Misinformation

Scholars distinguish between misinformation, disinformation, and malinformation in terms of intent and effect. Misinformation is false or inaccurate information published without malicious intent, while disinformation is designed to mislead. Malinformation is true information intended to cause harm, such as selectively publicizing a politician's personal information to shape public opinion. Disinformation is created or spread by a person or organization actively attempting to deceive their audience. In addition to causing harm directly, disinformation can also cause indirect harm by undermining trust and obstructing the capacity to effectively communicate information with one another. Disinformation can appear in any medium including text, audio, and imagery. For example, the scientific guidance around infant sleep positions has evolved over time, and these changes could be a source of confusion for new parents. Misinformation can also often be observed as news events are unfolding and questionable or unverified information fills information gaps. Even if later retracted, false information can continue to influence actions and memory. Rumors are unverified information not attributed to any particular source and may be either true or false. Definitions of these terms may vary between cultural contexts. == History ==

Early examples include the insults and smears spread among political rivals in Imperial and Renaissance Italy in the form of pasquinades. These are anonymous and witty verses named for the Pasquino piazza and talking statues in Rome. In pre-revolutionary France, "canards", or printed broadsides, sometimes included an engraving to convince readers to take them seriously. During the summer of 1587, continental Europe anxiously awaited news as the Spanish Armada sailed to fight the English. The Spanish postmaster and Spanish agents in Rome promoted reports of Spanish victory in hopes of convincing Pope Sixtus V to release his promised one million ducats upon landing of troops. In France, the Spanish and English ambassadors promoted contradictory narratives in the press, and a Spanish victory was incorrectly celebrated in Paris, Prague, and Venice. It was not until late August that reliable reports of the Spanish defeat arrived in major cities and were widely believed; the remains of the fleet returned home in the autumn. Misinformation has historically been linked to advancements in communications technologies. With the mass media revolution in the 20th century, television, radio, and newspapers were major vehicles for reliable information and misinformation. War-time propaganda, political disinformation, and corporate public relations operations often shaped the public perception, occasionally distorting facts to promote economic or ideological agendas. With the discovery of television as a popular medium, disinformation could be rapidly disseminated to millions of individuals, reinforcing existing bias and making correction more difficult. These early trends set the foundation for modern digital misinformation, which now spreads even more efficiently along internet networks. The first recorded large-scale disinformation campaign was the Great Moon Hoax, published in 1835 in the New York The Sun, in which a series of articles claimed to describe life on the Moon, "complete with illustrations of humanoid bat-creatures and bearded blue unicorns". The challenges of mass-producing news on a short deadline can lead to factual errors and mistakes. An example of such is the Chicago Tribunes infamous 1948 headline "Dewey Defeats Truman". In November 2005, Chris Hansen on Dateline NBC claimed that law enforcement officials estimate 50,000 predators are online at any moment. Afterward, then-U.S. attorney general Alberto Gonzales repeated the claim. However, the number that Hansen used in his reporting had no backing. Hansen said he received the information from Dateline expert Ken Lanning, but Lanning admitted that he made up the number 50,000 because there was no solid data on the number. According to Lanning, he used 50,000 because it sounds like a real number, not too big and not too small, and referred to it as a "Goldilocks number". Reporter Carl Bialik says that the number 50,000 is used often in the media to estimate numbers when reporters are unsure of the exact data. Social media platforms allow for easy spread of misinformation, and misinformation was a major talking point during the 2016 U.S. presidential election with claims of social media sites allowing "fake news" to be spread. Post-election surveys in 2016 suggest that many individuals who intake false information on social media believe them to be factual. The specific reasons why misinformation spreads through social media so easily remain unknown. A 2018 study of Twitter determined that, compared to accurate information, false information spread significantly faster, further, deeper, and more broadly. Similarly, a research study of Facebook found that misinformation was more likely to be clicked on than factual information. displaying the inaccurate Chicago Tribune headline, an example of misinformation|alt=Harry S. Truman gleefully displays a Chicago Tribune headline erroneously stating that his opponent, Thomas E. Dewey, defeated him in the United States presidential election. Moreover, the advent of the Internet has changed traditional ways that misinformation spreads. During the 2016 U.S. presidential election, content from websites deemed 'untrustworthy' reached up to 40% of Americans, despite misinformation making up only 6% of overall news media. Misinformation has been spread during many health crises. For example, misinformation about alternative treatments was spread during the Ebola outbreak in 2014–2016. During the COVID-19 pandemic, the proliferation of mis- and dis-information was exacerbated by a general lack of health literacy. For example, a conspiracy theory that COVID-19 was linked to the 5G network gained significant traction worldwide after emerging on social media. COVID-19 misinformation Misinformation is also a major public health problem, with effects on health behaviors. During the COVID-19 pandemic, social media was used as one of the main propagators of misinformation about symptoms, treatments, and long-term health-related problems, This problem led to an effort in developing automated detection methods for misinformation on social media platforms. The creator of the Stop Mandatory Vaccination made money posting anti-vax false news on social media. He posted more than 150 posts aimed towards women, garnering a total of 1.6 million views and earning money for every click and share. == Research ==

Much research on how to correct misinformation has focused on fact-checking. However, this can be challenging because the information deficit model does not necessarily apply well to beliefs in misinformation. Causes Factors that contribute to beliefs in misinformation are an ongoing subject of study. According to Scheufele and Krause, misinformation belief has roots at the individual, group and societal levels. At the individual level, individuals have varying levels of skill in recognizing mis- or dis-information and may be predisposed to certain misinformation beliefs due to other personal beliefs, motivations, or emotions. At the group level, in-group bias and a tendency to associate with like-minded or similar people can produce echo chambers and information silos that can create and reinforce misinformation beliefs. At the societal level, public figures like politicians and celebrities can disproportionately influence public opinions, as can mass media outlets. In addition, societal trends like political polarization, economic inequalities, declining trust in science, and changing perceptions of authority contribute to the impact of misinformation. Social media structures, which have been leveraged by politicians and news media for political and economic ends, have exacerbated the prevalence of misinformation. Historically, people have relied on journalists and other information professionals to relay facts. As the number and variety of information sources has increased, it has become more challenging for the general public to assess their credibility. This growth of consumer choice when it comes to news media allows the consumer to choose a news source that may align with their biases, which consequently increases the likelihood that they are misinformed. Polling shows that Americans trust mass media at record-low rates, and that US young adults place similar levels of trust in information from social media and from national news organizations. The pace of the 24 hour news cycle does not always allow for adequate fact-checking, potentially leading to the spread of misinformation. Further, the distinction between opinion and reporting can be unclear to viewers or readers. Sources of misinformation can appear highly convincing and similar to trusted legitimate sources. For example, misinformation cited with hyperlinks has been found to increase readers' trust. Trust is even higher when these hyperlinks are to scientific journals, and higher still when readers do not click on the sources to investigate for themselves. Research has also shown that the presence of relevant images alongside incorrect statements increases both their believability and shareability, even if the images do not actually provide evidence for the statements. For example, a false statement about macadamia nuts accompanied by an image of a bowl of macadamia nuts tends to be rated as more believable than the same statement without an image. Dramatic headlines may gain readers' attention, but they do not always accurately reflect scientific findings. Human cognitive tendencies can also be a contributing factor to misinformation belief. One study found that an individual's recollection of political events could be altered when presented with misinformation about the event, even when primed to identify warning signs of misinformation. Misinformation may also be appealing by seeming novel or incorporating existing stereotypes. Identification Several strategies have been suggested to reduce misinformation. One approach is to evaluate source credibility and motivation of the source, as well as considering plausibility of claims. Readers tend to distinguish between unintentional misinformation and uncertain evidence from politically or financially motivated misinformation. It can be difficult to undo the effects of misinformation once individuals believe it to be true. Individuals may desire to reach a certain conclusion, causing them to accept information that supports that conclusion, and are more likely to retain and share information if it emotionally resonates with them. The SIFT Method, also called the Four Moves, is one commonly taught method of distinguishing between reliable and unreliable information. This method instructs readers to first Stop and begin to ask themselves about what they are reading or viewing - do they know the source and if it is reliable? Second, readers should Investigate the source. What is the source's relevant expertise and do they have an agenda? Third, a reader should Find better coverage and look for reliable coverage on the claim at hand to understand if there is a consensus around the issue. Finally, a reader should Trace claims, quotes, or media to their original context: has important information been omitted, or is the original source questionable? Visual misinformation presents particular challenges, but there are some effective strategies for identification. Misleading graphs and charts can be identified through careful examination of the data presentation; for example, truncated axes or poor color choices can cause confusion. Reverse image searching can reveal whether images have been taken out of their original context. There are currently some somewhat reliable ways to identify AI-generated imagery, but it is likely that this will become more difficult to identify as the technology advances. A person's formal education level and media literacy do correlate with their ability to recognize misinformation. People who are familiar with a topic, the processes of researching and presenting information, or have critical evaluation skills are more likely to correctly identify misinformation. However, these are not always direct relationships. Higher overall literacy does not always lead to improved ability to detect misinformation. Context clues can also significantly impact people's ability to detect misinformation. Martin Libicki, author of Conquest In Cyberspace: National Security and Information Warfare, notes that readers should aim to be skeptical but not cynical. Readers should not be gullible, believing everything they read without question, but also should not be paranoid that everything they see or read is false. Factors influencing susceptibility to misinformation Various demographic, cognitive, social, and technological factors can influence an individual's susceptibility to misinformation. This section examines how age, political ideology, and algorithms may affect vulnerability to false or misleading information. Age Research suggests that age can be a significant factor in how individuals process and respond to misinformation. Some researchers have suggested that older individuals are more susceptible to misinformation than younger individuals due to cognitive decline. Other studies have found that, while this may be a factor, the issue is more complex than simply aging and experiencing cognitive decline. One notable area where cognitive decline is prevalent is repeated exposure to misinformation. A study found that older adults are more likely than younger adults to believe misinformation after repeated exposure, known as the illusory truth effect. This is linked to declines in memory and analytical reasoning, which can make it more challenging for older adults to distinguish between true and false information. Another commonly found explanation for older adults' susceptibility to misinformation is a lack of digital literacy. According to a nationally representative study of U.S. adults by Pew Research Center from 2023, 61% of adults aged 65 years or older own a smartphone, 45% use social media, and 44% own a tablet computer. All three numbers represent an increase over the last decade, indicating that older adults are spending more time online, thereby increasing their potential exposure to misinformation. This cognitive bias fosters an environment where misinformation that aligns with one's view thrives, creating echo chambers. Researchers explored the relationship between partisanship, the presence of an echo chamber, and vulnerability to misinformation, finding a strong correlation between right-wing partisanship and the sharing of online misinformation. They also discovered a similar trend among left-leaning users. Similar research has found that right- and left-wing partisans exhibit similar levels of metacognitive awareness, which refers to individuals' conscious awareness of their own thoughts and mental processes. In a study that asked participants to identify news headlines as true or false, both Democrats and Republicans admitted to occasionally suspecting they were wrong. This finding, coupled with confirmation bias, contributes to a media ecosystem where misinformation can thrive. Algorithms Social media algorithms are designed to increase user engagement. Research suggests that humans are naturally drawn to emotionally charged content, and algorithms perpetuate a cycle in which emotionally charged misinformation is disproportionately promoted on social media platforms. This misinformation is spread rapidly through algorithms, outpacing the speed of fact-checking. Additionally, most social media users possess a limited understanding of how algorithms curate their information feeds.|alt=In a Google search for "Joaquín Correa brother", Google's AI Overview erroneously states that "Joaquín Correa's brother is named Ángel Correa", and briefly details Ángel Correa's career. It cites the English Wikipedia article on Ángel Correa (which did not support the false relationship claim), alongside another unseen website. A note beneath the overview warns that "AI responses may include mistakes", and provides a hyperlink for further information. The rise of Artificial intelligence has also contributed to the formation of new types of misinformation and disinformation. This is called Synthetic media according to the UNHCR Factsheet. AI is capable of manipulation and modification of data and multimedia. AI is used in algorithms nowadays to mislead audience. The presence of synthetic media could intensify fake news and supports the spread of misinformation if used in the wrong way. Deep fakes are a part of synthetic media that have gained popularity recently in which faces of people are replaced. This manipulation has garnered widespread attention for their use in fake news, hoaxes, fraud and revenge porn. Speech synthesis (Another type of synthetic media) amplifies these deep fakes by artificially producing human speech with the help of a speech computer. Synthetic media has become a concern for industries and governments which made some countries already have a national response or national institutions are working on detecting and limiting its use. However, AI also helps by contributing to the fight against misinformation. • Deepfakes and Synthetic media create very convincing visual, audio, and textual evidence that is difficult to distinguish from legitimate authoritative evidence. • Internet bots and automated Internet trolls can rapidly sow disinformation. • Algorithmic bias plays a role in amplification of sensational and controversial material regardless of truth. AI misinformation examples LA wildfire Hollywood sign  In 2025, California experienced a firestorm disaster, accompanied by a massive wave of AI disinformation, which led to misinformation. An example of such misinformation is the AI-generated images of Hollywood Sign on fire. Jeff Zarrinnam, chairman of Hollywood Sign, said, "'They look so real that I couldn't tell if it was real or not,' he says. "'You know, if I didn't see the Hollywood Sign myself ... I would have probably believed' that it was on fire." The Hollywood sign was never on fire, but it led to multiple people contacting Jeff Zarrinnam asking if the sign was ok because they believed it to be burnt. A Microsoft AI for Good Lab study ran a test. The test, which had 12,500 global participants, chose whether an image was "Real or Artificial". In total, 287,269 images were seen by participants; only 93,490 were real images. The Microsoft AI for Good Lab study found that participants had a 62% success rate in guessing correctly. The test shows how hard it is to detect AI-generated images. Mata v. Avianca, Inc., ChatGPT uses large language models (LLMs) to generate text from human data (books, articles, social media, etc). LLMs are known to generate false information, whether they got their information from a parody site like The Onion, people posting misinformation, or the LLMs just making up data aka hallucinating. An example of such LLM hallucinations is the court case of Roberto Mata, Plaintiff, v. Aviance Inc., Defendant, in which two attorneys defending Mata submitted an AI-generated legal motion that hallucinated court cases. December 8th earthquake On December 8, 2025, Japan experienced an earthquake disaster, accompanied by multiple AI-generated videos that emerged on social media. These AI-generated videos showed and explained how the earthquake began, what happened during it, and its aftermath. These AI-generated videos misinform the Japanese public, causing a government response warning of such fake videos. Zelenskyy deepfakes Hackers broadcast a deepfake video of Volodymyr Zelenskyy telling his soldiers to surrender in 2022. Zelenskyy later disproved the deepfake. Brown University shooting On December 13, 2025, there was a shooting at Brown University, where the gunman wore a mask. Multiple people on social media are using AI-generated images to create a face for what the gunman would look like. AI cannot generate a real image of the gunman's face, which can lead to wrongful arrest when fake AI-generated faces are used. ==Countermeasures==

Factors that contribute to the effectiveness of a corrective message include an individual's mental model or worldview, repeated exposure to the misinformation, time between misinformation and correction, credibility of the sources, and relative coherency of the misinformation and corrective message. Corrective messages will be more effective when they are coherent and/or consistent with the audience's worldview. They will be less effective when misinformation is believed to come from a credible source, is repeated prior to correction (even if the repetition occurs in the process of debunking), and/or when there is a time lag between the misinformation exposure and corrective message. Additionally, corrective messages delivered by the original source of the misinformation tend to be more effective. However, misinformation research has often been criticized for its emphasis on efficacy (i.e., demonstrating effects of interventions in controlled experiments) over effectiveness (i.e., confirming real-world impacts of these interventions). Critics argue that while laboratory settings may show promising results, these do not always translate into practical, everyday situations where misinformation spreads. Several challenges have been suggested in implementing interventions for misinformation: an overabundance of lab research and a lack of field studies, the presence of testing effects that impede intervention longevity and scalability, modest effects for small fractions of relevant audiences, reliance on item evaluation tasks as primary efficacy measures, low replicability in the Global South and a lack of audience-tailored interventions, and the underappreciation of potential unintended consequences of intervention implementation. Similar sites allow individuals to copy and paste misinformation into a search engine and the site will investigate it. Some sites exist to address misinformation about specific topics, such as climate change misinformation. DeSmog, formerly The DeSmogBlog, publishes factually accurate information in order to counter the well-funded disinformation campaigns spread by motivated deniers of climate change. Science Feedback focuses on evaluating science, health, climate, and energy claims in the media and providing an evidence-based analysis of their veracity. Flagging or eliminating false statements in media using algorithmic fact checkers is becoming an increasingly common tactic to fight misinformation. Google and many social media platforms have added automatic fact-checking programs to their sites and created the option for users to flag information that they think is false. In some cases social media platforms' efforts to curb the spread of misinformation has resulted in controversy, drawing criticism from people who see these efforts as constructing a barrier to their right to expression. Crowdsourced fact-checking As a way to scale counter-measures, some platforms and researchers have proposed crowdsourcing interventions, which use the judgments of laypeople to identify and label misinformation. This approach, which is the model for systems like Wikipedia and X's "Community Notes," is seen as a potential multi-layered solution that can be faster and more comprehensive than professional fact-checking alone. Research has found that the aggregated judgments of a politically balanced group of laypeople can be as accurate as professional fact-checkers. This method is particularly studied as a response to partisan misinformation. Traditional fact-checking is often less effective for highly partisan content, as corrections from perceived "out-groups" are easily dismissed, while "in-group" members are often unwilling to challenge their own side. Other effective strategies focus on instilling doubt and encouraging people to examine the roots of their beliefs. In these situations, tone can also play a role: expressing empathy and understanding can keep communication channels open. Researchers have identified three ways to increase the efficacy of these social corrections for observers. Interestingly, while the tone of the correction may impact how the target of the correction receives the message and can increase engagement with a message, it is less likely to affect how others seeing the correction perceive its accuracy. While social correction has the potential to reach a wider audience with correct information, it can also potentially amplify an original post containing misinformation. Prebunking Misinformation typically spreads more readily than fact-checking. While prebunking can involve fact-based correction, it focuses more on identifying common logical fallacies (e.g., emotional appeals to manipulate individuals' perceptions and judgments, false dichotomies, or ad hominem fallacies) and tactics used to spread misinformation as well as common misinformation sources. Other interventions A report by the Royal Society in the UK lists additional potential or proposed countermeasures: • New Jersey mandated K-12 students to learn information literacy • "Inoculation" via educational videos shown to adults is being explored Broadly described, the report recommends building resilience to scientific misinformation and a healthy online information environment and not having offending content removed. It cautions that censorship could e.g. drive misinformation and associated communities "to harder-to-address corners of the internet". Online misinformation about climate change can be counteracted through different measures at different stages. Prior to misinformation exposure, education and "inoculation" are proposed. Technological solutions, such as early detection of bots and ranking and selection algorithms are suggested as ongoing mechanisms. Post misinformation, corrective and collaborator messaging can be used to counter climate change misinformation. Incorporating fines and similar consequences has also been suggested. The International Panel on the Information Environment was launched in 2023 as a consortium of over 250 scientists working to develop effective countermeasures to misinformation and other problems created by perverse incentives in organizations disseminating information via the Internet. There also is research and development of platform-built-in as well as browser-integrated (currently in the form of addons) misinformation mitigation. This includes quality/neutrality/reliability ratings for news sources. Wikipedia's perennial sources page categorizes many large news sources by reliability. Researchers have also demonstrated the feasibility of falsity scores for popular and official figures by developing such for over 800 contemporary elites on Twitter as well as associated exposure scores. Strategies that may be more effective for lasting correction of false beliefs include focusing on intermediaries (such as convincing activists or politicians who are credible to the people who hold false beliefs, or promoting intermediaries who have the same identities or worldviews as the intended audience), minimizing the association of misinformation with political or group identities (such as providing corrections from nonpartisan experts, or avoiding false balance based on partisanship in news coverage), and emphasizing corrections that are hard for people to avoid or deny (such as providing information that the economy is unusually strong or weak, or describing the increased occurrence of extreme weather events in response to climate change denial). AI as a tool to combat misinformation • Fact-checking algorithms are employed to fact-check truth claims in real-time. • Researchers are developing AI tools for detecting fabricated audio and video. • AI can be used for Information literacy and Media literacy education. Limitations Interventions need to account for the possibility that misinformation can persist in the population even after corrections are published. Possible reasons include difficulty in reaching the right people and corrections not having long-term effects. A 2020 review of the scientific literature on backfire effects found that there have been widespread failures to replicate their existence, even under conditions that would be theoretically favorable to observing them. Due to the lack of reproducibility, most researchers believe that backfire effects are either unlikely to occur on the broader population level, or they only occur in very specific circumstances, or they do not exist. For instance, one study found that inoculation and accuracy primes to some extent undermined users' ability to distinguish implausible from plausible conspiracy theories. Other scholars have shown through simulations that even if interventions reduce both the belief in false and true information, the effect on the media ecosystem may still be favorable due to different base rates in both beliefs. == Online misinformation ==

In recent years, the proliferation of misinformation online has drawn widespread attention. More than half of the world's population had access to the Internet in the beginning of 2018. However, the underlying factor is that it contains misleading or inaccurate information. On social media Pew Research reports shared that approximately one in four American adults admitted to sharing misinformation on their social media platforms. In the Information Age, social networking sites have become a notable agent for the spread of misinformation, fake news, and propaganda. Spread Social media platforms allow for easy spread of misinformation. Reasons for sharing misinformation on social media are varied, which can include presenting a conversation topic, finding the content interesting, and expressing an opinion. Agent-based models and other computational models have been used by researchers to explain how false beliefs spread through networks. Epistemic network analysis is one example of a computational method for evaluating connections in data shared in a social media network or similar network. Researchers fear that misinformation in social media is "becoming unstoppable". Sites such as Facebook have algorithms that have been proven to further the spread of misinformation in which how content is spread among subgroups. Social causes and echo chambers Spontaneous spread of misinformation on social media usually occurs from users sharing posts from friends or mutually-followed pages. People are inclined to follow or support like-minded individuals, creating echo chambers and filter bubbles. Research has also shown that viral misinformation may spread more widely as a result of echo chambers, as the echo chambers provide an initial seed which can fuel broader viral diffusion. Misinformation might be created and spread with malicious intent for reasons such as causing anxiety or deceiving audiences. Computational Propaganda actors benefit from both disinformation and misinformation. Rumors created with or without malicious intent may be unknowingly shared by users. People may know what the scientific community has proved as a fact, and still refuse to accept it as such. Lack of regulation Misinformation on social media spreads quickly in comparison to traditional media because of the lack of regulation and examination required before posting. This lack of regulation creates an environment where speed is prioritized over accuracy on social media. Because editorial oversight is not required, inaccurate or misleading posts can circulate widely before any fact-checkers or experts even become aware of them. Social media sites provide users with the capability to spread information quickly to other users without requiring the permission of a gatekeeper such as an editor or fact checker. The architecture of social platforms intensifies this issue, with features such as algorithmic amplification—which prioritizes highly emotional or engaging content—boosting the spread of misinformation because sensational and catching posts perform better. The problem of misinformation in social media is getting worse as younger generations prefer social media over journalistic for their source of information. Lack of peer review File:In Peer Review We Trust.jpg|thumb|Promoting more peer review to benefit the accuracy in information|alt=A protestor in a crowd holds up a sign reading, in the Comic Sans font: In Peer Review [(footnote 1 and 2)] We Trust / (and Comic Sans). Below, footnote 1 reads "except those predatory journals. Don't trust those. See Nature 543, 481–483 (23 March 2017) doi:10.1038/5434812"; footnote 2 reads "let's not start an academic debate about the flaws of peer review when the alternative is to trust someone's gut feeling" Due to the decentralized nature and structure of the Internet, content creators can easily publish content without being required to undergo peer review, prove their qualifications, or provide backup documentation. While library books have generally been reviewed and edited by an editor, publishing company, etc., Internet sources cannot be assumed to be vetted by anyone other than their authors. Misinformation may be produced, reproduced, and posted immediately on most online platforms. Countermeasures Combating the spread of misinformation on social media is difficult for reasons such as: • The profusion of misinformation sources makes the reader's task of weighing the reliability of information more challenging. • Social media's propensity for culture wars embeds misinformation with identity-based conflict. • The proliferation of echo chambers form an epistemic environment in which participants encounter beliefs and opinions that coincide with their own, moving the entire group toward more extreme positions. Journalists today are criticized for helping to spread false information on these social platforms, but research shows they also play a role in curbing it through debunking and denying false rumors. TikTok's design also plays a role in how quickly misleading information can spread. Because the app centers short, fast-moving videos, people often scroll without pausing to fact-check what they are watching. Content that feels personal or relatable can seem trustworthy even when it is not, which makes false claims easier to believe and share. Researchers have noted that this casual style of communication—combined with TikTok's fast-paced feed—creates an environment where emotionally charged or sensational posts gain attention quickly, even if the information is inaccurate. Several misinformation trends have gone viral on TikTok, including false COVID-19 cure claims, political rumors, fabricated crisis updates, and misleading safety warnings. During the pandemic, TikTok was widely criticized for videos promoting unproven home remedies and conspiracy theories. Other examples include viral hoaxes such as fake school threats and exaggerated weather alerts, which spread quickly because users tend to share alarming content without verifying it. TikTok's recommendation system is designed to prioritize content based on engagement, which can unintentionally elevate misleading or false claims. A 2022 investigation by the Center for Countering Digital Hate found that TikTok recommended misinformation within minutes of creating new accounts, including content related to public health and political events. Scholars note that because the algorithm optimizes for watch time and interaction, posts containing misinformation can be amplified even without coordinated manipulation. Misinformation on Facebook A research study of Facebook found that misinformation was more likely to be clicked on than factual information. The most common reasons that Facebook users were sharing misinformation for socially-motivated reasons, rather than taking the information seriously. Facebook's coverage of misinformation has become a hot topic with the spread of COVID-19, as some reports indicated Facebook recommended pages containing health misinformation. For example, this can be seen when a user likes an anti-vax Facebook page. Automatically, more and more anti-vax pages are recommended to the user. and has taken measures to stop the spread of misinformation, resulting in a decrease, though misinformation continues to exist on the platform. Misinformation on Twitter Twitter is one of the most concentrated platforms for engagement with political fake news. 80% of fake news sources are shared by 0.1% of users, who are "super-sharers". Older, more conservative social users are also more likely to interact with fake news. Bot accounts on Twitter accelerate true and fake news at the same rate. A 2018 study of Twitter determined that, compared to accurate information, false information spread significantly faster, further, deeper, and more broadly. A social media app called Parler has caused much chaos as well. Right winged Twitter users who were banned on the app moved to Parler after the January 6 United States Capitol attack, and the app was being used to plan and facilitate more illegal and dangerous activities. Google and Apple later pulled the app off their respective app stores. This app has been able to cause a lot of misinformation and bias in the media, allowing for more political mishaps. Misinformation on Telegram Telegram has been accused multiple times of facilitating the creation and spread of misinformation online, partly due to its deregulation and lack of fact-checking tools. Misinformation on YouTube == Impact ==

Trust of other information The Liar's Dividend describes a situation in which individuals are so concerned about realistic misinformation (in particular, deepfakes) that they begin to mistrust real content, particularly if someone claims that it is false. For instance, a politician could benefit from claiming that a real video of them doing something embarrassing was actually AI-generated or altered, leading followers to mistrust something that was actually real. On a larger scale this problem can lead to erosion in the public's trust of generally reliable information sources. When eavesdropping on conversations, one can gather facts that may not always be true, or the receiver may hear the message incorrectly and spread the information to others. On the Internet, one can read content that is stated to be factual but that may not have been checked or may be erroneous. In the news, companies may emphasize the speed at which they receive and send information but may not always be correct in the facts. These developments contribute to the way misinformation may continue to complicate the public's understanding of issues and to serve as a source for belief and attitude formation. Politics Some view being a politically misinformed citizen as worse than being an uninformed one. Misinformed citizens can state their beliefs and opinions with confidence and thus affect elections and policies. This type of misinformation occurs when a speaker appears "authoritative and legitimate", while also spreading misinformation. Misinformation has the power to sway public elections and referendums if it gains enough momentum. Leading up to the 2016 UK European Union membership referendum, for example, a figure used prominently by the Vote Leave campaign claimed that by leaving the EU the UK would save £350 million a week, 'for the NHS'. Claims then circulated widely in the campaign that this amount would (rather than could theoretically) be redistributed to the British National Health Service after Brexit. This was later deemed a "clear misuse of official statistics" by the UK statistics authority. Moreover, the advert infamously shown on the side of London's double-decker busses did not take into account the UK's budget rebate, and the idea that 100% of the money saved would go to the NHS was unrealistic. A poll published in 2016 by Ipsos MORI found that nearly half of the British public believed this misinformation to be true. Even when information is proven to be misinformation, it may continue to shape attitudes towards a given topic, meaning it has the power to swing political decisions if it gains enough traction. A study conducted by Soroush Vosoughi, Deb Roy and Sinan Aral looked at Twitter data including 126,000 posts spread by 3 million people over 4.5 million times. They found that political news traveled faster than any other type of information. They found that false news about politics reached more than 20,000 people three times faster than all other types of false news. Industry Misinformation can also be employed in industrial propaganda. Using tools such as advertising, a company can undermine reliable evidence or influence belief through a concerted misinformation campaign. For instance, tobacco companies employed misinformation in the second half of the twentieth century to diminish the reliability of studies that demonstrated the link between smoking and lung cancer. Medicine In the medical field, misinformation can immediately lead to life endangerment as seen in the case of the public's negative perception towards vaccines or the use of herbs instead of medicines to treat diseases. In regards to the COVID-19 pandemic, the spread of misinformation has proven to cause confusion as well as negative emotions such as anxiety and fear. Misinformation regarding proper safety measures for the prevention of the virus that go against information from legitimate institutions like the World Health Organization can also lead to inadequate protection and possibly place individuals at risk for exposure. Study Some scholars and activists are heading movements to eliminate the mis/disinformation and information pollution in the digital world. The general study of misinformation and disinformation is by now also common across various academic disciplines, including sociology, communication, computer science, and political science. Various scholars and journalists have criticised this development, pointing to problematic normative assumptions, a varying quality of output and lack of methodological rigor, as well as a too strong impact of mis- and disinformation research in shaping public opinion and policymaking. Summarising the most frequent points of critique, communication scholars Chico Camargo and Felix Simon wrote in an article for the Harvard Kennedy School Misinformation Review that "mis-/disinformation studies has been accused of lacking clear definitions, having a simplified understanding of what it studies, a too great emphasis on media effects, a neglect of intersectional factors, an outsized influence of funding bodies and policymakers on the research agenda of the field, and an outsized impact of the field on policy and policymaking." == Censorship accusations ==

Social media sites such as Facebook and Twitter have found themselves defending accusations of censorship for removing posts they have deemed to be misinformation. Social media censorship policies relying on government agency-issued guidance to determine information validity have garnered criticism that such policies have the unintended effect of stifling dissent and criticism of government positions and policies. Most recently, social media companies have faced criticism over allegedly prematurely censoring the discussion of the SARS-CoV 2 Lab Leak Hypothesis. Other accusations of censorship appear to stem from attempts to prevent social media consumers from self-harm through the use of unproven COVID-19 treatments. For example, in July 2020, a video went viral showing Dr. Stella Immanuel claiming hydroxychloroquine was an effective cure for COVID-19. In the video, Immanuel suggested that there was no need for masks, school closures, or any kind of economic shut down, attesting that her alleged cure was highly effective in treating those infected with the virus. The video was shared 600,000 times and received nearly 20 million views on Facebook before it was taken down for violating community guidelines on spreading misinformation. The video was also taken down on Twitter overnight, but not before former president Donald Trump shared it on his page, which was followed by over 85 million Twitter users. NIAID director Dr. Anthony Fauci and members of the World Health Organization (WHO) quickly discredited the video, citing larger-scale studies of hydroxychloroquine showing it is not an effective treatment of COVID-19, and the FDA cautioned against using it to treat COVID-19 patients following evidence of serious heart problems arising in patients who have taken the drug. Another prominent example of misinformation removal criticized by some as an example of censorship was the New York Post report on the Hunter Biden laptops approximately two weeks before the 2020 presidential election, which was used to promote the Biden–Ukraine conspiracy theory. Social media companies quickly removed this report, and the Post's Twitter account was temporarily suspended. Over 50 intelligence officials found the disclosure of emails allegedly belonging to Joe Biden's son had all the "classic earmarks of a Russian information operation". Later evidence emerged that at least some of the laptop's contents were authentic. == See also ==