Abstract
Personal lies (girl on date lying to dad) and fake news (Obama Bans Pledge of Allegiance) both deceive but in different ways, so they require different detection methods. People in long-term relationships try to tell undetectable lies to encourage, often, audience inaction. In contrast, unattached fake news welcome attention and try to ignite audience action. Thus, they differ in six ways: (a) speaker–audience relationship, (b) goal, (c) emotion, (d) information, (e) number of participants, and (f) citation of sources. To detect personal lies, a person can use their intimate relationship to heighten emotions, raise the stakes, and ask for more information, participants, or sources. In contrast, a person evaluates the legitimacy of potential fake news by examining the websites of its author, the people in the news article, and/or reputable media sources. Large social media companies have suitable expertise, data, and resources to reduce fake news. Search tools, rival news media links to one another’s articles, encrypted signature links, and improved school curricula might also help users detect fake news.
Personal lies and fake news both deceive but in different ways, so they require different detection methods. For example, a teenage girl (let’s call her Ann) on a date lies to her father, “Hi Daddy, I’m sorry I’m late. I was at the mall and lost track of time. I’ll be home in 20 minutes.” This personal lie differs substantially from the fake news article Obama Signs Executive Order Banning the Pledge of Allegiance Nationwide (see the appendix). These two types of deception differ in at least six ways: (a) speaker–audience relationship, (b) goal, (c) emotion, (d) information, (e) number of participants, and (f) citation of sources. People in close relationships tell personal lies to encourage, often, audience inaction via anodyne tales (possibly with emotional distractions) with minimal information, participants, or sources. In contrast, outsiders motivate audience action via fake news with emotional appeals, extensive information, many participants, and authoritative sources. To detect personal lies, a person can use the close relationship to heighten emotions, raise the stakes, and ask for more information, participants, or sources. In contrast, evaluating whether potential fake news is legitimate entails checking websites of the author, new story participants, or reputable media sources. Systemic ways to reduce fake news include corporate responsibility, search tools, encrypted signatures, and school curricula (see Table 1).
Comparison of Personal Lie and Fake News Along Six Dimensions Grounded in Six Theories.
Speaker–Audience Relationship
The relationship between the speaker and the audience determines the possible consequences of a deception. According to game theory (Colman, 2016), at one extreme, they are in a long-term, intimate relationship with substantial knowledge of one another and expect to continue engaging with one another into the distant future (e.g., daughter and father in an infinite repeated game). In the infinite repeated game, the audience has many opportunities to punish the speaker for a lie, so the cost of a detected lie is extremely high. Furthermore, the audience has substantial knowledge of the speaker (e.g., typical speaking patterns), which can increase detection of the lie (e.g., a nervous speaker might talk with atypical speed, duration, volume, pitch, or timbre). Hence, an infinite repeated game speaker has a strong incentive to reduce audience detectability of a lie.
At the other extreme, the speaker and audience are strangers who might not interact again (semi-anonymous email sender/twitter, single stage game). In the single stage game, however, the audience has no future opportunities to punish the speaker, so a detected lie has minimal cost. Furthermore, the audience knows little about the speaker and hence is less likely than otherwise to detect a lie. Hence, a single stage game speaker is less concerned than otherwise about audience detection of a lie.
Goal
The cost and likelihood of lie detection encourages a lower-value, defensive goal of inaction for personal lies rather than the higher-value, offensive goals of actions for fake news (value of a game; Colman, 2016). As detection of a personal lie is both costlier and more likely than that of fake news, a liar tries to reduce audience efforts toward detecting the lie. For example, a liar encourages audience inaction rather than action. When a liar creates an expectation for the audience to do nothing rather than to take action, the audience is more likely to be passive and less likely to exert substantial effort to detect deception.
In the above example, Ann tells her father, “I’ll be home in 20 minutes,” which suggests that her father wait at home (audience inaction) and discourages him from driving to her to pick her up (audience action). As her father is not expected to do anything, he can continue attending to his current activity rather than thinking about her and possibly considering her possible deception. In contrast, if she had asked him to drive to her location and pick her up, he might pay more attention to her story/lie while driving, acquire more information by seeing her at the pickup location, and possibly use it to detect her lie. Hence, a person telling a lie is more likely to seek audience inaction rather than audience action.
In contrast, the lower cost and lower likelihood of detection of fake news compared with personal lies encourages perpetrators to have goals that are more ambitious, so they often seek audience action rather than inaction. As the audience often does not know much about a fake news author, the former must use extensive time and effort to obtain information about the latter. Hence, when people read news for leisure (rather than for work or other practical uses), the cost of the information search often outweighs the benefit of greater confidence in a news story’s validity. Once a person unwittingly shares fake news with friends, relatives, and acquaintances, the fake news is laundered substantially and can spread more credibly throughout their networks. Thus, fake news authors aim for substantial audience action, such as attending protests (e.g., Russian trolls ignited both pro- and anti-Islam protests; Franceschi-Bicchierai, 2017).
Emotion
As emotions shape behaviors, judgments, and attitudes (de Hooge et al., 2008; Frijda, 2007; Garg et al., 2005; Han et al., 2014), arousing appropriate emotions in the listeners or audience can facilitate their inaction (personal lie) or action (fake news). According to appraisal theory, a person’s concerns drive evaluations of a situation (i.e., appraisals), which in turn elicits specific emotions (Lazarus, 1991; Smith & Ellsworth, 1985; Smith & Lazarus, 1993). Although people can evaluate the same event differently, a small set of commonly proposed appraisal dimensions for situational interpretations yields only a few possible appraisals, which enable rough predictions about likely emotional experiences (Ellsworth, 2013).
Dampening Emotions With Anodyne Personal Lies
In the close familial relationship, Ann does not want her father to discover her lie, so she begins with an emotional distraction and then tells an anodyne, unmemorable lie. Her use of a diminutive form (“Daddy”) highlights their close relationship and encourages her father’s warm emotions of love and protectiveness (Schneider, 2003; Sifianou, 1992). Next, she apologizes for a lesser offense (“I’m sorry I’m late”) to preemptively placate his potential anger (Ohbuchi et al., 1989) and distract him from her subsequent lie.
Ann’s lie comprises banal, commonplace events (“at the mall,” “lost track of time”). Her father often goes to the familiar, nearby mall, and not noticing the time is a common, unremarkable occurrence. Unlike new experiences, ordinary situations are appraised quickly and less consciously, especially when they are often-repeated, familiar ones (appraisal of novelty; Ellsworth, 2013). Such appraisals dampen potential intense emotional arousal that could otherwise focus her father’s attention on possible discrepancies in her words or actions (Ellsworth, 2013). As these common occurrences are unlikely to stand out in his memory, this specific case can easily be forgotten (Schmidt, 1991).
After her lie, Ann specifies her solution to the problem (“I’ll be home in 20 minutes”). As her solution does not require additional effort from her father, he is more likely to accept it and let her proceed, rather than consider alternatives (appraisal of anticipated effort; Smith & Ellsworth, 1985). His minimal required effort also dampens potentially strong negative emotions.
Eliciting Strong Emotions With Fake News
Unlike a personal lie, fake news aims to ignite strong emotional arousal in the audience, such as anxiety, fear, and especially anger, to spur them to act (e.g., share content via texts, attend demonstrations, and so on; Berger, 2011; Berger & Milkman, 2012; Frijda, 2007; Nabi, 2003; Stieglitz & Dang-Xuan, 2013). To attract attention and evoke strong emotions (e.g., contempt for the president’s order) and, hence, potential action from the audience, the author fabricated fake news about a ban on a common, widely supported practice: the pledge of allegiance.
The ban on the pledge of allegiance is a strikingly unusual and thus memorable moment (appraisal of novelty) that can alter many people’s subsequent behaviors at common events (e.g., football games). A person who evaluates such a change as motivationally relevant (i.e., important) and inconsistent with his or her values (i.e., threatening or undesirable; primary appraisals) and who holds a specific target(s) accountable for it (in this case, Obama, appraisal of accountability) will often experience anger or contempt (Lazarus, 1991; Roseman, 1996). While these intense, negative emotions increase attention to the news story and risk greater scrutiny and possible detection of fatal flaws, they also increase the likelihood of audience actions that the fake news author seeks, such as sharing the article (Berger & Milkman, 2012) or voting against Obama’s Democratic Party. Furthermore, after a person accepts false information as true, reversing its validity to false is difficult, especially when he or she feels angry about it (MacKuen et al., 2010).
Information
Personal lies offer only a bit of mundane, vague information to hinder detection (cognitive information processing; Lachman et al., 2015). In contrast, fake news provides extensive, vivid details to engage the audience and spur action.
Short, Mundane, Vague, Personal Lies
As Ann’s lie is short (22 words), it provides little information to examine and is easier to remember. A short lie is less likely than a long lie to have internal inconsistencies or inconsistencies with reality. Furthermore, a short lie requires less memory retrieval and, hence, is easier than a long lie to remember and repeat, if needed in the future.
Ann’s lie is also mundane. It mentions a common place (“at the mall”) and a common event (“lost track of time”) that the father can easily forget among a herd of similar indistinguishable memories, thereby hindering her father’s recollection of this specific event for future scrutiny (Lachman et al., 2015).
Ann’s lie is vague with no details. She does not mention any specific stores or activities. The lie’s vagueness reduces the strain on her memory, facilitates her future recall, and allows her to add new details as needed without fear of contradiction in the future. Furthermore, the vague lie hinders her father’s analysis of the situation and his memory of it, as it dissolves into many other similar memories (Lachman et al., 2015).
Long, Vivid, Detailed, Fake News
In contrast, the fake news article is long, with vivid details that increase both detection of the deception and the credibility of the story (Morgan et al., 2011). When given more information or evidence about a story, a person is more likely to believe that the story is correct (Fan et al., 2013). (As a quick comparison, this example fake news article is much longer than the example personal lie; 937 words compared with 22 words).
Indeed, the article includes a vivid photo of Obama signing a document, and photos stimulate formation of memories in readers much more than simple texts do (Pfau et al., 2006). In addition to the photo, the fake news includes many details, including supposed quotes from Obama, the two leading presidential candidates (Hillary Clinton and Donald Trump), and two fictitious people, “Paul Horner” (supposed constitutional scholar) and “Lawrence Ketchum” from Secular Coalition for America (an actual organization). These details increase the credibility of the fake news article (Colwell et al., 2007). While fake news’ greater length, vividness, and detail raise the detectability of its deception, few people (aside from academics or journalists) pay the information costs to do so; hence, they are often worth the payoff in greater credibility.
Number of Participants
Whereas personal lies minimize the number of participants, fake news includes many of them. By omitting other participants from her lie (Morgan et al., 2011), Ann reduces the likelihood that she or others inadvertently provide information to her father that contradicts her lie. For example, if Ann had said that her friend Valeria was with her at the mall, her father might talk with Valeria and discover a discrepancy, or someone else might tell him that Valeria was at a friend’s house at the time. Thus, personal lies often omit other participants.
In contrast, fake news mentions many participants to enhance both credibility and audience participation. For example, the above-mentioned fake news article includes 11 people in the photo and quotes the views of four other people (two fake people). When an activity is described as having more participants, more people can verify the speaker’s claim, so he or she is more credible to an audience (Latané, 2000). Furthermore, the audience is more likely to follow the behavior of a larger group of people than a smaller group (bandwagon effect; Morton et al., 2015). Hence, fake news articles aiming to ignite audience action (e.g., attend protests) often report that many people are participating (Franceschi-Bicchierai, 2017).
Cite Witnesses/Sources
Like participants, witnesses/sources also aid deception detection and credibility. For personal lies, mentioning witnesses rather than participants creates the same vulnerability of potentially contradictory versions of the same event (e.g., if Ana’s father talks to a witness or learns that a supposed witness was not at the mall; Morgan et al., 2011).
For fake news, more sources increase credibility but not action (unlike additional participants). When a story has more sources, especially authoritative sources, an audience is more likely to find it credible (cognitive authority, Rieh, 2010; status characteristics theory, Chiu & Khoo, 2003). Hence, the above-mentioned fake news story quotes President Obama, the two leading presidential candidates (Trump and Clinton), a supposed constitutional scholar, and a representative of an organization. Unlike participants, however, sources do not engage in the desired activity and have no bandwagon effect (Morton et al., 2015).
In short, personal lies and fake news differ along six dimensions: (a) speaker–audience relationship, (b) goal, (c) emotion, (d) information, (e) number of participants, and (f) citation of sources. When people are in intimate relationships, they might tell personal lies to encourage audience inaction via banal tales (possibly with emotional distractions) that include little information, few participants, and minimal sources, thereby discouraging further reflection. In contrast, strangers try to motivate audience action via fake news with stronger emotional appeals (preferably hatred), extensive information, many participants, and authoritative sources, thereby enhancing credibility and bandwagon effects. Next, we consider how to detect these deceptions.
Detecting Deception
As personal lies and fake news differ in their deception mechanisms, our methods for detecting them also differ. In addition to individuals detecting a single fake news article, systemic detection of fake news via corporate responsibility, web tools, and education is crucial.
Detecting Personal Lies
As a person in an intimate relationship aims to avoid punishment yet maintain perceived trust, he or she lies to hide information via anodyne tales that dampen emotional responses and offer little information, participants, or sources. Hence, the audience seeking to detect lies can capitalize on their close relationship to heighten emotions, raise the stakes, and ask for more information, participants, or sources (see Table 2).
Detecting Personal Lies.
In the above-mentioned personal lie example, the father might respond by saying, “Sweetie, I’m so glad that you called. I was concerned about you. Are you with friends who can bring you home?” The father uses a term of endearment (sweetie), appreciates her call (I’m so glad that you called), and expresses his concern for her welfare (I was concerned about you). All these actions highlight his love for her and emphasize the high stakes of their warm, intimate relationship (Horan & Dillow, 2009).
Then, his question continues his concern and asks for more information, specifically about potential additional participants who might serve as sources of information (Morgan et al., 2011). By doing so, the father highlights the cost of a lie and solicits more information to raise his likelihood of detecting it (Vrij, 2008). If she admits to the lie or he detects it, he can apply a suitable, fair, proportional punishment to maintain their relationship and discourage future lies (Vrij, 2008). As fake news operates very differently from personal lies, many strategies for detecting personal lies do not apply to fake news, so a person who can detect personal lies well might fail to recognize many fake news articles.
Detecting Fake News
Outsiders use fake news to spur audience action via strong emotional appeals, detailed information, many participants, and authoritative sources. Hence, detecting fake news entails evaluating the author or sender, tempering emotional impulses to activate critical thinking, thinking before acting, evaluating the information in the news article, viewing websites (if any) of people in the news story, and checking other news media sources (see Table 3).
Detecting Fake News.
Unlike personal lies, the author of a fake news article is typically not available for interrogation (Allcott & Gentzkow, 2017). Instead, a reader might search for the author’s website(s) or other webpages (e.g., reputable newspapers) to examine his or her credentials and past articles. Likewise, if the article was forwarded by someone else, that person’s website or webpages can also be examined. Still, effective fake news sites often post real news articles from traditional sources (e.g., Associated Press) much of the time to enhance their overall legitimacy and the credibility of rare fake news (Allcott & Gentzkow, 2017).
Fake news that activates readers’ anger also hinders their critical thinking, so dampening the initial emotional impulse facilitates fake news detection (Bakir & McStay, 2018). When reading a news article, information (stimuli) enters the brain, which initially interprets and activates an emotional response (Bear et al., 2006). According to the emotional response, the brain facilitates or hinders access to higher brain functions (Gazzaniga & Ivry, 2013). Rather than letting emotional impulses dominate, emotional awareness and regulation strategies can temper their emotional response (Bear et al., 2006). For example, the advice for young children to stop, think, and then act (red, yellow, and green traffic lights) also applies to adults (Chiu, 2018). In response to their heightened emotions, readers can learn to pause, recognize their emotions, and then try to control them, thereby enabling their critical thinking (Gazzaniga & Ivry, 2013) to consider the validity of the news article before taking any action.
Just as many fake news sites include many real news articles from traditional sources, a fake news article often includes many true statements, photos, and links, so scrutinizing them to detect a flaw is nontrivial (Shu et al., 2017). In the Obama Bans Pledge of Allegiance fake news article, for example, all its links accessed real websites. However, the Executive Order 13738 link only goes to the United States archive of executive orders, not to Executive Order 13738. Executive Order 13738 itself is a real order but does not ban the pledge of allegiance.
Also, the photo of Obama signing an order is a real photo, but he was signing a different executive order. Doing a Google image search for “Obama signs executive order” yielded exactly the same photo showing him signing the Stop Trading on Congressional Knowledge [STOCK] act over 3 years earlier on April 4, 2012 (Associated Press, 2012). Although the misleading link and copied photo are accessible evidence of fraud, the credibility that the government link and photo bestow far outweigh the small likelihood of a typical person successfully detecting it along with the small consequence of such a detection.
Rather than checking each statement, link, or photo, checking the official websites of the participants is not only faster but likely more reliable—indeed, news media sites might automatically include such relevant links to all its news in a standard location. A quick internet search identifies Obama’s personal website (www.barackobama.com) or the official White House website (www.whitehouse.gov). The absence of such an important executive order on both websites raises questions about its legitimacy.
Likewise, similar legitimate news stories should appear in reputable sources across different media (e.g., New York Times, National Public Radio, Associated Press; Manning, 2000). The presence of the news story in these different media sharply enhances its validity, whereas the absence of such a newsworthy story raises doubts about its validity.
After detecting fake news, a person can inform the sender/sharer of this information and reduce its further dissemination. However, few people have the computer skills, resources, or time to track down the original author, let alone punish the author, who might live in a different legal jurisdiction (Vosoughi et al., 2018).
Corporate Responsibility for Detecting Fake News
Large, social media companies (e.g., Facebook [Instagram, Whatsapp], Google [YouTube], Twitter) know their software and personnel best, have large troves of relevant data, and have large financial resources, so they are best positioned to detect fake news via human or technological means. As shown above, detecting fake news requires substantial social media expertise, which resides in these social media companies’ employees. Also, social media companies have the relevant, huge databases to inform and test fake news detection procedures/algorithms. Last, they have earned massive profits from social media and have a societal and corporate responsibility to use some of those profits to improve their services. Corporate advertisers and government institutions can punish these companies that allow fake news to spread by withdrawing their advertising or imposing proportional fines.
Designing Webpages to Aid Detection of Fake News
Web designers can include tools to facilitate detection of fake news, such as fact-check search tools, fact-checking sites, interlinked reputable newspapers, and encrypted signature links. A fact-check search tool might enable users to highlight text on the webpage and right-click on a mouse to send it to the search engine of a fact-checking site (e.g., www.factcheck.org/search). Users might fact-check the news article headline, a key event, a specific quote, or a particular person. A similar tool might send highlighted text to reputable newspapers (e.g., www.nytimes.com/search, www.washingtonpost.com/newssearch)—and even better, newspapers might link their opinions/editorials to those of their rivals to encourage reader understanding of different political/ideological views. Encrypted signature links open the author’s webpage and their other news articles. Future studies can test the efficacy of such tools.
Teaching Detection of Deception
Most traditional primary or secondary school curricula do not include personal lies or fake news detection, though educators are advocating inclusion of the latter in computer curricula. The natural home of personal lies is social psychology, which is rarely taught before university (Karandashev, 2011). Furthermore, teaching personal lies in primary or secondary school might face morality concerns that teaching students about lies might encourage them to lie more often (Tate et al., 2013).
Meanwhile, computer science/literacy courses are increasingly introduced in primary and secondary schools around the world (though less often in the United States; Grover & Pea, 2013). Furthermore, the explosion of available information (e.g., on the internet) and Russia’s election tampering efforts highlight the potential damage of fake news (Allcott & Gentzkow, 2017). Hence, appropriate computer curricula to address them are under development (Journell, 2017).
In this vein, this comparison of personal lies and fake news can inform curricula that teach both. As personal lies and fake news differ along several dimensions, they are contrasting cases that clarify their meanings, which is often an effective instruction strategy (Roelle & Berthold, 2015). Hence, future studies can test whether contrasting personal lies and fake news can help students both understand them and improve their capacity to detect them.
Conclusion
Personal lies and fake news differ in six ways (speaker–audience relationship, goal, emotional arousal, information, number of participants, and citation of sources), so methods for detecting them differ. People in close relationships tell personal lies to encourage audience inaction by minimizing emotional arousal, information, participants, and sources. In contrast, unknown authors’ fake news try to spur audience action via emotional appeals, extensive information, many participants, and authoritative sources. A person seeking to detect personal lies can use their close relationship to heighten emotions, raise the stakes, and ask for more information, participants, or sources. In contrast, a person testing whether a news story is fake news can check websites of the author, sender, participants, and reputable sources across media. As large social media companies have suitable expertise, data, and resources, they are best positioned to reduce fake news. Otherwise search tools, linked opposing websites, encrypted signatures, and improved school curricula might help users avoid being victimized by fake news.
Footnotes
Appendix
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.