An additional example of misinformation is retracted scientific articles. These articles present flawed information, whether intentionally or not. 

Example of Misinformation: Retracted Scientific Articles

A belief that (powerful) others are engaging in conspiratorial behavior (e.g. controlling less powerful others) or attempting to cover up the truth. 

Conspiracy Theories

Rumors, conspiracy theories, satire news, and hoaxes

Johns Hopkins University

Information that is (verifiably) misleading, false, or incomplete. Misinformation can be created with or without the intent to misinform the public. 

Misinformation 

Ackland, R., & Gwynn, K. (2020). Truth and the dynamics of news diffusion on twitter. In R. Greifeneder, M. Jaffé, E. J. Newman, & N. Schwarz (Eds.), The psychology of fake news: Accepting, sharing, and correcting misinformation (pp. 27–46). London: Routledge. 

Truth and the dynamics of news diffusion on twitter

- The information appears to be true or is believable 
- Being rewritten in different forms
- Being accessible through multiple sources
- Confirmation Bias 
- Authoritative bias 
- Targeting hot topics
- Indicating urgency
- The Sunk Cost Fallacy 
- emotional appeals 
- False Beliefs
- Labels can lead to errors in assessment of information
- False Memories
- Inaccurate evaluation of information
- Ease of Processing
- Underthinking
- Deliberative processes

Reasons Misinformation Spreads

Examples of Misinformation

The process of determining the accuracy of information. Often performed and published by professional fact checkers such as Politifact or Snopes.

Fact Checking

- algorithmic
- corrective
- legislative
- psychological
- humor
- emotional refutations
- social media disclaimers

Possible solutions to Misinformation

Forewarning against misinformation should not only refute the incorrect information, it should also explain the dangers of misinformation in general. This is more effective than refuting alone. Further explored in Eakin, Schreiber, & Sergent-Marshall, 2003.

Effective forewarning against misinformation

- Because there is no single source of data that covers all three modes of consuming news, researchers select data sources on "the basis of their availability," which doesn't necessarily correspond with representativeness.
- The studies done on fake news often fail to consider how much of the fake news is consumed relative to other types of news or non-news related content.
- Even when the prevalence of fake news is low compared to other content, fake news can still be considered important because of its disproportionate impact on certain populations. Therefore comprehensive questions of prevalence on their own cannot resolve questions about influence.

Reasons Why It Is Difficult to Empirically Evaluate Disagreements Over the Prevalence and Importance of Misinformation

According to Guess & Lyons (2020) misinformation and disinformation differ regarding the author's/creater's intent. Misinformation and Disinformation are often difficult to distinguish because it’s difficult to tell whether someone spread wrong information intentionally (Disinformation) or unintentionally (Misinformation). If political misinformation is spread by politicians it's usually considered as disinformation. Also, fake news which are organized and spread by established news organizations are considered disinformation.

Distinction between Misinformation and Disinformation

Oftentimes, the producers of misinformation hide their identity. However, a few producers have been identified, e.g. Macedonian teenagers and Russia’s Internet Research Agency (IRA).

Production of Misinformation

It's difficult to trace misinformation back to their original source. Sources of fake news tend to be hyperpartisan and far-right (pro-Trump during the 2016 U.S. election). This notion is supported that even in mainstream, left-wing journalists tend to follow journalistic guidelines and codes more than right-wing journalists. In the past years, automated bots have much contributed to the spread of misinformation. It has been found than certain social media sites such as Facebook are better for spreading fake news than others such as twitter. 

Supply of Misinformation

Guess et al. (2018): approximately 27% of Americans had consumed at least one fake news article over the five weeks before the U.S. presidential election in 2016. Fourney et al. (2016): ca. 0.34% of Microsoft Explorer users (who agreed to anonymously share their internet usage) visited a fake news domain in a day. Grinberg et al. (2019): on twitter, ca. 5% of political content originates from fake news sources in 2016. Guess et al. (2018): 0.01 % of tweets contained fake news during the French presidential election in 2017. 

Even thought these statistics have their limitations and are difficult to interpret, one can say that only a small amount of social media content is fake news and only a small amount of social media users is responsible for the huge dissemination of fake news.

Prevalence of Misinformation

Scientific racism is the use of pseudoscience to claim inherent racial superiority of some groups over others. It fails to account for social and political factors when explaining racial inequalities and justifies them by using the authority of science as an objective way of knowledge formation (Gould, 1996).

Scientific Racism 

This concept refers to the attempt to correct the spread of misinformation by reducing people’s misconceptions. This topic focuses on ways to offer misinformation correction, the number of corrections offered to make an impact, and the source of the misinformation corrections. 

Correcting Misinformation

- Health Misinformation
- Political Misinformation
- Fake News
- Disinformation
- Misinformation in Online Communities

Types of Misinformation

The extent to which a person believes misinformation relative to accurate content

Truth Discernment

Topic of research project on visualization of information and misinformation.

Identifying Misinformation through Visualization

References for Who falls for fake news? Psychological and clinical profiling evidence of fake news consumers

Avram, M., Micallef, N., Patil, S., & Menczer, F. (2020). Exposure to social engagement metrics increases vulnerability to misinformation. Harvard Kennedy School (HKS) Misinformation Review. https://doi.org/10.37016/mr-2020-033

Exposure to social engagement metrics increases vulnerability to misinformation

References for Exposure to social engagement metrics increases vulnerability to misinformation

Misleading information that is presented to someone after witnessing event can change how they recall and explain that event. One common explanation is retroactive interference (new learning interfering with old memory/understanding)

Learn Before

Related

Learn After