Hypothesis and Theory ARTICLE
The Politics of Embarrassment: Considerations on How Norm-Transgressions of Political Representatives Shape Nation-Wide Communication of Emotions on Social Media
- 1Social Neuroscience Lab, Department of Psychiatry and Psychotherapy, Universität zu Lübeck, Lübeck, Germany
- 2Department of Advertising and Public Relations, Michigan State University, East Lansing, MI, United States
- 3Department of Communication, Michigan State University, East Lansing, MI, United States
- 4Department of Philosophy, Goethe-Universität Frankfurt am Main, Frankfurt, Germany
In this article, we hypothesize, and then demonstrate, that experiences of embarrassment have significantly increased in the United States, due in part, to the current situation in American politics under President Donald Trump. We provide support for our hypothesis by conducting both qualitative and quantitative analyses of Twitter posts in the U.S. obtained from the Crimson Hexagon database. Next, based on literature from social psychology, social neuroscience, and political theory, we propose a two-step process explaining why Trump's behavior has caused people in the U.S. to feel more embarrassment. First, compared to former representatives, Trump violates social norms in a manner that seems intentional, and second, these intentional norm violations specifically threaten the social integrity of in-group members—in this case, U.S. citizens. We discuss how these norm violations relate to the behavior of currently represented citizens and contextualize our rationale in recent changes of political representation and the public sphere. We conclude by proposing that more frequent, nation-wide experiences of embarrassment on behalf of the representative may motivate political actions to prevent further harm to individuals' self-concepts and protect social integrity.
Emotions are powerful motivational forces for human behavior. Feelings of guilt lead to reparative actions (Keltner and Buswell, 1997), pride makes people strive for achievements (Tracy and Robins, 2004), fear due to a potential threat causes us to flee or fight (Ekman, 1992), and outrage may serve as a catalyst for collective action (Spring et al., 2018). These examples demonstrating the relationship between emotion and action refer to firsthand experiences, but something else seems to be at stake when we experience emotions vicariously, on behalf of others. What drives our feelings of embarrassment for other people's wrongdoings or gaffes? Since Donald Trump's election as the President of the United States of America (U.S.), these questions have gained new significance. Here, we take a closer look at the current expression of second-hand affect across the U.S. with a specific focus on vicarious embarrassment.
First-person embarrassment is defined as a transient emotional reaction when one's own public or social image is endangered due to a violation of social etiquette. Examples of situations that elicit these image concerns include physical pratfalls, cognitive shortcomings, loss of control over the body, shortcomings in physical appearance, or failure at privacy regulation. For all of these cases, the public nature of the event is an integral part of the embarrassment experience, as it requires looking at oneself through the eyes of real or imagined others (Miller and Tangney, 1994; Miller, 1996; Keltner and Buswell, 1997). Several recent studies further examined the emotion of embarrassment, but through the eyes of bystanders (Miller, 1987; Hawk et al., 2011; Krach et al., 2011; Paulus et al., 2018). These studies delineate how watching the behavioral flaws of others can trigger vicarious emotional states in observers, illustrating that the image-concerns of the clumsy or inept protagonist at the center of attention are justified. It follows then that second-hand or vicarious embarrassment is elevated in more empathic people; the more empathic the person, the more embarrassment they feel for others. This increased embarrassment correlates with increased activation in brain regions involved when observing others in physically painful situations (Krach et al., 2011, 2015) and it has been argued that vicarious embarrassment may arise because people imagine themselves in the ridiculed person's shoes and simulate the potential threat this would mean for their own social integrity (Paulus et al., 2015). Therefore, vicarious embarrassment signals that another's social integrity is in danger and that help or social support might be deemed necessary (e.g., if one sees another's zipper on their pants is open, one can take action to notify the unaware person). Notably, the same idea accounts for sharing others' bodily pain, where an immediate affective representation of the harm to another's bodily integrity enables people to take action and help (Zaki et al., 2016). To note however, previous research has shown that to experience vicarious embarrassment, it is not necessary to perceive an affective reaction like embarrassment in the other person (e.g., blushing or lowering of the head and/or gaze) (Paulus et al., 2013, 2015). More specifically, when observers don't perceive an affective reaction in others who violate social norms, it can be interpreted in two ways—the observed individuals are either unaware of their mishap, or they are aware but they intended to behave in this manner. In other words, regarding the latter case, the observed person is aware of the potential threat to their social integrity but proceeded to violate social norms on purpose (Krach et al., 2011). This intentionality is important to keep in mind when considering the communication of vicarious embarrassment and other emotions across the U.S. in the current political climate.
Recent polls (Danner, 2017; Gross, 2017) and a variety of colorful statements on social media platforms show that Donald Trump's public performance has been repeatedly judged as shameful or embarrassing. We suggest that this vicarious embarrassment is wide-spread, across the U.S., and specifically induced in response to intentional norm violations by Trump, without any attribution of first-hand embarrassment. With this in mind, we set out to achieve three goals with this article: (1) we aim to provide further evidence linking Donald Trump to nationwide communication of embarrassment through both qualitative and quantitative analyses of Twitter posts, (2) we discuss a two-step rationale on why U.S. citizens have experienced this increased embarrassment on behalf of Trump, and (3) we hypothesize that these frequent expressions of embarrassment may motivate political actions in an attempt to both prevent further harm to individuals' self-concept and to protect their social integrity.
We analyzed Twitter posts across the U.S. to capture trends of embarrassment- and affect-related expressions from June 2015 to the end of 2017. A keyword-based approach, which has been widely used in empirical studies of public attention and emotion (Russell Neuman et al., 2014; Peng et al., 2017), was adopted in the current study to identify embarrassment-related tweets. Specifically, we took two different approaches to find evidence linking the nationwide communication of embarrassment or other affective expressions to Donald Trump. Our first approach is descriptive and qualitative, and restricted to the time between the June 1, 2015 and August 15, 2017. Here, we searched embarrassment-related keywords (i.e., “embarrassment” | “embarrassing” | “embarrassed”) in the Crimson Hexagon database (CH), a social media analytics company which gathers, stores, and analyzes Twitter posts with a supervised text analysis model (Hopkins and King, 2010). Geo-location was limited to the U.S. and the language was specified as English in the search. We obtained two statistics from CH: (1) the daily number of embarrassment-related tweets which included at least one of the three embarrassment-related keywords, and (2) the total number of tweets posted by U.S. accounts per day. The number of tweets communicating embarrassment on each day were then normalized by the total number of tweets sent from U.S. accounts on each day to quantify the relative amount of embarrassment communications on Twitter in parts per million (ppm). We summarized the relative expression of embarrassment on Twitter with the mean and median across three time periods: (1) the remaining presidency of Barack Obama until the presidential election (June 1, 2015–November 7, 2016), (2) the transition period after the election until the day before the inauguration of Donald Trump (November 8, 2016 to January 19, 2017), and (3) a period of time during the presidency of Donald Trump (January 20, 2017 to August 13, 2017).
In this analysis, we also examined the timeseries of relative embarrassment communication on Twitter for peaks in the signal. We did this to explore the potential association of an “embarrassment signal” concerning Donald Trump in greater detail. Therefore, we selected three peak dates for their strongest relative embarrassment utterances and extracted the full text of around 40,000 tweets containing the embarrassment keywords for further qualitative analysis on each date: October 10, 2016 (44,389 tweets), March 18, 2017 (39,072 tweets), and May 26, 2017 (49,653 tweets). For each day, we cleaned Tweets from retweets to achieve a more balanced weighting of semantic context of embarrassment expressions. Further, we removed a set of frequent English words and expressions that were considered to not carry semantic meaning in the approach of our analysis (i.e., “I,” “and,” “the,” “have,” “over,” “take” etc.) and the search term related to embarrassment. Finally, we counted the frequencies of the remaining words for each day and represented these counts as word-clouds, with the font size of each word linearly scaled with the frequency of the expression in the set of Tweets on each day. To do this, we used the WordArt.com software framework (https://wordart.com). This graphical depiction and input frequencies were qualitatively examined for potential associations with Donald Trump's presidency and events that he was involved on that day or prior to that day. We also assumed that the initial observation for the top three peaks may also generalize, to a non-negligible degree, to other noticeable events in the signal. Therefore, in a final step of this qualitative analysis, we show which policy changes or actions by Donald Trump coincide with the 10 strongest peaks in embarrassment utterances during this time period (see Figure 1C).
Figure 1. Expression of embarrassment on Twitter in the U.S. (A) Mentions of embarrassment on Twitter between June 1, 2015 and August 13, 2017. The relative number of tweets related to embarrassment increased by ~45% since the start of Trump's presidency (in red) compared to the last year of Obama's presidency before Trump was elected (in blue). The purple region of the timeline indicates the period after Trump was elected for office, but before his inauguration. m indicates the arithmetic mean and md indicates the respective median of tweets containing the words “embarrassment” or “embarrassing” or “embarrassed” during Trump's and Obama's presidency, including retweets. The y-axis refers to parts per million (ppm) of all tweets sent from U.S. Twitter accounts. (B) Word clouds demonstrating the association between embarrassment and Trump for three selected dates. Word clouds were computed from tweets (excluding retweets) for days when there was a high volume of tweets about embarrassment [see boxes on peaks in (A) October 10, 2016 (44,389 tweets); March 18, 2017 (39,072 tweets); and May 26, 2017 (49,653 tweets)]. Word clouds show strongest associations with Donald Trump and related political events (e.g., “debate,” “Merkel,” “NATO”) but also references to the U.S. (e.g., “country,” “America”) or his representational claim (e.g., “president,” “leader”). Word size is scaled by the word count in these tweets after removing common English words (e.g. “the,” “over,” “take,” “after,” and “you”) and the search terms “embarrassment,” “embarrassing,” and “embarrassed” using the WordArt.com (https://wordart.com) software framework. @realDT* refers to @realDonaldTrump and was shortened for display purposes. (C) Peaks in embarrassment expressed on U.S. Twitter labeled with events and actions taken by Trump within the preceding days. The blue section of the timeline refers to Obama's presidency, the red section refers to Trump's presidency, and the purple section depicts the period after Trump was nominated for office, but before his inauguration. MOAB refers “Mother of all bombs”.
In our second analytic approach, we used quantitative methods to relate Trump to affective expressions communicated on social media. For this analysis, we examined Tweets posted from June 1, 2015 to December 31, 2017, and geo-location was again limited to the U.S. We selected a broader set of keywords than above, all representing different affective expressions that could be potentially linked to political actions of representative leaders in the CH database. Keywords were affective expressions of either positive or negative valence, with some representing what have been called moral emotions (i.e., embarrassment, shame, pride, and guilt, see Tracy et al., 2007), and some affective expressions that may be considered not in this moral emotion domain (i.e., happiness, sadness, anger, and disgust, for a discussion of the moral implications of disgust however see e.g., Chapman et al., 2009; Giner-Sorolla and Chapman, 2017; Tracy et al., 2019). For each emotional expression we searched the CH database for relevant forms, such as conjugations, that could appear in written communication, similar to our search for embarrassment expressions for each day as explained above (i.e., shame: “shame” | “ashamed” | “shameful”; guilt: “guilt” | “guilty”; pride: “pride” | “proud”; embarrassment: “embarrassment” | “embarrassed” | “embarrassing” | “embarrasses”; anger: “anger” | “angry” | “angers”; happiness: “happy” | “happiness”; sadness: “sad” | “saddening” | “saddens”; disgust: “disgust” | “disgusting” | “disgusted” | “disgusts”). By doing these CH database searches, we obtained the total amount of affective expressions for each affective word-group and day during the selected time interval. In addition, we computed the probability of “Trump” being co-mentioned with the expressions on the same day. This was done by counting the frequency of tweets that included both “Trump” and the affective expression and dividing it by the total number of tweets containing the respective affective expression on each day. To estimate the dependency between the two timeseries, i.e., the total volume of a specific affective expression on each day and the probability of “Trump” being co-mentioned with this expression, we first controlled for autoregression (AR2) within each timeseries. Each raw data timeseries starting from June 3, 2015 was regressed on the data from 1 to 2 days before and unstandardized residuals were saved using a linear regression model with SPSS 25 (IBM Corp. Released 2017. IBM SPSS Statistics for Windows, Version 25.0. Armonk, NY: IBM Corp). These residual timeseries were tested for dependencies using Spearman's rho in “R” (R Core Team, 2018) as a non-parametric estimate that is not affected by outliers in the data and has little assumptions on the nature of the association such as linearity using the RVAideMemoire package (Hervé, 2018). The computed measure thus provides an estimate for how much the day-to-day variation in the rank of affective communication on U.S. Twitter was associated with the rank of the probability that “Trump” was included in the communication of this affective expression in the respective time-period. We also computed 95% confidence intervals of Spearman's rho by bootstrapping with 10,000 repetitions for each affective expression. For visualization purposes we plotted the raw data together with the corresponding Spearman's rho and confidence intervals for each affective expression separately.
Before presenting our results, we'd like to bring up several points regarding our methodology and subsequent potential limitations of our analyses. First, while qualitative and quantitative approaches are legitimate in their own right, we believe that combining these approaches is a more effective methodology to allow inferences on whether people in the U.S. (increasingly) communicate embarrassment on behalf of Donald Trump's actions and policies. To note however, our quantitative analyses are correlational in nature, and therefore, do not necessarily imply causation. It is not unreasonable to assume that an association between embarrassment and Trump could result from a single narrative that is repeatedly used in Twitter communication, for example, to exemplify embarrassing incidents which have very different causes or a collectively shared memory that reappears from time to time. Our qualitative analyses, however, contextualize the association of Trump and embarrassment in Twitter posts and, with limited breadth, demonstrate that increased embarrassment utterances refer to different actions and policies of Trump that occurred at that specific time. While these analyses allow for inferences linking Trump's actions and policies to the resulting communication of embarrassment across the U.S., they do not provide any insights into the causal mechanisms that underlie this association.
Second, the validity of our results depends on the reliability of Twitter data. While there are specific peculiarities with Twitter data that might not be present in other sources when people share their state of mind (McCormick et al., 2017), the validity of various types of communication on social media, such as Twitter, has been more fundamentally put into question recently—specifically in regard to bots and the spreading of fake news during political campaigns (Read, 2018; Grinberg et al., 2019). Therefore, as the validity of each Twitter post we analyzed is impossible to verify, it could be that some of the data presented below do not represent authentic acts of communication by individuals expressing their emotional state. Nevertheless, we present the Twitter data as collected, and we consider the presence of non-authentic content in our analyses as unsystematic error, that does not bias the general finding. Furthermore, to support the validity of our data, it is unlikely that the systematic action of bots on Twitter were specific to the domain of embarrassment communication with regard to Trump. It's more likely that there was an artificial skewing of communication away from embarrassment and toward more positive emotions (e.g., pride or happiness) that would support his candidacy and subsequent presidency (Gorodnichenko et al., 2018).
Third, our analyses of U.S. Twitter data only consider the written communicative act of affective expressions. This a legitimate approach as most research on affective experiences rests on some sort verbal report such as questionnaires, dairies or other artifacts of communication to infer subjective experiences of an individual (Barrett et al., 2007). In support of this, subjective reports of affective experiences such as pain, fear or more complex emotional states, such as vicarious embarrassment, map well onto psychophysiological and neural signatures that reflect core dimensions of affective processes such as arousal (see e.g., Wager et al., 2013; Geuter et al., 2014; Paulus et al., 2015). However, due to the nature of our source (i.e., Twitter posts), we have limited coverage on the affective constructs at hand. We cannot differentiate core affective dimensions, such as arousal and valence or even the intensity of the experienced affect that manifests in other channels of interpersonal communication such as bodily and facial expressions, voice, or gestures. More in-depth analyses with regards to affective experiences besides frequency counts of affective utterances in written Twitter posts or specific use of expressions in context with Trump would assist in supporting our hypothesis, but would be impossible to collect now when looking back at previous events. Therefore, we present historical Twitter data to support our hypothesis.
Overall, we observed an increase in relative embarrassment utterances on U.S. Twitter accounts that coincides with the presidency of Donald Trump. In the final year of Obama's presidency until the presidential election, we observed an average of 909.5 ppm Tweets per day referring to embarrassment, with a median of 871.2 ppm. In the first half year since Donald Trump took office, these numbers substantially increased, averaging 1319.2 ppm Tweets per day (median 1194.2 ppm). This is an increase of 45% ppm (see Figure 1A)1.
For the top three peaks in the embarrassment timeseries (excluding the day of the election) we found support for the notion that the increased expression of embarrassment was related to Trump or events during his presidency. While during Obama's presidency, the embarrassment signal peak on October 10, 2016 was associated with Trump and the presidential debate, with the most frequent, co-occurring words being “debate,” “Trump,” and “@realDonaldTrump,” while also finding strong references to “America,” “American,” or “country,” and relatively less frequent mentioning of “@HillaryClinton” or “Hillary.” The embarrassment signal peak on March 18, 2017 also had high frequent co-mentioning of “Trump,” “@realDonaldTrump,” “@Potus” but also “country,” “American,” “America,” as well as “Merkel,” suggesting a link to the visit of the German Chancellor. The other set of highly frequent words that were mentioned alongside embarrassment such as “Celebrities” or “Moments” might point to a different topic that contributed to the peak in embarrassment communication on that day. Regarding the embarrassment signal peak on May 26, 2017, “Trump,” “@realDonaldTrump,” and “@Potus” as well as “American,” “America,” “country” together with “NATO” and “world” had the strongest co-occurrence with embarrassment. This suggests a link to the NATO summit (see Figure 1B). Motivated by these findings for the top three events in the signal, we proposed actions of Donald Trump and events during his presidency that coincide with the top 10 peaks in embarrassment communications on U.S. Twitter between June 1, 2015 and August 13, 2017 (see Figure 1C for an annotation of the daily ppm of Tweets containing embarrass*).
Our qualitative analysis had limited breadth and provided insights only into the context of specific events in the communication of embarrassment. In fact, it could be the case that the dynamics in the communication of affect on U.S. Twitter might be rather random with changes in the signal being associated with different, idiosyncratic events, and unsystematic factors. With this in mind, we extended our initial, qualitative analysis, and examined whether Trump was an associated factor in affective expressions on U.S. Twitter. We did this by simply relating the daily volume of affective expressions with the probability that “Trump” was mentioned in the same Tweet.
Overall, we found clear indications that day-by-day variations in the U.S. American communication of affect on social media was systematically related to Trump. In the time period from June 3, 2015 to December 31, 2017, we found the daily volume of embarrassment-related Tweets to be positively correlated with the probability that Trump was co-mentioned in the Tweet, with a moderate effect size (Spearman's rho = 0.25, 95% CI: 0.18; 0.32). During peak days “embarrassment” Tweets explicitly including “Trump” comprised between 20 and 35% of all embarrassment-related messages that were sent from U.S. Twitter accounts (see Figure 2 for a depiction of the daily averages together with the measures of association after controlling for autoregression in the timeseries). To rule out that this association might have been affected by Tweets included prior to the election, we have repeated the same analyses for the post-election period and observed a comparable pattern of association between affective expressions and Trump. If changes appeared, they are in the direction that the association with embarrassment only increased post-election (see Table S1 for details). Similarly, the change in the Twitter policy to increase the number of characters to 280 per Tweet on November 7, 2017, was not responsible for this pattern as we observed the same associations in the post-election period when restricting the analyses to Tweets with 140 character limit only (data not shown).
Figure 2. Association of “Trump” with the daily communication of emotional expression on Twitter in the U.S between June 3, 2015 and December 31, 2017. Each plot depicts the daily volume of Tweets containing the emotional expression (e.g., for disgust all Tweets containing either “disgust,” “disgusting,” “disgusted,” or “disgusts”) on the x-axis and the probability that “Trump” was co-mentioned in the Tweets with the emotional expression of that day on the y-axis. Correlation coefficients depict Spearman's rho after controlling for linear autoregressive effects (AR2) in each of the two timeseries together with their 95% confidence intervals (in brackets below) and p-values (two-sided). Strongest associations can be found with emotional expressions with negative valence such as embarrassment but also disgust, shame, and anger.
A somewhat lower, but positive association with the probability of explicitly co-mentioning “Trump” was present for the daily volume of Tweets communicating “Shame” (rho = 0.16, 95% CI: 0.09; 0.23), “Disgust” (rho = 0.18; 95%CI: 0.11; 0.24), and “Anger” (rho = 0.17; 95%CI: 0.10; 0.24). In contrast, variability in the daily volume of Tweets communicating “Guilt” (rho = 0.05, 95%CI: −0.02; 0.13), “Sadness” (rho = 0.05; 95%CI: −0.02; 0.11), and “Pride” (rho = 0.01; 95%CI: −0.05; 0.08) were unrelated to the probability of “Trump” being included in those Tweets. For “Happiness” a negative association was found (rho = −0.12; 95%CI: −0.19; −06) indicating that on days when the volume of Tweets containing “happy” or “happiness” increased, the probability that these tweets also contained “Trump” was lower. Overall, the non-overlapping CIs imply that the dynamics in communication of affect across U.S. Twitter accounts are more strongly related to Trump for emotional concepts with negative valence such as embarrassment, disgust, shame, and anger, compared to those with positive valence such as pride or happiness. Thus, the probability of the presence of “Trump” in affective communication on social media does not generally impact the nationwide sharing of affect but seems to follow a specific pattern of embarrassment and related affect with negative valence being at its core.
Our Twitter analyses substantiate a link between the communication of embarrassment across the U.S. and the presidency of Donald Trump. The qualitative examination of specific events as well as the quantitative analysis of the whole timeseries data together support the notion that people have had the urge to communicate embarrassment related to Trump and that this sharing of embarrassment with regard to Trump constitutes a significant proportion of the “overall embarrassment signal” on social media in the U.S. If the daily volume of embarrassment communication increased, it was more likely that there was an association with Trump in the signal. It must be noted that this association—even though prominent—was not limited to the experience of embarrassment; nationwide dynamics in communicating other affective experiences with more negative valence such as shame, disgust, and anger also revealed an above-chance association with the probability of co-mentioning Trump, while others, such as pride and happiness, did not.
With the above results, we demonstrated that utterances of embarrassment have significantly increased in the U.S. and that this increase is related to the advent of Trump's presidency. In the following we aim to explain the causal mechanisms of this effect, and how and why the action of political representatives presses individuals to communicate embarrassment on their behalf. In doing so, we consider two aspects (1) the attributed intentionality of the observed norm transgression, and (2) the potential identity threat by association.
The Intentionality of Norm Transgression
While recent findings suggest that purely accidental etiquette violations do not inform about the character of the protagonist (Stocks et al., 2011), norm violations do contain information that allow these inferences if the protagonist acts intentionally. The differentiation between accidental and intentional norm violations has been described before (Berthoz et al., 2002), but without much focus on the emotional states elicited in observers. This, however might be especially relevant when aiming to understand affective reactions to the current U.S. president's behavior.
Earlier U.S. presidents' mishaps and etiquette violations were mostly construed as unintentional, whereas Donald Trump appears to deliberately transgress social norms, as if he did not care that they exist. A good contrast to the current political climate involves an incident with a former President of the United States, George W. Bush. In the year 2000, while talking to Vice-President Dick Cheney, President Bush spotted New York Times reporter Adam Clymer. Not realizing that the microphones in front of him were on, Bush commented to Cheney: “There's Adam Clymer, major league a–h-le from the New York Times.” Clearly, our eavesdropping was unintended and President Bush would not have made the comment if he had been aware of the active microphones. Indeed, he soon stated, “I regret that it made it to the airwaves.” (Berman and Hill, 2000). As such, this was a prototypical gaffe—it lacked intention and the protagonist expressed post-gaffe regret over his wrongdoing to signal guilt and offering reconciliation (Tangney et al., 1998). Nowadays, President Trump often finds himself in similar situations where he violates social norms and etiquettes, but crucially, these transgressions appear intentional to the observers and he does not express signs of regret. For example, while on the campaign trail in November of 2015, Trump openly mocked the physical disability of a New York Times reporter (for video of this, please see footnote2) When Trump was asked later about this mocking, he claimed that he didn't know the reporter personally and was mocking only his journalism, not his disability (Trump and the reporter had met in person many times and were on a first-name basis for years; Haberman, 2015). Compared to George W. Bush, Donald Trump seems fine with willfully disrespecting prevailing and shared social norms (e.g., not mocking others' physical disabilities) and, accordingly, does not make appeasement gestures afterwards. Expressions of appeasement are usually provided to help restore one's social image (Keltner and Buswell, 1997) and reduce antipathy in observers (Semin and Manstead, 1981), and therefore, Trump's lack of regret signaling regarding his social norm transgressions further supports the attribution of intentionality to his behavior and his personality. It is the intentionality of the norm transgression that differentiates the affective experiences of earlier political climes from the situation people now face with Donald Trump. Willful norm or etiquette violations have become to a daily business. Given that background, the question arises how this might affect people he claims to represent. We will discuss this issue by referring to literature on intergroup psychology and theories of political representation.
Identity Threat by Association
The literature on social identity theory and intergroup behavior describes that embarrassment on behalf of others emerges both when observing the misbehavior of unrelated individuals, and also to an even greater extent, when observing the mishaps of in-group members (Shearn et al., 1999; Lickel et al., 2005). These so-called group-based emotions depend on the social relationship between the observer and the actor—this association renders others' wrongdoings relevant for oneself (Fortune and Newby-Clark, 2008; Müller-Pinzler et al., 2016). Social relationships are established not only through direct social interactions, but also through shared membership in a relevant social category such as religion, gender, family, or nationality (Iyer et al., 2007; Lickel et al., 2007). If in-group members who identify in the same social category now behave or express opinions that run counter to one's beliefs (e.g., racist attitudes or sexual harassment), the group's social integrity is threatened and one's own social image is endangered. Importantly, this group-based, vicarious shame or embarrassment emerges even when one wasn't involved in, or responsible for, the other group members' norm transgressions (Lickel et al., 2005; Chekroun and Nugier, 2011). In other words, one need only identify with one of the transgressors' social categories to feel vicarious embarrassment.
Coming back to Donald Trump, this theory posits that people who communicate embarrassment on his behalf share some sort of self-relevant social category with him, such as nationality or political party. Furthermore, President Trump is not just a U.S. American citizen like others who identify as U.S. American. As an elected leader, he has an outstanding role for the common identity of U.S. citizens: he is supposed to represent the U.S. While Donald Trump was running for the Republican nomination, U.S. Americans who opposed him, could construct their social identity without referring to him. U.S. citizens' own ethical standards and norms were not affected by Trump because he did not yet represent the whole of the U.S. Thus, his counterparts could easily express malignant joy for the gaffes and norm transgressions he committed during his campaign. Evidence supporting this rationale can be derived from press and media artifacts of this time, of which we highlight one particular example from the campaign trail in 2016: “And yet, as the campaign has worn on and Trump has emerged as the leader in the delegate count, another liberal reaction to his rise has emerged: schadenfreude. Trump's nomination could very well lead to the collapse of the Republican Party, which many liberals view as an increasingly debased institution that deserves not merely to lose elections but to be permanently vanquished.” (citation from an article in Slate by Chotiner, 2016). However, after being elected President of the United States, this situation changed. “People may say things during a campaign, but it's different when you become a public servant,” Senator Susan Collins, Republican of Maine told The New York Times (Glenn and Haberman, 2017). Currently, people who identify as U.S. American are linked to Trump, they are members of the same in-group and Trump is the elected leader of this group. As the first representative of the United States, he has a unique and outstanding status. He is not just one member of the U.S. American collective, but he is assigned to be the one to form this community. This is how political representation works in a presidential system; the social identity of a community is constructed through the personal identity of the president (Manow, 2008). Therefore, the representative needs to appear in front of an “audience” which approves him of being actually representing–thus representation involves publicity (Saward, 2006). Thus, the deliberate trespassing of values and normative standards by Trump poses a specific threat for the social integrity of the represented. This threat may cause the feelings of embarrassment on his behalf (“[…] embarrassing to our country,” Glenn and Haberman, 2017).
Norm Transgressions as Political Instrument
Many political theorists have pointed out that the transformation of the public space during the last decades has led to an increased reduction of politics into a mode of appearance (Habermas, 1962; Manin, 1997; Blühdorn, 2013). The diagnosis is that, instead of aiming at democratic participation or deliberation, politics today is primarily affect-oriented: Instead of applying specific procedures of representative government, the “new role” of the representing would lie in generating affective bonds with the people she/he claims to represent. Trump and his political strategies can be seen as a result of this development (Rubenstein et al., 2018). The deliberate trespassing of values and normative standards by Trump must be envisioned within this context, but in order to understand vicarious expressions of embarrassment for Trump it is necessary to view the situation from a positive, as well as from a negative, perspective. On the positive end it is an intentional symbolic strategy for signaling that he “belongs to ‘the people’ as opposed to the corrupt elite” as Rubenstein et al. (2018) argue. Trump thereby explicitly distances himself from the “aloof” political class who has settled in its own routine procedures and behavioral norms. Thus, he actively aligns with those people who might similarly view themselves as outsiders of the system. From this perspective, the according emotional expression would obviously not be embarrassment or shame, but rather positively valenced emotions such as pride. So, how can the negative affective response of embarrassment be understood? Therefore, it is important to consider also the negative end of Trump's affective politics: By refusing the social norms and standards of the “political elite,” Trump also expresses his rejection of the representative system as such. The appeal he emits for his supporters is based on the rejection of the political role the representative system ascribes to him. Thereby, for those who understand their social integrity as U.S. American citizens to be based on the formal structure of a representative system, Trump involves a specific threat. As we detail, the expression of feelings like vicarious embarrassment shows that, in particular for those people, Trump's claim to represent, is not acknowledged. One's embarrassment on behalf of their representative shows a strong rejection of the symbolic identification he needs to create. This affective expression is specifically relevant because in a political context the representing relation cannot simply be quit by stepping out of the group (Runciman, 2007). One could assume that the emotion of embarrassment expresses a failing but not discardable relation of representation, which is a serious threat for democracy (Dovi, 2007)–specifically because it is caused by voluntary and (in terms of support) successful actions. This is the double effect of the described context of affect-oriented politics: While on the one hand it has caused powerful feeling states, such as vicarious embarrassment, shame, or guilt (Glenn and Haberman, 2017), Trump's norm transgressive behavior also seems to be particularly appealing, because of the expressed repulsive emotions it causes. For those who, by expressing feelings of embarrassment show that they see a danger for the system of representation in this appeal, a need for further political actions may arise, as we will conclude below.
Conclusion and Implications for Motivating Political Action
Taken together, we think that the intentionality of social norm transgressions, the identity threat experienced by in-group members, and the instrumental value of norm transgression for the new clime of affective politics, may trigger the urge for communicating embarrassment more frequently. One may speculate that such vicarious emotions could elicit actions, such as political engagement and demonstrations aimed at preventing further harm to one's self-image and the social groups that one identifies with. For example, Doosje and colleagues revealed that even long after colonizing Indonesia, Dutch participants showed feelings of guilt by association and that such feelings of guilt apparently increased the willingness to compensate for their group's past behavior. Also, and in line with many other studies on in-group identification (e.g., Branscombe et al., 1999), the willingness to compensate was moderated by measures of Dutch national identification, with lower identifiers showing higher motivation to act (Doojse et al., 1998). Turning toward more recent events, the experience of shame for another's actions not only predicted a motivation to distance oneself from in-group members who openly displayed prejudice toward a minority (Johns et al., 2005), but also the intent for political action in response to illegitimate military actions of U.S. forces in Iraq (Iyer et al., 2007). These studies imply that the embarrassment on behalf of Donald Trump fosters the rejection of the representative's claim and increases the motivation for political action by U.S. citizens. As a simple consequence this might lead to increases or changes in voting behavior as journalists and others have already speculated: “But numbers like this – in which large majorities of people in key swing states call the President of the United States an “embarrassment” – should concern him. We don't tend to emulate – or, more importantly for Trump, vote for – embarrassments.”; (Cillizza, 2017). Ultimately, however, the impact of vicarious embarrassment could also strengthen the search for other forms of political action which may transgress and break the official institutional frame.
FP, LM-P, MM, DM, and SK developed the concept of the manuscript and wrote the paper. T-QP collected data and together with FP and SK conducted data analyses.
Conflict of Interest Statement
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fcomm.2019.00011/full#supplementary-material
1. ^Notably, this increase is merely correlational in nature and at this point does not provide the means for inferring an association of Trump's presidency and his actions to the communication of embarrassment on Twitter.
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Keywords: affective politics, embarrassment, Twitter, Trump, social norm violation, vicarious emotions
Citation: Paulus FM, Müller-Pinzler L, Meshi D, Peng T-Q, Martinez Mateo M and Krach S (2019) The Politics of Embarrassment: Considerations on How Norm-Transgressions of Political Representatives Shape Nation-Wide Communication of Emotions on Social Media. Front. Commun. 4:11. doi: 10.3389/fcomm.2019.00011
Received: 15 June 2018; Accepted: 05 March 2019;
Published: 27 March 2019.
Edited by:Joshua C. Shurley, Clovis Community College, United States
Reviewed by:Tim Markham, Birkbeck University of London, United Kingdom
Tilman Reitz, Friedrich-Schiller-Universität Jena, Germany
Copyright © 2019 Paulus, Müller-Pinzler, Meshi, Peng, Martinez Mateo and Krach. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.