F. N., Henrique, L., Benevenuto, F., Chakraborty, A., Kulshrestha, J., Babaei, M., & Gummadi, K. P. (2018, June). Media bias monitor: Quantifying biases of social media news outlets at large-scale. In Twelfth international AAAI conference on web and social media.

Sloan, W. D., & Mackay, J. B. (2007). Media Bias: Finding It, Fixing It. McFarland.

van Dalen, A. (2012). Structural Bias in Cross-National Perspective: How Political Systems and Journalism Cultures Influence Government Dominance in the News. The International Journal of Press/Politics, 17(1), 32–55. https://doi.org/10.1177/1940161211411087

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Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education.

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