Fact-checking is the act of checking factual infomention in non-fictional text in order to determine the veracity and correctness of the factual statements in the text. This may be done either before (ante hoc) or after (post hoc) the text has been published or otherwise disseminated.[1] Fact-checking may be done privately, such as when a magazine editor wants to verify the contents of a news article, either before or after publication. This is called internal fact-checking.[2] Alternatively, the fact-checking analysis may be published, in which case it is called external fact-checking.[2]

Ante hoc fact-checking (fact-checking before dissemination) aims to remove errors and allow text to proceed to dissemination (or to rejection if it fails confirmations or other criteria). Post hoc fact-checking is most often followed by a written report of inaccuracies, sometimes with a visual metric from the checking organization (e.g., Pinocchios from The Washington Post Fact Checker, or TRUTH-O-METER ratings from PolitiFact). Several organizations are devoted to post hoc fact-checking, such as FactCheck.org and PolitiFact.

Research on the impact of fact-checking is relatively recent but the existing research suggests that fact-checking does indeed correct misperceptions among citizens, as well as discourage politicians from spreading misinformation.

Post hoc fact-checking

External post hoc fact-checking by independent organizations began in the United States in the early 2000s.[2]

Consistency across fact-checkers

One study finds that fact-checkers PolitiFact, FactCheck.org, and Washington Post's Fact Checker overwhelmingly agree on their evaluations of claims.[3][4] However, a study by Morgan Marietta, David C. Barker and Todd Bowser found "substantial differences in the questions asked and the answers offered." They concluded that this limited the "usefulness of fact-checking for citizens trying to decide which version of disputed realities to believe."[5] A paper by Chloe Lim, PhD student at Stanford University, found little overlap in the statements that fact-checkers check. Out of 1065 fact-checks by PolitiFact and 240 fact-checks by The Washington Post's Fact-Checker, there were only 70 statements that both fact-checkers checked. The study found that the fact-checkers gave consistent ratings for 56 out of 70 statements, which means that one out every five times, the two fact-checkers disagree on the accuracy of statements.[6]


Studies of post hoc fact-checking have made clear that such efforts often result in changes in the behavior, in general, of both the speaker (making them more careful in their pronouncements) and of the listener or reader (making them more discerning with regard to the factual accuracy of content); observations include the propensities of audiences to be completely unswayed by corrections to errors regarding the most divisive subjects, or the tendency to be more greatly persuaded by corrections of negative reporting (e.g., "attack ads"), and to see minds changed only when the individual in error was someone reasonably like-minded to begin with.[7]

Correcting misperceptions

A 2015 study found evidence a "backfire effect" (correcting false information may make partisan individuals cling more strongly to their views): "Corrective information adapted from the Centers for Disease Control and Prevention (CDC) website significantly reduced belief in the myth that the flu vaccine can give you the flu as well as concerns about its safety. However, the correction also significantly reduced intent to vaccinate among respondents with high levels of concern about vaccine side effects—a response that was not observed among those with low levels of concern."[8] A 2017 study attempted to replicate the findings of the 2015 study but failed to do so.[9]

A 2016 study found little evidence for the "backfire effect": "By and large, citizens heed factual information, even when such information challenges their partisan and ideological commitments."[10] A study of Donald Trump supporters during the 2016 race similarly found little evidence for the backfire effect: "When respondents read a news article about Mr. Trump's speech that included F.B.I. statistics indicating that crime had "fallen dramatically and consistently over time," their misperceptions about crime declined compared with those who saw a version of the article that omitted corrective information (though misperceptions persisted among a sizable minority)."[11][12] A 2018 study found no evidence of a backfire effect.[13]

Studies have shown that fact-checking can affect citizens' belief in the accuracy of claims made in political advertisement.[14] A paper by a group of Paris School of Economics and Sciences Po economists found that falsehoods by Marine Le Pen during the 2017 French presidential election campaign (i) successfully persuaded voters, (ii) lost their persuasiveness when fact-checked, and (iii) did not reduce voters' political support for Le Pen when her claims were fact-checked.[15] A 2017 study in the Journal of Politics found that "individuals consistently update political beliefs in the appropriate direction, even on facts that have clear implications for political party reputations, though they do so cautiously and with some bias... Interestingly, those who identify with one of the political parties are no more biased or cautious than pure independents in their learning, conditional on initial beliefs."[16]

A study by Yale University cognitive scientists Gordon Pennycook and David G. Rand found that Facebook tags of fake articles "did significantly reduce their perceived accuracy relative to a control without tags, but only modestly".[17] A Dartmouth study led by Brendan Nyhan found that Facebook tags had a greater impact than the Yale study found.[18][19] A "disputed" tag on a false headline reduced the number of respondents who considered the headline accurate from 29% to 19%, whereas a "rated false" tag pushed the number down to 16%.[18] A 2019 study found that the "disputed" tag reduced Facebook users' intentions to share a fake news story.[20] The Yale study found evidence of a backfire effect among Trump supporters younger than 26 years whereby the presence of both untagged and tagged fake articles made the untagged fake articles appear more accurate.[17] In response to research which questioned the effectiveness of the Facebook "disputed" tags, Facebook decided to drop the tags in December 2017 and would instead put articles which fact-checked a fake news story next to the fake news story link whenever it is shared on Facebook.[21]

Based on the findings of a 2017 study in the journal Psychological Science, the most effective ways to reduce misinformation through corrections is by:[22]

  • limiting detailed descriptions of / or arguments in favor of the misinformation;
  • walking through the reasons why a piece of misinformation is false rather than just labelling it false;
  • presenting new and credible information which allows readers to update their knowledge of events and understand why they developed an inaccurate understanding in the first place;
  • using video, as videos appear to be more effective than text at increasing attention and reducing confusion, making videos more effective at correcting misperception than text.

A 2019 meta-analysis of research into the effects of fact-checking on misinformation found that fact-checking has substantial positive impacts on political beliefs, but that this impact weakened when fact-checkers used "truth scales", refuted only parts of a claim and when they fact-checked campaign-related statements. Individuals' preexisting beliefs, ideology, and knowledge affected to what extent the fact-checking had an impact.[23] A 2019 study in the Journal of Experimental Political Science found "strong evidence that citizens are willing to accept corrections to fake news, regardless of their ideology and the content of the fake stories."[24]

A paper by Andrew Guess (of Princeton University), Brendan Nyhan (Dartmouth College) and Jason Reifler (University of Exeter) found that consumers of fake news tended to have less favorable views of fact-checking, in particular Trump supporters.[25] The paper found that fake news consumers rarely encountered fact-checks: "only about half of the Americans who visited a fake news website during the study period also saw any fact-check from one of the dedicated fact-checking website (14.0%)."[25]

A 2018 study found that Republicans were more likely to correct their false information on voter fraud if the correction came from Breitbart News rather than a non-partisan neutral source such as PolitiFact.[26]

Political discourse

A 2015 experimental study found that fact-checking can encourage politicians to not spread misinformation. The study found that it might help improve political discourse by increasing the reputational costs or risks of spreading misinformation for political elites. The researchers sent, "a series of letters about the risks to their reputation and electoral security if they were caught making questionable statements. The legislators who were sent these letters were substantially less likely to receive a negative fact-checking rating or to have their accuracy questioned publicly, suggesting that fact-checking can reduce inaccuracy when it poses a salient threat."[27]

Political preferences

One experimental study found that fact-checking during debates affected viewers' assessment of the candidates' debate performance and "greater willingness to vote for a candidate when the fact-check indicates that the candidate is being honest."[28]

A study of Trump supporters during the 2016 presidential campaign found that while fact-checks of false claims made by Trump reduced his supporters' belief in the false claims in question, the corrections did not alter their attitudes towards Trump.[29]

A 2019 study found that "summary fact-checking", where the fact-checker summarizes how many false statements a politician has made, has a greater impact on reducing support for a politician than fact-checking of individual statements made by the politician.[30]

Controversies and criticism

Political fact-checking is sometimes criticized as being opinion journalism.[31][32] In September 2016, a Rasmussen Reports national telephone and online survey found that "just 29% of all Likely U.S. Voters trust media fact-checking of candidates' comments. Sixty-two percent (62%) believe instead that news organizations skew the facts to help candidates they support."[33][34]

Informal fact-checking

Individual readers perform some types of fact-checking, such as comparing claims in one news story against claims in another.

Rabbi Moshe Benovitz, has observed that: "modern students use their wireless worlds to augment skepticism and to reject dogma." He says this has positive implications for values development:

"Fact-checking can become a learned skill, and technology can be harnessed in a way that makes it second nature… By finding opportunities to integrate technology into learning, students will automatically sense the beautiful blending of… their cyber… [and non-virtual worlds]. Instead of two spheres coexisting uneasily and warily orbiting one another, there is a valuable experience of synthesis…".[35]

Detecting fake news

Fake news has become increasingly prevalent over the last few years, with over a 100 incorrect articles and rumors spread incessantly just with regard to the 2016 United States presidential election.[36] These fake news articles tend to come from satirical news websites or individual websites with an incentive to propagate false information, either as clickbait or to serve a purpose.[36] Since these articles typically hope to intentionally promote incorrect information, these articles are quite difficult to detect.[37] When identifying a source of information, one must look at many attributes, including but not limited to the content of the email and social media engagements.[37] The language, specifically, is typically more inflammatory in fake news than real articles, in part because the purpose is to confuse and generate clicks.[37] Furthermore, modeling techniques such as n-gram encodings and bag of words have served as other linguistic techniques to determine the legitimacy of a news course.[37] On top of that, researchers have determined that visual-based cues also play a factor in categorizing an article, specifically some features can be designed to assess if a picture was legitimate, and provides us more clarity on the news.[37] There is also many social context features that can play a role, as well as the model of spreading the news. Websites such as “Snopes” try to detect this information manually, while certain universities are trying to build mathematical models to do this themselves.[36]

Organizations and individuals

Some individuals and organizations publish their fact-checking efforts on the internet. These may have a special subject-matter focus, such as Snopes.com's focus on urban legends or the Reporters' Lab at Duke University's focus on providing resources to journalists.

On-going Research in Fact-checking and Detecting Fake News

Since the 2016 United States presidential election, fake news has been a popular topic of discussion by President Trump and news outlets. The reality of fake news had become omnipresent, and a lot of research has gone into understanding, identifying, and combating fake news. Also, a number of researchers began with the usage of fake news to influence the 2016 presidential campaign. One research found evidence of pro-Trump fake news being selectively targeted on conservatives and pro-Trump supporters in 2016.[38] The researchers found that social media sites, Facebook in particular, to be powerful platforms to spread certain fake news to targeted groups to appeal to their sentiments during the 2016 presidential race. Additionally, researchers from Stanford, NYU, and NBER found evidence to show how engagement with fake news on Facebook and Twitter was high throughout 2016.[39] Recently, a lot of work has gone into detecting and identifying fake news through machine learning and artificial intelligence. In 2018, researchers at MIT's CSAIL (Computer Science and Artificial Intelligence Lab) created and tested a machine learning algorithm to identify false information by looking for common patterns, words, and symbols that typically appear in fake news.[40] More so, they released an open-source data set with a large catalog of historical news sources with their veracity scores to encourage other researchers to explore and develop new methods and technologies for detecting fake news.

Despite the ongoing research at top universities and institutions, there is much debate on the effectiveness of such technology in identifying fake news. There is still not enough good training data for machine learning and AI scientists to use to create very accurate predictive models on detecting fake news. Nonetheless, a lot of research is still ongoing to better understand fake news and their characteristics.

Ante hoc fact-checking

Among the benefits of printing only checked copy is that it averts serious, sometimes costly, problems. These problems can include lawsuits for mistakes that damage people or businesses, but even small mistakes can cause a loss of reputation for the publication. The loss of reputation is often the more significant motivating factor for journalists.[41]

Fact checkers verify that the names, dates, and facts in an article or book are correct.[41] For example, they may contact a person who is quoted in a proposed news article and ask the person whether this quotation is correct, or how to spell the person's name. Fact-checkers are primarily useful in catching accidental mistakes; they are not guaranteed safeguards against those who wish to commit journalistic frauds.

As a career

Professional fact checkers have generally been hired by newspapers, magazines, and book publishers, probably starting in the early 1920s with the creation of Time magazine in the US.[41][2] Fact checkers may be aspiring writers, future editors, or freelancers engaged other projects; others are career professionals.[41]

Historically, the field was considered women's work, and from the time of the first professional American fact checker through at least the 1970s, the fact checkers at a media company might be entirely female or primarily so.[41]

The number of people employed in fact-checking varies by publication. Some organizations have substantial fact-checking departments. For example, The New Yorker magazine had 16 fact checkers in 2003.[41] Others may hire freelancers per piece, or may combine fact-checking with other duties. Magazines are more likely to use fact checkers than newspapers.[2] Television and radio programs rarely employ dedicated fact checkers, and instead expect others, including senior staff, to engage in fact-checking in addition to their other duties.[41]

Checking original reportage

Stephen Glass began his journalism career as a fact-checker. He went on to invent fictitious stories, which he submitted as reportage, and which fact-checkers at The New Republic (and other weeklies for which he worked) never flagged. Michael Kelly, who edited some of Glass's concocted stories, blamed himself, rather than the fact-checkers, saying: "Any fact-checking system is built on trust ... If a reporter is willing to fake notes, it defeats the system. Anyway, the real vetting system is not fact-checking but the editor."[42]

Education on fact-checking

With the circulation of fake news on the internet, many organizations have dedicated time to create guidelines to help read to verify the information they are consuming. Many universities across America provide university students resources and tools to help them verify their sources. Universities provide access to research guides that help students conduct thorough research with reputable sources within academia. Organizations like FactCheck.org, OntheMedia.org, and PolitiFact.com provide procedural guidelines that help individuals navigate the process to fact-check a source.

Books on professional fact-checking

  • Sarah Harrison Smith spent some time and also headed the fact-checking department for The New York Times. She is the author of the book, The Fact Checker's Bible.
  • Jim Fingal worked for several years as a fact-checker at The Believer and McSweeney's and is co-author with John D'Agata of The Lifespan of a Fact which is an inside look at the struggle between fact-checker (Fingal) and author (D'Agata) over an essay that pushed the limits of the acceptable "artistic license" for a non-fiction work.

Alumni of the role

The following is a list of individuals for whom it has been reported, reliably, that they have played such a fact-checking role at some point in their careers, often as a stepping point to other journalistic endeavors, or to an independent writing career:

See also


  1. Fellmeth, Aaron X.; Horwitz, Maurice (2009). "Ante hoc". Guide to Latin in International Law. Oxford University Press. doi:10.1093/acref/9780195369380.001.0001. ISBN 978-0-19-536938-0.
  2. Graves, Lucas; Amazeen, Michelle A. (25 February 2019), "Fact-Checking as Idea and Practice in Journalism", Oxford Research Encyclopedia of Communication, Oxford University Press, doi:10.1093/acrefore/9780190228613.013.808, ISBN 9780190228613
  3. Amazeen, Michelle A. (1 October 2016). "Checking the Fact-Checkers in 2008: Predicting Political Ad Scrutiny and Assessing Consistency". Journal of Political Marketing. 15 (4): 433–464. doi:10.1080/15377857.2014.959691. hdl:2144/27297. ISSN 1537-7857.
  4. Amazeen, Michelle A. (2 January 2015). "Revisiting the Epistemology of Fact-Checking". Critical Review. 27 (1): 1–22. doi:10.1080/08913811.2014.993890. hdl:2144/27304. ISSN 0891-3811.
  5. Marietta, Morgan; Barker, David C.; Bowser, Todd (2015). "Fact-Checking Polarized Politics: Does The Fact-Check Industry Provide Consistent Guidance on Disputed Realities?" (PDF). The Forum. 13 (4): 577. doi:10.1515/for-2015-0040. Retrieved 27 September 2016.
  6. "Checking how fact-checkers check".
  7. Amazeen, Michelle (2015) "Monkey Cage: Sometimes political fact-checking works. Sometimes it doesn't. Here's what can make the difference.," The Washington Post (online), 3 June 2015, see , accessed 27 July 2015.
  8. Nyhan, Brendan; Reifler, Jason (9 January 2015). "Does correcting myths about the flu vaccine work? An experimental evaluation of the effects of corrective information" (PDF). Vaccine. 33 (3): 459–464. doi:10.1016/j.vaccine.2014.11.017. hdl:10871/21566. ISSN 1873-2518. PMID 25499651.
  9. Haglin, Kathryn (1 July 2017). "The limitations of the backfire effect". Research & Politics. 4 (3): 2053168017716547. doi:10.1177/2053168017716547. ISSN 2053-1680.
  10. Wood, Thomas; Porter, Ethan (5 August 2016). "The Elusive Backfire Effect: Mass Attitudes' Steadfast Factual Adherence". SSRN 2819073. Cite journal requires |journal= (help)
  11. Nyhan, Brendan (5 November 2016). "Fact-Checking Can Change Views? We Rate That as Mostly True". The New York Times. ISSN 0362-4331. Retrieved 5 November 2016.
  12. Nyhan, Brendan; Porter, Ethan; Reifler, Jason; Wood, Thomas J. (21 January 2019). "Taking Fact-Checks Literally But Not Seriously? The Effects of Journalistic Fact-Checking on Factual Beliefs and Candidate Favorability". Political Behavior. doi:10.1007/s11109-019-09528-x. ISSN 1573-6687.
  13. Guess, Andrew; Coppock, Alexander (2018). "Does Counter-Attitudinal Information Cause Backlash? Results from Three Large Survey Experiments". British Journal of Political Science: 1–19. doi:10.1017/S0007123418000327. ISSN 0007-1234.
  14. Fridkin, Kim; Kenney, Patrick J.; Wintersieck, Amanda (2 January 2015). "Liar, Liar, Pants on Fire: How Fact-Checking Influences Citizens' Reactions to Negative Advertising". Political Communication. 32 (1): 127–151. doi:10.1080/10584609.2014.914613. ISSN 1058-4609.
  15. Rodriguez, Barrera; David, Oscar; Guriev, Sergei M.; Henry, Emeric; Zhuravskaya, Ekaterina (18 July 2017). "Facts, Alternative Facts, and Fact Checking in Times of Post-Truth Politics". SSRN 3004631. Cite journal requires |journal= (help)
  16. Hill, Seth J. (16 August 2017). "Learning Together Slowly: Bayesian Learning about Political Facts". The Journal of Politics. 79 (4): 1403–1418. doi:10.1086/692739. ISSN 0022-3816.
  17. Pennycook, Gordon; Rand, David G. (12 September 2017). "Assessing the Effect of "Disputed" Warnings and Source Salience on Perceptions of Fake News Accuracy". SSRN 3035384. Cite journal requires |journal= (help)
  18. Nyhan, Brendan (23 October 2017). "Why the Fact-Checking at Facebook Needs to Be Checked". The New York Times. ISSN 0362-4331. Retrieved 23 October 2017.
  19. Clayton, Katherine; Blair, Spencer; Busam, Jonathan A.; Forstner, Samuel; Glance, John; Green, Guy; Kawata, Anna; Kovvuri, Akhila; Martin, Jonathan (11 February 2019). "Real Solutions for Fake News? Measuring the Effectiveness of General Warnings and Fact-Check Tags in Reducing Belief in False Stories on Social Media". Political Behavior. doi:10.1007/s11109-019-09533-0. ISSN 1573-6687.
  20. Mena, Paul (2019). "Cleaning Up Social Media: The Effect of Warning Labels on Likelihood of Sharing False News on Facebook". Policy & Internet. 0. doi:10.1002/poi3.214. ISSN 1944-2866.
  21. "Facebook stops putting "Disputed Flags" on fake news because it doesn't work". Axios. 27 December 2017. Retrieved 28 December 2017.
  22. Chokshi, Niraj (18 September 2017). "How to Fight 'Fake News' (Warning: It Isn't Easy)". The New York Times. ISSN 0362-4331. Retrieved 19 September 2017.
  23. Walter, Nathan; Cohen, Jonathan; Holbert, R. Lance; Morag, Yasmin (24 October 2019). "Fact-Checking: A Meta-Analysis of What Works and for Whom". Political Communication. 0: 1–26. doi:10.1080/10584609.2019.1668894. ISSN 1058-4609.
  24. Porter, Ethan; Wood, Thomas J.; Kirby, David (2018). "Sex Trafficking, Russian Infiltration, Birth Certificates, and Pedophilia: A Survey Experiment Correcting Fake News". Journal of Experimental Political Science. 5 (2): 159–164. doi:10.1017/XPS.2017.32. ISSN 2052-2630.
  25. "Selective Exposure to Misinformation: Evidence from the consumption of fake news during the 2016 U.S. presidential campaign" (PDF).
  26. Holman, Mirya R.; Lay, J. Celeste (2018). "They See Dead People (Voting): Correcting Misperceptions about Voter Fraud in the 2016 U.S. Presidential Election". Journal of Political Marketing. 18 (1–2): 31–68. doi:10.1080/15377857.2018.1478656.
  27. Nyhan, Brendan; Reifler, Jason (1 July 2015). "The Effect of Fact-Checking on Elites: A Field Experiment on U.S. State Legislators". American Journal of Political Science. 59 (3): 628–40. doi:10.1111/ajps.12162. hdl:10871/21568. ISSN 1540-5907.
  28. Wintersieck, Amanda L. (5 January 2017). "Debating the Truth". American Politics Research. 45 (2): 304–331. doi:10.1177/1532673x16686555.
  29. Nyhan, Brendan; Porter, Ethan; Reifler, Jason; Wood, Thomas J. (n.d.). "Taking Fact-checks Literally But Not Seriously? The Effects of Journalistic Fact-checking on Factual Beliefs and Candidate Favorability" (PDF).
  30. Agadjanian, Alexander; Bakhru, Nikita; Chi, Victoria; Greenberg, Devyn; Hollander, Byrne; Hurt, Alexander; Kind, Joseph; Lu, Ray; Ma, Annie; Nyhan, Brendan; Pham, Daniel (1 July 2019). "Counting the Pinocchios: The effect of summary fact-checking data on perceived accuracy and favorability of politicians". Research & Politics. 6 (3): 2053168019870351. doi:10.1177/2053168019870351. ISSN 2053-1680.
  31. Riddell, Kelly (26 September 2016). "Eight examples where 'fact-checking' became opinion journalism". Washington Times. Retrieved 27 September 2016.
  32. Graves, Lucas (2016). Deciding What's True: The Rise of Political Fact-Checking in American Journalism. Columbia University Press. p. 27. ISBN 9780231542227. Retrieved 27 September 2016.
  33. Reports, Rasmussen. "Voters Don't Trust Media Fact-Checking – Rasmussen Reports™". Retrieved 17 October 2016.
  34. Lejeune, Tristan (30 September 2016). "Poll: Voters don't trust media fact-checkers". Retrieved 17 October 2016.
  35. Moshe Benovitz et al., 2012, "Education: The Social Media Revolution: What Does It Mean for Our Children?" Jewish Action (online), 24 August 2012, New York, NY, USA:Orthodox Union, see , accessed 28 July 2015.
  36. Allcott, Hunt (2017). "Social Media and Fake News in the 2016 Election." The Journal of Economic Perspectives" (PDF). The Journal of Economic Perspectives. 31: 211–235. doi:10.1257/jep.31.2.211 via JSTOR.
  37. Liu, Huan; Tang, Jiliang; Wang, Suhang; Sliva, Amy; Shu, Kai (7 August 2017). "Fake News Detection on Social Media: A Data Mining Perspective". arXiv:1708.01967v3. Bibcode:2017arXiv170801967S. Cite journal requires |journal= (help)
  38. Guess, Andrew (9 January 2018). "Selective Exposure to Misinformation: Evidence from the consumption of fake news during the 2016 U.S. presidential campaign" (PDF). Dartmouth. Retrieved 5 March 2019.
  39. Allcott, Hunt (October 2018). "Trends in the Diffusion of Misinformation on Social Media" (PDF). Stanford. Retrieved 5 March 2019.
  40. Hao, Karen. "AI is still terrible at spotting fake news". MIT Technology Review. Retrieved 6 March 2019.
  41. Harrison Smith, Sarah (2004). The Fact Checker's Bible: A Guide to Getting it Right. New York: Anchor Books. pp. 8–12. ISBN 0385721064. OCLC 53919260.
  42. John Watson (2 April 2017). "What is Fact Checking? – FactCheck Sri Lanka". Factchecksrilanka.com. Archived from the original on 7 November 2017. Retrieved 7 December 2017.
  43. "An Interview With Susan Choi". Archived from the original on 18 February 2001. Retrieved 18 November 2006.CS1 maint: BOT: original-url status unknown (link)
  44. "CNN.com – Transcripts". Transcripts.cnn.com. 1 June 2006. Retrieved 18 October 2011.
  45. "Contributors". Archived from the original on 19 March 2006. Retrieved 17 November 2006.CS1 maint: BOT: original-url status unknown (link)
  46. "William Gaddis (American author)". Britannica.com. Retrieved 18 October 2011.
  47. Skurnick, Lizzie. "Content". Mediabistro.com. Retrieved 18 October 2011.
  48. "Hodge, Roger D." Archived from the original on 8 March 2007. Retrieved 18 November 2006.CS1 maint: BOT: original-url status unknown (link)
  49. Kirkpatrick, David D. "David Kirkpatrick". The New York Times.
  50. "Swarthmore College Bulletin". Swarthmore.edu. July 2011. Archived from the original on 27 October 2008. Retrieved 18 October 2011.
  51. "Sean Wilsey – About Sean Wilsey – Penguin Group". Us.penguingroup.com. Archived from the original on 27 September 2011. Retrieved 18 October 2011.

Further reading

  1. Lewis-Kraus, Gideon (21 February 2012). "The Fact-Checker Versus the Fabulist". The New York Times. Retrieved 27 July 2015.
  2. "Archived copy". Archived from the original on 8 September 2015. Retrieved 28 July 2015.CS1 maint: archived copy as title (link)
  3. "Wayback Machine" (PDF). Archived from the original on 6 September 2015. Retrieved 7 December 2017.CS1 maint: BOT: original-url status unknown (link)
  4. Bergstrom, Carl; West, Jevin (2017). "Calling Bullshit: Data Reasoning in a Digital World". University of Washington. Retrieved 5 February 2018.
  5. "Calling Bullshit in the Age of Big Data". YouTube. UW iSchool. 10 July 2017. Retrieved 17 February 2018.
  6. Jones, Josh (11 April 2016). "Carl Sagan Presents His "Baloney Detection Kit": 8 Tools for Skeptical Thinking". Open Culture: the best free cultural & educational media on the web. Retrieved 17 February 2018.
  7. Sagan, Carl. "The Fine Art of Baloney Detection" (PDF). Free University of Berlin. Retrieved 17 February 2018.
This article is issued from Wikipedia. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.