Psychological distance in emotion attribution 1
RUNNING HEAD: Psychological distance in emotion attribution

Happier than thou?
A self-enhancement bias in emotion attribution

Desmond C. Ong, Noah D. Goodman, and Jamil Zaki
Department of Psychology, Stanford University
In Press at: Emotion
Manuscript dated: 31 January 2017
Address Correspondence to:
Desmond C. Ong
Department of Psychology
Stanford University
Stanford, CA 94305
dco@stanford.edu
Word count: 7828
Abstract word count: 190
Number of references: 51
5 Figures, 1 Table in text.
Author Contributions: D.C.O., N. D. G., and J. Z. designed the research and wrote thepaper. D.C.O. collected and analyzed the data.
The authors declare no conflict of interest.
© 2017, American Psychological Association. This paper is not the copy of recordand may not exactly replicate the final, authoritative version of the article. Please do
not copy or cite without authors permission. The final article will be available, upon
publication, via its DOI: 10.1037/emo0000309

Psychological distance in emotion attribution 2
ABSTRACT
People tend to judge themselves as exhibiting above average levels of desirable traits—
including competence, kindness, and life satisfaction—but does this self-enhancement
extend to emotional responses? Here, we explore this question by having people attributeemotions to themselves and others following simple gambles. We demonstrate thatpeople display an emotional self-enhancement bias that varies with the context of theemotion-eliciting situation. People judge themselves as experiencing more positive
emotional reactions on average, and they also believed that others’ emotions are moresensitive to gamble outcomes, such that people judge others to experience stronger
negative affect in response to negative outcomes (Study 1). This self-enhancement bias
further tracks social distance, such that people attribute less positive and more negative
emotion to more dissimilar, as compared to more similar others (Study 2). People also
predict less favorable emotional states for themselves and others experiencing events inthe future, as compared to the present (Study 3), suggesting that this attribution bias
extends across multiple dimensions of psychological distance. Broadly, these datasuggest that people exhibit self-enhancement in emotion attribution, but do so in subtle
ways that depend on situational and social factors.

Keywords: Emotion; Attribution; Inference; Self-enhancement; Psychological distancePsychological distance in emotion attribution 3
People tend to view themselves in an unrealistically positive light. For instance,
individuals judge themselves to be more competent, kind, attractive, and likely to succeed
than the average person (Blaine & Crocker, 1993; Dunning, Meyerowitz, & Holzberg,
1989; Mezulis, Abramson, Hyde, & Hankin, 2004; Taylor & Brown, 1988). Thistendency to self-enhance occurs when people make global evaluations of their personal
attributes or traits, relative to that of the average person (Brown, 1986; Chambers &Windschitl, 2004; Hughes & Zaki, 2015). Here, we examined whether such selfenhancement extends to people’s judgments of emotional states.
Emotional states are discrete, momentary responses that arise in response to
motivationally relevant events, such as arguing with a friend or winning an award (e.g.,
Barrett, Mesquita, Ochsner, & Gross, 2007; Ortony, Clore, & Collins, 1988). At least two
properties of emotions differentiate them from the traits typically examined in selfenhancement research. First, emotional states are relatively transient, often lasting on theorder of seconds. Traits like one’s competence and kindness, by contrast, remain constantover much longer timescales. Second, emotional states are context-dependent—they arise
in response to specific events—while traits are generally construed as global evaluations
that are less susceptible to contextual variation. Traits might thus be uniquely amenable
to self-enhancement. Consider a typical “self-enhancement experiment”, whereindividuals are asked to make abstract, generalized attributions, like judging their own
trustworthiness compared to that of the average person. When making these judgments,
people can flexibly draw on favorable information about themselves (e.g., Dunning et al,1989), and need not be limited to specific instances of trustworthy behavior. This also
applies to work in which people report higher levels of life satisfaction and other items ofPsychological distance in emotion attribution 4
Subjective Well-Being (SWB) than their peers (Lykken & Tellegen, 1996; Vautier &Bonnefon, 2008; Wojcik & Ditto, 2014)1.
By contrast, making a judgment of an emotional state requires considering thecontext in which the emotion arises (e.g., Ong, Zaki, & Goodman, 2015; Zaki & Ochsner,2011). The context-sensitivity of emotion inference, or affective cognition, sets up
multiple predictions about how people might self-enhance for emotional states. On the
one hand, judgments about one’s own emotional states could approximate selfenhancement over traits like trustworthiness and SWB (Lykken & Tellegen, 1996;
Wojcik & Ditto, 2014). In this case, individuals would globally self-enhance—attributing
more positive emotions to themselves, versus others, irrespective of how “good” or “bad”
a situation is. This prediction is represented in Figure 1a.
A second prediction focuses on people’s sensitivity to situation features, andemerges from research on affective forecasting—people’s predictions about their future
emotional responses. Work in this domain reliably demonstrates that people overestimate
the extent to which discrete events, such as winning the lottery or breaking a limb, will
impact their emotional states (Gilbert, Pinel, Wilsom, Blumberg, & Wheatley, 1998;
Wilson & Gilbert, 2003). This phenomenon arises in part because of a focalism bias thatcharacterizes people’s over-reliance on a “focal” event when predicting emotional
responses (Schkade & Kahneman, 1998; Wilson, Wheatley, Meyers, Gilbert, & Axsom,
2000).

1 At least in English, laypeople and scientists alike often do not distinguish between“happy” emotional states, “happy” moods, a temperamentally “happy” individual, or
global “happiness with life”. In this manuscript, we use “happy” to refer to theemotional state, while we consider items like “happiness with life” as part of SWB(e.g. Lykken & Tellegen, 1996; Vautier & Bonnefon, 2008; Wojcik & Ditto, 2014).

Psychological distance in emotion attribution 5
The focalism bias characterizes people’s forecasts about their own future
emotions, but it could also affect their judgments about others’ emotions. Recent theories
describe both temporal distance—e.g., predictions about the future—and social
distance—e.g., inferences about others—as two sub-types of a more general“psychological distance” (Maglio, Lieberman, & Trope, 2013; Parkinson, Liu, &Wheatley, 2014; Trope & Liberman, 2010). Both social and temporal distance alters
people’s inferences and decision-making in similar ways (e.g., Bar-Anan, Liberman,
Trope, & Algom, 2007; Pronin, Olivola, & Kennedy, 2008; Soderberg, Callahan,
Kochersberger, Amit, & Ledgerwood, 2015; Tamir & Mitchell, 2011). For example,
when deciding how much time to contribute to help tutor fellow schoolmates, students
offered less help if they thought they would help “this week”, than if they thought theywould help “next semester”. Similarly, students themselves offered less help as comparedto how much they thought other freshmen would help (Pronin et al, 2008). Returning toemotion judgments, we predict that focalism—which affects judgments about emotions
across temporal distance—might similarly apply to judgments about emotions acrosssocial distance. People have less information to draw from when drawing inferences
about either socially or temporally distant events, and thus might suffer from a focalism
bias in both cases. If this is the case, people should over-emphasize the emotionally
relevant features of a situation when making judgments about others’ emotions, ascompared to their own. Thus, we may predict that social distance would increase people’s
sensitivity towards situation features, as represented by Figure 1b. For instance,
individuals might overestimate the emotional impact that winning an award, or getting
into an argument, might have on others, as compared to themselves.

Psychological distance in emotion attribution 6
The previous two predictions—self-enhancement and increased sensitivity—
while seemingly different, are not mutually exclusive. In fact, they offer potentiallycomplementary predictions about the nuances of affective cognition. Global selfenhancement, from studies on social comparison, is thought to stem from underlying
motivational forces, and can be operationalized as a “difference in the means” (orintercepts; Fig. 1a). Increased sensitivity, from studies on affective forecasting, is framed
as part of the cognitive process of reasoning about emotions, and can be operationalized
as a “difference in the slopes” (Fig. 1b). A third possibility is that emotional state
attributions across social distance could exhibit both a global self-enhancement and anincreased sensitivity bias. That is, people might globally attribute more positive
emotional reactions to themselves as compared to others, and simultaneously exhibit anincreased sensitivity to outcomes when rating others’ emotional responses. If this is thecase, then we might expect the disparity between self- and other-oriented emotion
attributions to be especially marked as outcomes become more negative, as represented
by Figure 1c. Under this contextualized self-enhancement model, there may be little tono difference between self and other attributions of emotions following positive events:
people would feel similarly positive as they think others will when good things happen.
But following a negative event, people’s self-attributions would be more positive (lessnegative) than their attributions of others’ emotions following that same negative event.
This prediction is also consistent with previous research suggesting that self-enhancement
might serve to buffer against negative, self-threatening information, and hence bestrongest in negative situations (e.g. Alicke & Sedikides, 2009; Taylor & Brown, 1988).

Psychological distance in emotion attribution 7

Self

Other

b) Increased Sensitivityc) Contextualized
Self Enhancement

Positivea) Global
Self Enhancement

Negative

Judgments of Target's Emotional ValenceTargetWorse

BetterWorse

BetterWorse

BetterGoodness Of Outcome

Figure 1. Predictions. On the vertical axis are attributions of emotional valence following
an outcome: negative valence at the bottom and positive valence towards the top. On thehorizontal axes are how “good” or “bad” the outcome is. Overall, emotional valence
attributions should increase with the “goodness” of the outcome. Predictions for
attributions to oneself are given in solid lines, while attributions to others are given indashed lines. (a) Predictions from a context-independent global self-enhancement bias.
(b) Predictions from an “increased sensitivity” account: attributions to others are moresensitive to changes in the outcome. (c) Combining both (a) and (b) to get contextualized
self-enhancement.
In this work, we test these three plausible models of affective cognition byleveraging a paradigm we developed to examine emotion attribution under tightly
controlled circumstances (Ong, Zaki, & Goodman, 2015). In this paradigm, participants
view another person playing a monetary gamble, and then infer the emotions they believethat person feels in response to the outcome of the gamble. Here, we extend thisparadigm by comparing participants’ inference about another person’s emotions toinferences about their own emotions after playing the gamble. This affords at least two
methodological advantages. First, we can vary the parameters of the gambles thatparticipants observe, which allowed us to vary the “goodness” of the outcome (thePsychological distance in emotion attribution 8
horizontal axes in Fig. 1) in a systematic fashion. Classic theories argue that people’s
subjective utility tracks not the absolute value of an outcome, but rather the extent towhich it exceeds expectations (Kahneman & Tversky, 1979; Mellers, Schwartz, Ho, &Ritov, 1997). In particular, we varied the prediction error, or extent to which participants
won more or less money than would have been expected based on the gamble parameters.
Indeed, we found in previous work that prediction errors in this paradigm strongly
predicted people’s attributions about others’ emotions (Ong et al., 2015).
Secondly, this paradigm allowed us to carefully control the form of judgment
people made through a between-participants approach. In studies of self-enhancement,
individuals are typically asked to directly compare themselves to others (“Compared tothe average person, how X are you?”; e.g., Dunning et al., 1989; Lykken & Tellegen,
1996; Wojcik & Ditto, 2014). This approach has faced methodological criticisms (Klar &Giladi, 1999), for example, on the grounds that it induces a socially desirable motive forparticipants to self enhance (Chambers & Windschitl, 2004). Scientists can circumvent
this problem by having participants make separate judgments about themselves versus
others (Vautier & Bonnefon, 2008). This so-called “indirect method” provides a moreconservative and precise estimate of self-enhancement (Chambers & Windschitl, 2004).
Here, to model biases in emotion inference, we take this method a step further, and havedifferent groups of participants make judgments only about themselves, or about others ina between-participants fashion.

Psychological distance in emotion attribution 9
Overview of the Current Work
Across three studies, we examined how people attribute emotions to themselves, or toothers, following simple gambles. We find evidence for contextualized self-enhancement
in emotion attribution consistent with the combination of biases described in Figure 1c.
In Study 1, participants observed another person make simple monetary gambles, or
imagined playing those same gambles themselves. Participants attributed more positiveand less negative emotions to themselves as compared to others, especially in response tonegative outcomes. In Study 2, we manipulated the social closeness between theparticipants and the target, and demonstrate that the strength of emotion attribution bias
varies parametrically with social distance (Murray & Holmes, 1997; Suls, Lemos, &Stewart, 2002).
In Study 3, we further probed the idea that emotion attribution might varysimilarly across both social and temporal distances. In particular, we combined these two
types of distances by asking participants to make attributions about themselves or anotherperson, either now or in the future. This 2-by-2 factorial design indeed revealed that
temporal distance affected emotion attribution in a similar manner to social distance:
Participants attributed more positive and less negative emotions to targets (themselves orothers) in response to gambles made now, as opposed to gambles in the future. Broadly,
our data speak to a nuanced self-enhancement bias in the attribution of emotional statesthat (i) varies by situation context, and (ii) varies along multiple dimensions of
psychological distance.

Psychological distance in emotion attribution 10
Methods and Results
All code to replicate our experiments and reproduce our analyses, and all data, can befound at: https://github.com/desmond-ong/emotionPsychDistanceStudy 1: Self and Other emotion attributions
Study 1 examined participants’ attributions of emotions to themselves and another person
following a hypothetical monetary gamble. The simple nature of the paradigm allowed us
to systematically vary features of the scenario (e.g., how much the target wins in aparticular gamble) and examine the resulting emotion attribution.
Methods. We recruited 200 participants (81 female; mean age=34.5 years) online
using Amazon’s Mechanical Turk (AMT), and randomly assigned them to an Other(N=98) or a Self (N=102) condition. The Other condition is a replication of the firstexperiment of Ong et al. (2015).
Other condition. On each trial, participants watched a fictional character spin awheel containing three monetary payoffs of differing amounts. Participants were asked toimagine that the character had won the amount of money associated with the part of thewheel on which they had landed (much like in the gameshow “Wheel of Fortune”; see
Fig. 2 for an illustration).
Outcomes on each trial were selected, without replacement, from a larger set of
50 different scenarios. Each scenario comprised winning a particular amount of moneyon a particular wheel. The wheels were designed to de-correlate the amount won on aparticular spin from the expected value—the averaged reward that one should expect

Psychological distance in emotion attribution 11
from the wheel2. This allowed us to vary how positive or negative the outcome was,relative to the expectation of the wheel, and examine participants’ emotion attribution as
a function of these outcomes. All values on the wheels are greater than or equal to $0: ourprevious work (Ong et al., 2015) demonstrated that spins with negative prediction errors
are interpreted as negatively valenced events, even if the gamble has a positive payoff(This follows previous work on reference-dependent utility, e.g., Kahneman & Tversky,1979).
After observing the outcome of a spin, participants judged the extent to which
they believed the character would experience each of eight emotions (Happiness,
Sadness, Anger, Surprise, Disgust, Fear, Contentment, and Disappointment), using 9
point Likert scales. Each participant completed 10 trials. The names of the characters
were randomized on every trial.
Self condition. Participants imagined themselves, instead of a fictional character,playing the gambles. Participants clicked a button to spin the wheel, and after observing
the outcome of the spin, rated how they felt along the same eight emotions used in the
Other condition. The gambles were hypothetical, and participants were not paid any
additional money based on the outcomes of the gambles. Like the Other condition,
participants completed 10 trials.

2

The expected value is calculated using a standard definition. For each sector of the wheel, we take theproduct of the notational reward and the probability of obtaining that reward (i.e., the size of the sector
relative to the whole wheel). The expected value of a wheel is the sum of these products.

Psychological distance in emotion attribution 12

Figure 2. Illustration of the experimental paradigm used in Studies 1-3. In the Other
condition, participants are shown a stick figure character as above, playing the wheel andwinning a certain amount (i.e., Fig. 2A and 2B). In the Self condition, the stick figure
character is removed and participants are asked to imagine themselves playing the game.
Study 2 uses the same sequence as the Other condition in Study 1. Study 3 replicatesStudies 1 and 2 and extends them by adding two Future conditions, where participants
only see the wheel before it is spun and prospectively rate how they or another target
would feel if it were to land on one of the outcomes (i.e., Fig. 2A only).
Results. We operationalized the utility of the outcome by calculating a prediction
error (PE) for each outcome, as in our previous work with this paradigm (Ong et al,2015). PE signals, here, how positive or negative each gamble outcome was relative tothe wheel’s expected value (PE = win – expected value). In essence, a high (positive) PE
means that an outcome was better than expected, whereas a low (negative) PE means thatan outcome is worse than expected (Holroyd & Coles, 2002; Kahneman & Tversky,
1979; Sutton & Barto, 1998). We constructed linear mixed-effects models, with PE andits interactions with a condition (Other versus Self) dummy variable as fixed effects, andrandom intercepts by participant and scenario. We estimated eight separate models, one
for each of the eight emotions.
Figure 3 displays data for Happy and Disappointment judgments as a function of(i) condition (Other versus Self), and (ii) Prediction Error (PE). In both conditions, PE
positively predicts happiness judgments, and negatively predicts disappointment

Psychological distance in emotion attribution 13
judgments. This means, unsurprisingly, that participants judge both themselves andothers as feeling more happiness and less disappointment after receiving better, as
compared to worse, monetary outcomes.

Experimental
Condition

Self

Other

−50

Experimental
Self
Condition−25
0Prediction Error

Other
25

50

−50

−25

25

50

10.0

Happy

7.5

5.0

2.5

Disappointment

7.5

5.0

2.5

0.0
0

Prediction Error
Figure 3. Participants’ attributions of happiness and disappointment to themselves (insolid, red lines) and others (dashed, blue lines) as a function of PE. Data points are
jittered for visibility, with best linear fits overlaid, with a shaded 95% confidence region.

Psychological distance in emotion attribution 14
Two key findings emerged from our analysis. First, when controlling for PE,
participants attribute less happiness (b = -0.307 with 95% CI: [-0.596, -0.019], t(196) = 2.09, p = 0.04; see Table 1 for full statistics) to others than to themselves. The simple
effect of distance can be interpreted as the difference between the Other and Self
conditions when the target wins an amount equal to the expected value of the wheel (i.e.,
at PE=0). This means that, on average, participants attribute 0.31 points less happiness(on a 9 point scale) to others than to themselves after winning the expected amount.
Participants also tended to attribute more sadness, anger, disgust, and disappointment(p’s<0.001), to others as compared to themselves for an expected reward (see Table 1 for
full results). The self-enhancement simple effect was not significant for judgments ofcontentment (p=0.29). Overall though, assessing the pattern of results across all of theemotions, the simple effect results are consistent with a self-enhancement bias (Fig. 1a),whereby participants self-enhance by attributing more positive emotions and lessnegative emotions to themselves as compared to others.
We next explored reward sensitivity, or the slope of the graphs in Figure 3. We
find that social distance increases sensitivity to the prediction error of the outcome. Theinteractions of Self versus Other condition with PE are significant and positive for bothhappiness and contentment (p’s<0.001; Table 1). In particular, this suggests thatparticipants weigh the outcome PE more when making judgments about others’ emotions
than when making judgments about themselves. A unit change in the goodness of theoutcome affects participants’ judgments for others more than it affects participants’
judgments for themselves (as in Fig. 1b). The interactions are also significant and in thepredicted directions for negative emotions: sadness, anger, disgust, and disappointment

Psychological distance in emotion attribution 15(p’s<0.001). These interactions demonstrate an increased sensitivity to changes in thesituation valence, and are similarly robust across both positive and negative emotions.
The linear mixed-effects models provided good fits to the data, explaining between 51%
to 76% of the variance (see Table 1 for individual model R2).
Overall, the combination of both the interaction (steeper slope) and the simple
effect (group differences at zero PE) imply that the self-enhancement effect iscontextualized, and is more pronounced at negative PE, i.e., when targets lose more
relative to the expected value. Participants think that they would react much morepositively than others when reacting to negative gamble outcomes (negative PE), and thisdifference diminishes when outcomes are better than expected (positive PE; Fig. 1c).

Simple Effect of Distanceb [95% CI]tp-.307 [-.596, -.0185] -2.09.038*.260 [-.216, .736]
1.07.29 n.s.

Reward Sensitivityb [95% CI]
t.0148 [.0107, .0190]
7.07.0157 [.0103, .0210]
5.75

p<.001***<.001***

R2
.76
.69

-.0245 [-.355, .306]-.15.89 n.s.

.0154 [.0112, .0195]

7.31<.001***

.76

Sad
Anger
DisgustDisappointment.643 [.336, .949].511 [.221, .801].447 [.190, .703].877 [.559, 1.195]

4.11
3.46
3.41
5.40

<.001***<.001***<.001***<.001***-.0237 [-.0282, -.0193]-.0195 [-.0231, -.0159]-.0159 [-.0198, -.0121]-.025 [-.0301, -.0199]

-10.5
-10.6
-8.05
-9.65

<.001***<.001***<.001***<.001***

.63
.58
.51
.69

Negative
EmotionComposite.620 [ .367, .873]

4.80<.001***-.0211 [-.0245, -.0178]-12.4<.001***.69

SurpriseFear.748 [.323, 1.173].033 [-.159, .225]

3.45
0.33

<.001***.74 n.s.

-.0046 [-.0105, .0014]-.0015 [-.0033, .0003]

-1.51
-1.63

.13 n.s.
.11 n.s.

.56.63

EmotionHappy
Content
Positive
emotioncomposite

Table 1. Study 1 results. Each row indicates the results of one model predicting one
emotion (or emotion composite, described in text). Left: Coefficients on the simple effectof condition (i.e. the contrast Other-Self at PE=0) in the mixed models. Right: Rewardsensitivity, or the coefficient on the Condition x PE interaction term in the mixed models.
(n.s. not significant, * p<.05, ** p<.01, *** p<.001). We calculated model R2 using thedefinition of “conditional R2” provided by Nakagawa and Schielzeth (2013), which
describes the proportion of variance explained by both the fixed and random effects.

Psychological distance in emotion attribution 16
For a rough estimate of the effect size in meaningful quantities, consider thecoefficients on the simple effects and interaction terms in the model predicting
disappointment (coefficients = 0.88 and -0.025 respectively; Table 1). On average,
participants tended to attribute 0.88 points more disappointment, on a 9 point Likert
scale, to a random other than to themselves, if both had won an amount equal to the
expected value of the gamble—this is the simple effect. For every additional dollar “lost”(in our paradigm), participants’ attributions of disappointment to others increases 0.03
units more per dollar, as compared to their attributions of disappointment tothemselves—this is the difference in slopes. Concretely, if both the average participant
and a stranger won $35 less than the expected value, then the participant would attribute
0.88 + (-0.025)*(-35) = 1.76 more points of disappointment to this stranger than tothemselves, or almost double the simple effect. Conversely, this other-versus-selfdifference would decrease in magnitude as the PE becomes less negative and morepositive. However, we caution against extrapolating the results to large, positive PEs
beyond what we measured. Importantly, we do not expect the self-enhancement tosignificantly “flip” in sign at extreme positive values of PE, given the theoreticalmotivation for this effect, although future work could verify this via empiricallyexamining even larger, positive PEs. Finally, we stress that these specific numericalmagnitudes of the effects apply within our current paradigm, and is meant more toillustrate a general, intuitive understanding of the results.
For completeness, we report the results over surprise and fear, though we had no apriori hypotheses regarding these emotions from our prior work (Ong et al., 2015).
Looking at the simple effects, we find that participants attributed more surprise to othersPsychological distance in emotion attribution 17
as compared to themselves (p<0.001), but no difference in fear (p=0.74). The interactionsof self versus other with PE did not significantly predict surprise and fear judgments(p’s>0.11).
Finally, because the results of Study 1 suggested one pattern of results for the
positive emotion judgments, and a second pattern for the negative emotions, we created
two composite variables to minimize the number of comparisons in the studies we report
later in this paper. We averaged the positive (happiness, contentment) and negative(sadness, anger, disgust, and disappointment) emotion attributions into two composites.
We verified that the results for the emotion composites are consistent with the individual
emotions (Table 1). The simple effect for the positive emotion composite is not
significant, although the simple effect for the negative emotion composite, and theincreased sensitivity for both positive and negative emotion composites, appear to bestrong, robust effects. We argue that the lack of statistical significance for the simple
effect of the positive emotions by itself is not a disconfirmation of our hypotheses, as
simple effects have to be interpreted together with higher-order interactions. In addition,
the results for the positive emotions should be interpreted together with thecomplementary results for the negative emotions. For the remaining studies in the paper,
we will use the emotion composites as the unit of analysis, and we present the results on
all the individual emotions in the Supplemental Material.

Study 2: Social DistanceStudy 1 demonstrates that people attribute more favorable emotion states to themselves
than to others following a simple gamble; their judgments for others were also more

Psychological distance in emotion attribution 18
sensitive to changes in the reward. In Study 2, we examine how this bias varies withsocial distance, by having participants draw inferences about the emotions of targets who
systematically varied in social distance from the participants.
Methods. We recruited 300 participants (122 female; mean age=33.6 years)
online using Amazon’s Mechanical Turk (AMT). In the first part of the experiment,
participants learnt about a “previous participant” in our experiment with whom they had
been paired. Participants were told that they would first get to know a little about theirpartner (hereafter, the target). Participants answered a series of personality questions
from a ten-question subset of the Big Five Inventory (BFI-10; e.g., “I see myself as
someone who is reserved”; Rammstedt & John, 2007). For simplicity, we adapted the
BFI-10 such that participants answered each item as a True/False binary item instead ofon a Likert scale. After each question, participants were told that the target had given
either the same or a different answer as them. As an attention check, participants thenindicated the answer that the target had given. Sixty-two participants answered one ormore of these attention checks incorrectly; these participants’ data were excluded fromfurther analysis.
In actual fact, we generated the target’s answers to the BFI to vary the perceived
social distance separating the target and participant. We did this by varying the number of
personality questions that the target answered similarly to the participants. In particular,
participants encountered targets who answered 1, 3, 5, 7, or 9 questions (out of a total of10) in the same way participants themselves had answered. Thus, a participant who
encountered a target who answered 9 questions similarly to the participant would
experience low social distance from (i.e., high similarity with) that target. Conversely, aPsychological distance in emotion attribution 19
participant who encountered a target who answered 1 question similarly to the participant
would experience high social distance from (i.e., low similarity with) that target. All
participants answered the BFI-10 in the same order, but saw the order of similar anddissimilar feedback in a random order. Note that each participant saw only one target, andconsequently only one social distance: Social distance was a between-participant
manipulation.
After answering the BFI-10, participants then saw a summary statement: they andthe target had an approximately 10%, 30%, 50%, 70%, or 90% similarity in personality.
As a manipulation check, participants then filled out a continuous version of the Inclusionof Other in Self scale (IOS; Aron, Aron, & Smollan, 1992), to indicate how much theyfelt their self-concepts and that of the target overlapped. They also reported on how
similar they felt to, how much they liked, and how much they empathized with the target.
The second half of the experiment was similar to the Other condition in Study 1(Fig. 2). Participants watched the target play ten rounds of the same wheel game as inStudy 1, attributing emotions to the target after each round.
Results. Manipulation checks confirmed that the manipulated social distanceincreased participants’ subjective distance from the target. As expected, the number ofquestions targets and participants answered similarly tracked participants’ sense ofoverlap with (r=0.60, t(236)=11.43, p<0.001), similarity to (r=0.76, t(236)=18.22,
p<0.001), liking of (r=0.46, t(236)=7.91, p<0.001), and empathy for the target (r=0.46,t(236)=8.06, p<0.001).
Next, we modeled the results in a similar fashion as Study 1. We created two
composite variables by averaging the positive and negative emotion ratings. Results forPsychological distance in emotion attribution 20
individual emotions are consistent with the results for the emotion composites, and wereport detailed results for the individual emotions in the Supplemental Material. We fit
mixed-effects linear models separately for the positive emotion composite and thenegative emotion composite. We used the PE of the gambles that the target played, as inStudy 1, and its interaction with manipulated social distance as fixed effects. We modeledsocial distance as a continuous variable3.
As targets became more socially distant from (i.e., less similar to) the participants,
participants attributed more negative emotions to the target (b=0.055 [0.009, 0.101],t(232)=2.33, p=0.020), but not significantly different positive emotions (p=0.34; Fig. 4,
left panel). This is a simple effect, and so can be interpreted as the effect of distancewhen the target won an amount equal to the expectation of the gamble. We also observe
significant interactions of social distance with PE (Fig. 4, right panel) for both positive
emotions (b=0.0011 [0.0005, 0.0018], t(232)=3.35, p<0.001) and negative emotions (b=0.0012 [-0.0018, -0.0006], t(232)=-3.90, p<0.001). This means that participants’
judgments of others’ emotions become more sensitive to changes in the outcome as thosetargets became more socially distant. The models explained a large proportion of thevariance in participants’ emotion attributions (positive composite model conditional
R2=.76; negative composite conditional R2=.71; using the definition from Nakagawa &Schielzeth, 2013). The results of Study 2 replicate that of Study 1: the weak, nonsignificant result of the simple effect of positive emotions as well as the robust simple
effect for negative emotions, and the interactions for both composites. We note that the
regression coefficient effect sizes in Study 2 are weaker than the effect sizes in Study 1,

3 We tested for, but did not find, non-linear (i.e., quadratic) effects of social distance, so we report themodel with only a linear social distance term.

Psychological distance in emotion attribution 21
and this is correspondingly because the social distance manipulation is subtler andweaker in Study 2 (see Supplemental Materials for more details). That said, despite thesubtler manipulation, both the simple effects and the interactions replicate the pattern
documented in Study 1: social distance affects emotion judgments least at positive levelsof PE, and more at negative levels of PE.

Magnitude of Coefficients (b's)

Distance simple effect (at PE=0)

Reward Sensitivity x Distance

0.10
0.001
0.05
0.000
0.00
−0.001−0.05

Positive

Negative

Positive

Negative

Composite Emotions
Figure 4. Study 2 results. Left: Simple effect (i.e., the effect of social distance at PE=0).
Right: Reward sensitivity across social distance (i.e., interaction of social distance with
PE). Error bars represent 95% Confidence Intervals.
The results of Study 2 demonstrate that in addition to rating themselves as
experiencing more desirable emotion than a stranger, people also judge socially close, ascompared to distant targets to feel more similarly to them. People’s judgments also
increase in sensitivity to the situation outcome for distant, as compared to socially close,
targets. Studies 1 and 2 thus jointly provide consistent evidence for a social-distancemoderated bias in emotional reasoning.

Psychological distance in emotion attribution 22
Study 3: Combining social and temporal distanceStudies 1 and 2 showed evidence for an emotion attribution bias that varies with social
distance. In particular, the increased sensitivity that people show when making judgments
about others’ emotions (Studies 1 and 2) looks similar to the focalism bias that people
display when making judgments about their future emotions (e.g. Wilson et al, 2000).
Indeed, previous work shows that both social and temporal distances affect cognition insimilar ways (e.g., Bar-Anan et al., 2007; Kim, Zhang, & Li, 2008; Pronin et al., 2008;
Tamir & Mitchell, 2011). Following this reasoning, we should also expect that theobserved emotion attribution bias should similarly apply to judgments about targets in the
future. We designed Study 3 to test this by varying both social and temporal distance.
Methods. We recruited 400 participants online using Amazon’s Mechanical Turk
(AMT), and randomly assigned them to one of four conditions in a 2 (target: Other vs.
Self) x 2 (time frame: Now vs. Future) design.
The Other,Now (N=100) and Self,Now (N=100) conditions were identical to the
Other and Self conditions in Study 1, and provide a direct replication. In the twocorresponding Future conditions (N=100 for Self,Future; N=100 for Other,Future),
participants were shown the same wheels but did not actually see gambles take place.
Instead, participants were asked to forecast how the target (Self or Other) would feel inthe future if the wheel were to land on one of the payoff amounts. They were only asked
about one possible outcome (“How do you think [you / other character’s name] will feel
if the wheel landed on $X?”). Concretely, participants were only shown the initial
position of the wheels, and the wheels were never spun. For example, in the Self,Future
condition, a participant on a trial could be shown the initial wheel in Figure 2A and bePsychological distance in emotion attribution 23
asked to predict how they would feel if the wheel were to land on $60. After theparticipant made emotion judgments for just one possible outcome, the experiment would
immediately move on to the next trial.
Results. We followed the same analysis procedure as in the first two studies. We
created a positive emotion composite and a negative emotion composite; the results forthe individual emotions, given in the Supplemental Material, are consistent with theemotion composites reported here. Here, we have a 2x2 design and hence 2 condition
dummy variables, one for the “Other-Self” contrast (social distance) and one for the“Future-Now” contrast (temporal distance). We included, as fixed effects, all theinteractions between the three predictors: PE, a dummy variable for the social distancecondition, and the corresponding dummy variable for the temporal distance condition. As
in our previous studies, we included random intercepts by participant and scenario. We
estimated two separate models, one for the positive emotion composite and one for thenegative emotion composite.
Similar to Studies 1 and 2, we again find results consistent with contextualized
self-enhancement (Fig. 5, left panel). There is a significant simple effect of social
distance on the negative emotions. When the target won an amount equal to the expectedvalue, participants tended to attribute more negative emotions to others than tothemselves (b=0.655 [0.425, 0.885], t(378)=5.58, p<0.001), but not less positive
emotions (p=0.12). In addition, there is also a significant simple effect of temporal
distance. Participants attributed more negative emotions (b=0.426 [0.183, 0.668],t(378)=3.44, p<0.001) and less positive emotions (b=-0.329 [-0.632, -0. 026], t(378)=2.13, p=0.034) to targets in the future, as compared to targets who already know thePsychological distance in emotion attribution 24
results of the gamble. The two-way interactions between the Other-Self and Future-Now
dummy variables were not significant for either the positive or negative emotion
composites (p>.7).

Magnitude of Coefficients (b's)

Contrast

Self−Other

Distance simple effect (at PE=0)

Now−Future
Reward Sensitivity x Distance

0.01
0.5
0.00
0.0
−0.01

−0.5
−0.02
Positive

Negative

Positive

Negative

Composite Emotions
Figure 5. Study 3 results. Left: Simple effect by distance (i.e., the effect of the distancemanipulations at PE=0). Right: Reward sensitivity across psychological distance (i.e., theinteractions of the two distance manipulations with PE). Error bars represent 95%
Confidence Intervals.
Next, we examine the interactions with PE. Again, similar to Studies 1 and 2, wefind that, for social distance, there is a significant interaction with PE for positive(b=0.010 [0.0055, 0.015], t(378)=4.34, p<0.001) and negative emotions (b=-0.016 [0.020, -0.012], t(378)=-8.49, p<0.001). We observe a similar pattern for temporal
distance for negative emotions (b=-0.0084 [-0.012, -0.005], t(378)=-4.44, p<0.001),
although the interaction with positive emotions is not significant (b=0.003, p=.13). These
interactions reflect a pattern similar to the one documented in Studies 1 and 2:

Psychological distance in emotion attribution 25
Participants rate themselves, as compared to others, and targets now, as compared to in
the future, as experiencing less negative and more positive emotions following relatively
unfavorable outcomes. When prediction errors become more positive, this bias shrinks,
suggesting that observers reason that, when good things happen, everyone is similarly
positive.
Finally, we were interested in how both dimensions of psychological distance
together might influence the emotion attribution bias. For example, the effect of
psychological distance could be super-additive across both dimensions, whereby the
combined effect of the temporal-and-social distance manipulations would be stronger
than the sum of the individual manipulations. Conversely, the effect of distance could be
sub-additive, whereby the combined effect would be less than the sum of the individual
effects. To investigate this, we examined the highest-order interactions in our model. The
three-way (PE x social x temporal) interaction is significant for positive emotions (b=0.0090 [-0.0154, -0.0026], t(378)=-2.75, p=0.006) and marginally significant for negative
emotions (b=0.0048 [-0.0005, 0.0101], t(378)=1.78, p=0.076). These three-way
interactions are opposite in sign to the two-way (PE x social / PE x temporal)interactions (e.g., the coefficient for the three-way interaction for positive emotions isless than zero, while the corresponding two-way interactions are both greater than zero).
This difference in sign suggests that the effects of distance are diminishing across the twodimensions. That is, the marginal effects of distance taper off when both social andtemporal distance are present; Put another way, the effect of psychological distance on
the emotion attribution bias is sub-additive across multiple dimensions of distance. Thisis consistent with at least two previous studies that also found diminishing returns acrossPsychological distance in emotion attribution 26
two dimensions of psychological distance when people make choices about distant others(Kim et al., 2008; Pronin et al., 2008). We expand on this point in the general discussion.
The results of Study 3 replicate and extend the results of Studies 1 and 2. As in
Studies 1 and 2, the models in Study 3 explained a large proportion of the variance inparticipants’ emotion attributions (conditional R2=.69 and .64 for the positive andnegative composites respectively). The fact that our bias accumulates across both social
and temporal distances is also consistent with previous work showing that dimensions of
psychological distance interchangeably (and sub-additively) affect decision-making (Kimet al, 2008; Pronin et al, 2008). Importantly, our results underscore the idea that thesenuanced emotion attribution processes are not limited to social judgments. Rather, thisbias underlies how people fundamentally reason about emotions (Ong et al, 2015) acrossmultiple forms of psychological distance.

Discussion
We tested three plausible theoretical models about how people make attributionsof emotions under varying levels of psychological distance. Across three studies, wefound evidence for a context-sensitive egocentric bias in people’s judgments of emotions.
First, participants, on average, tended to attribute less positive and more negative
emotions to others than to themselves after experiencing an emotionally relevant
situation—in our study, hypothetical gambles. Second, participants’ judgments of others’
emotions, as compared to their own emotions, are more sensitive to the emotionally
relevant features of a situation (Study 1). We found that this context-sensitivity scaleswith social distance: Participants attributed less favorable emotions to targets that werePsychological distance in emotion attribution 27
socially distant, as compared to targets that were socially closer (Study 2). Moreover, thebias is moderated in a similar manner by temporal distance as well. Participants judgedthat they (and others) in the future would similarly feel less favorable emotions after
gambles, as compared to after gambles they have just played (Study 3). Despite theconservative between-participant nature of our studies, the pattern of results robustly
replicated across the three studies. Our findings illustrate a complex interplay between
people’s tendencies to self-enhance and the context-sensitivity with which people makeemotion attributions.
The two characteristics of this bias—the self-enhancement and the increased
sensitivity to situation features—can be interpreted by bringing together two different
literatures. First, motivated self-enhancement accounts for the overall direction of thebias: people self-enhance by attributing more favorable emotions to themselves. For
example, negatively valenced events might function like a “threat” towards one’s
emotional well-being, and this bias may serve an adaptive purpose by allowing people tobuffer their emotional health against such negative information (e.g., Alicke & Sedikides,
2009; Taylor & Brown, 1988). Second, the focalism bias studied in the affective
forecasting literature accounts for the increased sensitivity to situation features. One
possible explanation for this effect in our studies is that people have less information
when making judgments about others or their distant future selves, such as how theseothers tend to react in a given situation, and therefore base their judgments more on
salient contextual information in the situation. By contrast, when making judgments
about themselves, people have more information: they know their own preferences andidiosyncrasies, and they might even spontaneously reappraise extreme situations. Hence,Psychological distance in emotion attribution 28
their judgments would incorporate these other factors, and would track less strongly the
specific features of the situation. Future work should examine the specific cognitive
processes that contribute to this sensitivity bias in emotion attribution.
The current work offers a different angle to previous work on how people makejudgments of emotions across time. In addition to affective forecasting (e.g., Gilbert et al,
1998; Wilson & Gilbert, 2003), this work also relates to previous studies on what has
been called unrealistic optimism (e.g., Weinstein, 1980). When thinking about their lifein the abstract, people tend to predict that they will experience greater Subjective WellBeing in the distant future, as compared to the present or the near future (Heller, Stephan,
Kifer, & Sedikides, 2011; Robinson & Ryff, 1999; Stephan, Sedikides, Heller, &Shidlovski, 2015). Although at first glance this may seem contradictory to our current
findings, we propose that this may be resolved by considering whether such attributions
are made in a global or contextualized manner. One proposed explanation of unrealistic
optimism is that, when asked to predict their global SWB in the future, without additional
context, people rely on abstract ideals like ideal self-concepts, hopes, and ambitions(Heller et al, 2011), and hence inflate their predictions of their future SWB. Indeed,priming people with more concrete information about their future attenuates thisforecasting optimism (Robinson & Ryff, 1999). By contrast, when individuals forecast
their emotions in a specific emotion-elicting context, such as how they would feel if theirteam wins or loses a football game, they tend to focus on the specific features of that
context, and their predictions tend to be biased based on the specific context (e.g., Wilson
et al, 2000). Thus, evidence points to there being different underlying cognitive processes
that contribute to global versus contextualized judgments. They need not be mutuallyPsychological distance in emotion attribution 29
exclusive; Certain trait judgments (e.g., one’s current SWB) may occur via anaggregation of a set of states (e.g., recent emotional states), and so contextualized effects
might contribute to global trait judgments as well, but presumably to a weaker extent.
This leaves open many questions, such as how emotional state judgments—and theirassociated cognitive processes and biases—may affect judgments of longer-term affectlike mood, and global assessments like SWB. These are important questions in social
cognition that future research should explore.
Converging evidence suggests not only that different dimensions of psychologicaldistance are somewhat interchangeable, but also that distances can be added acrossdimensions (Kim et al., 2008; Pronin et al., 2008). In Study 3, we found that the effect ofdifferent dimensions of distance on emotion attribution is sub-additive: that is, the effectof both social and temporal distance is smaller than the sum of the effect of social
distance, and the effect of temporal distance. Such sub-additivity is common across otherbasic psychological processes like perception: People tend to perceive brightness,loudness, an object’s physical size and distance, and even economic gains and losses subadditively (e.g., Stevens’ psychophysical power law; see Kim et al, 2008 for an in depth
discussion). The sub-additive perception of multiple dimensions of psychologicaldistance has important implications for designing applications. For example, considering
one’s present situation from an emotionally distant standpoint contributes to adaptive
emotion regulation (Kross & Ayduk, 2008). Adding additional dimensions of
psychological distance (e.g., imagining an event in a spatially distant location) may yielddiminishing results. Finally, we currently do not know how units of distance on one
dimension (e.g., time) map onto distances on another dimension (e.g., social distance).

Psychological distance in emotion attribution 30
The “Now-Future” temporal distance manipulation we used in Study 3 elicited weaker
behavioral effects than the “Self-Other” social distance manipulation, and one reason
could be because the temporal manipulation translated to a psychologically smaller
amount of perceived psychological distance as compared to the social distancemanipulation. Future research should more rigorously map the relationships between
these distance dimensions.
The gambling paradigm we used in our studies offers at least two advantages.
First, it provides a standardized, somewhat novel situation, which facilitates comparing
judgments across participants. Second, and perhaps more importantly, the nature of theparadigm allowed us to parametrically vary various parameters of the gamble. This inturn enabled us to quantitatively measure the size and context dependency of the selfenhancement bias. This also means that the paradigm is simple, and does not capture therichness of situations we encounter in everyday life. That said, we feel that the work
presented here gives a firm footing from which to further examine more naturalistic
scenarios, across different contexts. For example, an interesting open question is whether
this emotion attribution bias varies with the social desirability of emotions in different
types of situations. Negative emotions are often undesirable (as in our studies), but insome cases, people want to feel negative emotions (Tamir, Mitchell, & Gross, 2008;
Zaki, 2014), for example, when negative emotions are goal-consistent like feeling anger
or antipathy prior to a conflict. Recent work also suggests that in cases like these where
negative emotions might be desirable, people might self-enhance by claiming to feel
more negative emotions. For instance, individuals from a majority race reading about
racial discrimination perpetrated by their racial group judge themselves to feel more guiltPsychological distance in emotion attribution 31
than others in their racial group (Goldenberg, Saguy, & Halperin, 2014). Individuals also
judge themselves to feel more intense negative emotions than others immediately
following large-scale negative events, such as national tragedies and terrorist attacks(White & Van Boven, 2012). Thus, biases in emotion attribution might not always reflecta desire to view one’s self as experiencing more positively valenced emotions, but should
flexibly tune individuals towards the belief that they experience more desirable emotions,irrespective of valence. This is also a natural prediction of theories of motivated cognition(e.g., Hughes & Zaki, 2015). Future work should test this prediction by varying the goalconsistency of emotions across a variety of contexts.
This work also raises interesting questions about the nature of the cognition andmotivations that underlies this bias. Because we designed these studies as betweenparticipants, we were not able to examine individual differences in this bias. Additional
research addressing this could help scientists understand possible cognitive andmotivational mechanisms, as well as potential implications, such as for mental health(Taylor & Brown, 1988). Previous studies have suggested that depressed patients may notshow “better-than-average” social comparative biases (e.g., Alloy & Abramson, 1979;
but see Ackermann, & DeRubeis, 1991, for a summary of challenges), and may in fact,
want to regulate their emotions to feel more sadness (Millgram, Joorman, Huppert, &Tamir, 2015). Understanding biases and motivations in emotion attribution might prove
to be especially important for understanding and treating mood disorders like major
depression, bipolar, and the anxiety disorders. Future work should start by investigating
how individual differences in patients’ emotion attribution (to themselves and to others,Psychological distance in emotion attribution 32
under different contexts) might be related to risk for psychopathology, symptom severity,or potential relapse in remitted patients.
In sum, we show that the self-enhancement bias common across many aspects ofsocial comparison extends to contextualized emotional states as well. People self-enhanceby attributing more positive and less negative emotions to themselves than to others.
Importantly, however, this bias varies with the situation context. In our studies, this bias
varies with the valence of a given situation, such that this self-enhancement is strongest
in negative situations, and is relatively attenuated in positive situations. We also
demonstrate that this bias varies parametrically with social distance and across multiple
dimensions of psychological distance. Our results speak to the importance of contrasting
global evaluations, made outside a specific situation context, with contextualized
affective cognition. There remain many more questions, such as how this emotion
attribution bias might vary with the goal-consistency or social desirability of emotions incontext. Thus, our results support the claim that people might often consider themselves“happier than thou”, but this motivated bias is more nuanced and context-dependent thanpreviously understood.

Acknowledgements
This work was supported in part by an A*STAR National Science Scholarship to
DCO and by a James S. McDonnell Foundation Scholar Award to NDG. We would liketo thank Patricia Chen and Brent Hughes for comments on earlier versions of thismanuscript.

Psychological distance in emotion attribution 33
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Psychological distance in emotion attribution 37
Supplemental Material
All code and data can be found athttps://github.com/desmond-ong/emotionPsychDistance
As reported in the text, we fit mixed-effects linear models for each of theemotions, using PE and its interaction with the distance variables as fixed effects, andrandom intercepts by participants and trials. These models were of the form: Emotion ~distance * PE. For Study 3, there are 2 types of distances, hence we added allinteractions: Emotion ~ social_distance * temporal_distance * PE. There are 8 different
emotions, across three studies, so there are 24 different models. In Table S1 we report thecoefficients and p-values of the simple effects of condition, as well as the interactions ofcondition with PE, for all studies. The coefficients for Study 1 were reported in the main
text, and are reproduced in the table to aid in comparison. We provide a short, informal
discussion on the relative magnitudes of the coefficients across our studies, to show that
our estimated results are consistent in magnitude across studies.

Psychological distance in emotion attribution 38

EmotionStudy 1Social Distance(Other - Self)

Study 2Social DistanceStudy 3Social Distance(Other - Self)

Study 3
TemporalDistance(Future - Now)

Happy

-0.31 (0.04*)-0.023 (0.27)-0.063 (0.64)-0.17 (0.24)

Content

0.26 (0.29)(unexpected
sign)
0.64
(<0.001***)0.51(<0.001***)0.45(<0.001***)0.88(<0.001***)-0.025 (0.51)-0.44 (0.031*)-0.50 (0.022*)

0.051 (0.046*)

0.77(<0.001***)0.62(<0.001***)0.43(<0.001***)0.85(<0.001***)0.61(<0.001***)0.40 (0.005**)0.75(<0.001***)0.033 (0.74)

0.080 (0.017*)

0.42 (0.026*)

0.042 (0.038*)

0.70(<0.001***)0.22 (0.012*)

0.015(<0.001***)
0.016(<0.001***)0.0011(0.001***)0.0012 (0.011*)

0.0121(<0.001***)0.0079 (0.011*)

0.0056 (0.017*)-0.024(<0.001***)-0.020(<0.001***)-0.016(<0.001***)-0.025(<0.001***)-0.0011(0.003**)-0.0018(<0.001***)-6.7e-4(0.049*)-0.0011(0.0085**)-0.018(<0.001***)-0.015(<0.001***)-0.011(<0.001***)-0.021(<0.001***)-0.015(<0.001***)-0.0087(<0.001***)-0.003 (0.091)

Surprise-0.0046 (0.13)-8.5e-4 (0.065)-0.0043 (0.15)-0.0037 (0.22)

Fear-0.0015 (0.11)-4.5e-5 (0.75)-0.0049(<0.001***)-0.0036(0.0033**)

Simpleeffects of
distance

Sad
Anger
DisgustDisappointment
SurpriseFear

0.075 (0.005**)
0.048 (0.066)
0.046 (0.091)

0.12 (0.36)
0.54(<0.001***)0.14 (0.13)

RewardSensitivities
Happy
Content
Sad
Anger
DisgustDisappointment

0.0014 (0.641)-0.0062(0.024*)

Psychological distance in emotion attribution 39
Table S1: Table of regression coefficients, with p-values in parentheses. We havepresented the table to facilitate comparison across studies and emotions: The top half ofthe table contains the coefficients for the simple effect of distance (at PE=0). The bottom
half of the table contains the coefficients for reward sensitivity across psychologicaldistance (interaction of distance with PE). The contrasts are always in a direction taking
the Self (Now) as a reference point; hence the coefficients should be interpreted as theeffect of increasing distance. The three-way interactions for Study 3 are omitted forclarity. (* p<.05, ** p<.01, *** p<.001)
Comparing Study 1 to Study 2. The coefficients for Study 1 given in Table S1 are forthe “Other – Self” contrast. The coefficients for Study 2 are for 1 unit of ‘distance’, which
we operationalized as answering differently 1, 3, 5, 7, or 9 personality questions, out of
10 questions. This forms a “distance scale”, and we treated social distance as linearly
increasing with number of personality questions answered differently (see Study 2
Methods). The “Self” and “Other” conditions from Study 1 should map somewhere onto
this scale, although their exact positions are still an open research question. A possible
assumption is that “Self” is somewhat close to a target answering 0 questions out of 10
differently from the participant (i.e., the target answered all 10 questions similarly), and arandom “Other” is somewhat close to a target answering 10 questions out of 10
differently. Thus the Study 1 “Other – Self” contrast might roughly be equal to 10 unitsof Study 2 “distance”. Under this assumption, we should, on average, observe that thecoefficients for Study 1 are an order of magnitude larger (i.e., ten times larger) than thecoefficients for Study 2. Indeed, this is generally the case, especially for the interactions
with PE. We note that the simple distance results for Study 2 lose significance for most of
the emotions. We believe that some loss of power might be expected due to the weakersocial distance manipulation in Study 2, although we also think that the pattern of resultsPsychological distance in emotion attribution 40
should be interpreted across the multiple emotions and the multiple studies, rather thanrelying on individual significance values.
Comparing Study 1 to Study 3. We might have expected that the coefficients on Social
Distance in Study 3 should be about the same magnitude as that for Study 1 as they bothcontain an “Other – Self” contrast. Note, however, that the models for the two studies are
not identical, as the models for Study 3 include the effects of temporal distance as well:thus, the “social distance” coefficients roughly capture the (Other,Now – Self,Now) and(Other,Future – Self,Future) contrasts. Nonetheless, the two studies are in theory
measuring the same phenomenon (effect of comparison across social distance), and so weshould expect to see coefficients of comparable magnitude. Indeed, the coefficients forthe negative emotions are very similar numerically across Study 1 and Study 3, although
there is weaker agreement for the positive emotions.
Comparing within Study 3. Finally, one might compare the coefficients for Study 3
across the social and temporal conditions. As mentioned in the main text, the magnitudesof the coefficients for the temporal condition are generally smaller than the corresponding
coefficients for the social condition. This suggests that in our paradigm, the effect of the“Future-Now” manipulation is weaker than the effect of the “Other-Self” manipulation.
We discuss this in the main text in the General Discussion.