=Paper= {{Paper |id=Vol-2890/paper1 |storemode=property |title=Memes to an End: A Look into what makes a Meme Offensive. |pdfUrl=https://ceur-ws.org/Vol-2890/paper1.pdf |volume=Vol-2890 |authors=Yehia Elkhatib,Kieran Hill |dblpUrl=https://dblp.org/rec/conf/www/ElkhatibH21 }} ==Memes to an End: A Look into what makes a Meme Offensive.== https://ceur-ws.org/Vol-2890/paper1.pdf

Memes to an End: A Look into what makes a
Meme Offensive?

Yehia Elkhatib1,2[0000−0003−4639−436X] and Kieran Hill1
1
School of Computing and Communications, Lancaster University, UK
mail@kieranhill.xyz
2
School of Computing Science, University of Glasgow, UK
{firstname.lastname}@glasgow.ac.uk

Abstract. Using memes is a popular method of online communication,
including both lighthearted and dark humor as well as polarizing sub-
jects. But what makes a meme offensive? Does this depend on a meme’s
content or format? Does a meme offensiveness vary across audiences? In
order to answer these questions, we recruit 316 participants to score two
sets of meme variants in terms of their offensiveness. We augment this
with interviews to extract additional insights.

Keywords: Memes · Internet meme · Offending content · Online abuse
· Media consumption · Social medium

1 Introduction
An Internet meme (or just meme) is a multimodal medium of communicating
a certain message using the juxtaposition of textual and visual formats. This
commonly takes the form of a brief comment over an image referencing pop
culture, politics, or social issues. An example of a meme is shown in Figure 1.
Memes have been very widely used in social media of various types and in
innumerable languages [1]. The use of memes has helped accelerate the formation
and evolution of Internet subcultures of different types; cf. [3].
Anecdotally, memes are quite efficient at delivering a complex message in a
succinct way. Generally, this is due to the mix of text and visual content (in
image or video format), which allows for almost immediate portrayal of context
and illustration of contrast. This also allows low-effort embedding into trending
phenomena, as well as crossing cultural and language barriers.
The significant role of memes in modern online culture and society in general
is well documented [3,4,21]. We are interested in the common use of memes by In-
ternet subcultures that exhibit counter-cultural, abusive or hate attitudes, such
as far-right subreddits and politically incorrect 4chan boards. Given such promi-
nent use in social media where it is easily exploited to spread misinformation [24]
?
Copyright c 2021 for this paper by its authors. Use permitted under Creative Com-
mons License Attribution 4.0 International (CC BY 4.0). Presented at the MISINFO
2021 Workshop, held in conjunction with the 30th ACM The Web Conference, 2021,
in Ljubljana, Slovenia.
2 Elkhatib and Hill

Fig. 1. An example of a meme.

even mobilizing voters [11,20], we are motivated to identify the characteristics of
a meme that enables it to deliver a potentially inflammatory or offensive point
of view. We are also motivated to investigate how this varies across audiences of
varied demographics.
We carry out a randomized controlled trial to answer the above questions. We
recruit a total of 316 participants to review two different groups of potentially
offensive memes, and ask them to quantitatively score their reaction towards
them. We also invite them to provide qualitative feedback. Consequently, we
are able to draw some fundamental insights into the nature of memes. This
is the first study of its kind to try to isolate, using mixed methods analysis,
the characteristics of a meme that makes it palatable or offensive to different
audiences.
In the remainder of this paper we will be using politically incorrect and
potentially inflammatory language as and when context dictates. Section 2 briefly
surveys related work. Section 3 describes our methodology for collecting memes,
recruiting participants, and designing the survey. Section 4 presents the results of
our study. Section 5 reflects on the results and discusses their wider implications.
Section 6 concludes and outlines future work.

2 Related Work
Memes play a significant role in modern online culture [3,4,21] and indeed in
society at large. For instance, several studies have looked into the effect of memes
on the rhetoric and voter mobilization of alt-right political groups during the
2016 US Presidential Election [10,20,11,14,18].
Memes to an End: A Look into what makes a Meme Offensive 3

Various works have been published on the spread of memes in online me-
dia. Shifman [22] studied features that help a creative derivative culture around
YouTube memes. Guadagno et al. [9] analyzed emotional response to memes and
what contributes to one going viral, while Huntington [12] looked into a meme’s
persuasiveness and effect on online political engagement. Neither study inves-
tigated a meme’s potential to cause offense. Zannettou et al. [27] followed the
spread of memes across online platforms, and observed the popularity of memes
in racist online forums and fringe Internet subcultures. Johann and Bülow [13]
investigated reasons for uptake in meme use, and attributed success to adoption
by journalists. They also highlighted how novelty of meme derivatives through
image editing increases diffusion. Lonnberg et al. [15] built models of meme
spread, incorporating the users who help it spread and their willingness to do
so. Other studies focused on developing methods to automatically recognize
memes [2,19,23].
Yoon [26] found deep rooted racist tendencies in using memes, using color-
blindness as pretext without acknowledging the adverse effects of the implied
racist message. Williams and Dupuis [24] used memes to study the correlation
between political affiliation and levels of personal openness and dispositional
affects.
Despite all of this interest, however, our work is the first (trial or observa-
tional) to dive into why some memes could be more offensive than others.

3 Methodology

We utilized a set of ‘real’ memes collected from Reddit, and complemented them
with synthesized ones in order to vary a certain feature of the meme whilst con-
trolling the others. We designed a survey to collect data on perceived emotions
from a large number of user of different backgrounds.

3.1 Meme collection and creation

We collected a set of memes from the /r/ImGoingToHellForThis subreddit
where offensive content is typically posted. The memes, collected in November-
December 2019, covered a variety of sensitive subjects such as politics, religion,
and race. We attempted to select a variety of meme formats to appeal to different
audiences. However, we aimed not to choose memes that are highly topical in
order to minimize the effect of context or trendiness on meme perception.
We focus in this study on the two main features that constitute a meme: im-
age format and textual message. In order to identify the degree to which each
can play on perception of offense, we vary one while keeping the other the same
as in the original meme collected from Reddit. We used MemeGenerator.com
to alter either the format or text to include in the survey variants. When text
is changed, a message from another /r/ImGoingToHellForThis meme is used.
Examples are shown in Figures 2–3, with the full list included in Table 1. All
memes could be accessed at https://github.com/kieranhill97/Memeology/.
4 Elkhatib and Hill

Table 1. A summary of the memes used in each of the survey sets as well as the themes
they discuss.

Survey A Survey B
Q# Meme Theme Meme Theme
I’m kind of I’m kind of
1 Social niceties Web culture
retarded retarded
2 Pro gamer move Atomic bombings Pro gamer move Murder, Gaming
Infidelity, Domestic
3 Keep your secrets Keep your secrets Abandonment
abuse
4 Starter packs Sexuality Starter packs Race
Star Wars good vs
5 Daily struggle Death, Parenthood Death, Parenthood
evil
Xbox Series X Xbox Series X
6 Religion 9/11
Parodies Parodies
African kid crying
7 Crying woman Disability, Poverty Disability, Poverty
with a knife
Assassination Assassination
8 Troll quotes Troll quotes
(Lincoln) (Kennedy)
I worry about you
Batman slapping
9 Poverty sometimes, Poverty
Robin
Candice
10 I am speed Suicide I am speed Race
I don’t want any I don’t want any
11 Disability (child) Disability (sibling)
damn vegetables damn vegetables
Atomic bombings,
12 Plants vs Zombies Atomic bombings Rice Krispies
Race
13 She can’t do that Gender, Religion She can’t do that Gender, Trump
When Your
Parents Ask
14 Roll safe Death Death
Where All Your
Money Went
What’s funnier What’s funnier
15 Nazism 9/11
than 24 than 24
16 Careful, he’s a hero Gender Careful, he’s a hero Race, Murder
17 Daily struggle Slavery Daily struggle Murder, Cancer
Woman yelling at
18 Gender Who would win Gender
a cat
19 Nut button Terrorism Highway exit turn Terrorism
20 Surprised Pikachu Terrorism Surprised Pikachu Abuse
Memes to an End: A Look into what makes a Meme Offensive 5

Fig. 2. The meme in Q2 where the text is modified, but the format remains the same.

Fig. 3. The memes in Q7 where the format is modified, but the text remains unchanged.

3.2 Survey design

We used a survey questionnaire as the tool to collect input specifically due to
its inherent nature of disconnecting the participant from the researcher and
also from other participants (as in a focus group). The aim was to help the
participants answer freely without feeling implicit pressure to select a politically
correct answer when faced with a polarizing topic.
The survey had 2 variants, each with 20 memes. The size was calibrated to
sustain participant interest throughout the survey and elicit earnest responses.
Upon start, each participant was assigned one of the 2 sets based on a simple
round robin protocol. The corresponding questions in each survey matched each
other in either visual format or textual content. Variation was made between
sets to identify the characteristic of the meme that has potential to cause more
6 Elkhatib and Hill

offense. Each question asked the participants how offended the meme made them
feel on a 5-point Likert scale between ‘Not offensive at all’ and ‘Extremely of-
fensive’. Subjects were informed at the beginning of the survey that the study
was intended to offend and that the memes do not represent the views of the
researchers. The survey was IRB approved.
At the end of the survey, participants were asked to indicate if they are willing
to answer follow-up open-ended questions.

3.3 Participant recruitment
Between February 23rd and 26th 2020, different social media (namely Reddit,
Facebook, and Twitter) were used to spread the survey in an attempt to make
the group of participants as diverse as possible in terms of online culture. We
also recruited locally on our university campus. Demographic information was
collected for summary statistics but all responses were anonymized.
Participation was limited to a single response linked to a Google account
in order to prevent multiple responses from skewing the data. This restriction
limited participation to those with a Google account and were willing to use
it to sign in. There were 550 visits to the survey landing page, 320 of which
completed the survey (a response rate of 57.5%). 4 results had to be disregarded
due to incomplete data, resulting in 316 valid responses. Of these, 37 participants
provided further input in the form of answers to our open-ended questions.

4 Result Analysis
In this section we present and examine the results of the study.

4.1 Participant demographics
First, we inspect how our round robin assignment of survey affected the partici-
pant demographics of each survey set. This resulted in fairly equivalent sets, as
is depicted in Figures 4–5. The only observable disparity is in the frequency of
meme usage, but the difference is not statistically significant.

Fig. 4. Demographics of the participants over the two randomly assigned surveys.
Memes to an End: A Look into what makes a Meme Offensive 7

Fig. 5. Behavior and attitudes towards memes as self-reported by the participants.

Fig. 6. A comparison of the aggregated response scores of the two survey sets.

4.2 Overall comparison

To systematically identify the difference in scores between corresponding ques-
tions of the two surveys (shown in Figure 6), we used the t-test and Mann-
Whitney-Wilcoxon methods. Both are non-parametric and produce statistically
significant results [25]. We found the results of the t-test to be a little more
sensitive to differences in survey scores (Figure 7). This method identified the
following questions as those with highly significant differences across surveys
(p < 0.01): Q3, Q6, Q9, Q12, Q13, and Q17. Furthermore, the ones with signifi-
cant differences (0.01 < p < 0.05) were identified as: Q2, Q5, and Q10. We now
discuss our observations that account for these differences.

4.3 Form vs. substance

Participant response seems to be associated with the message of a meme more
than with its visual aspects. This can be particularly observed in Q7, Q8, Q11,
8 Elkhatib and Hill

Fig. 7. Violin plots of the collected responses, color-coded in how different they are
between surveys. Red indicates significant divergence between the results of the two
surveys, followed in order by orange, yellow, and blue which marks insignificant diver-
gence.

Q18 and Q19 where the message was constant while the meme changed. Ex-
ceptions are Q5, Q9, and Q14, which can be attributed to slightly awkward
meme use when the same message was retained without adjustment while the
meme changed. In effect, the framing in most cases seems less effective than the
content.
Similarly, this is also observed in instances where the meme is reused with a
different message (such as Q3, Q13, and Q17) where it can be significantly more
or less offensive depending on the content. Interestingly, though, 86% of those
interviewed after the survey provided input that agreed with the statement “the
format of a meme can change its meaning”, which is contrary to what the data
shows us.

4.4 Theme matters

The theme of tragic events, especially large-scale ones (e.g., the atomic bombings
of Hiroshima and Nagasaki) are consistently received as being more offensive.
This is evident from the significant changes in Q2, Q6, Q12, and from the lack
thereof in Q15 where both themes were large-scale tragic events (The Holocaust
and 9/11, respectively). Moreover, combining more than one offensive theme
tends to garner higher scores signaling higher level of perceived offense. Examples
include Q3 and Q12. An exception is Q17 where the theme of slavery was more
offensive than murder and cancer combined.
Some themes were deemed to be less offensive than expected, such as religion.
However, we avoid to draw any conclusion on this as we did not collect nor control
for participants’ religious and spiritual beliefs.

4.5 The demographic effect

We observed some associations between participant demographics and response
to memes. Although no extremely strong correlations were detected, a few de-
serve remark (Figure 8). Most obvious, perhaps, is that age is a fairly good
indicator of the frequency of meme use. A stronger correlation, however, exists
Memes to an End: A Look into what makes a Meme Offensive 9

Fig. 8. Pearson correlation coefficient (r) between participant demographics and the
magnitude and variability of their responses.

between a participant’s gender3 and how easily offended they are by the memes.
Moreover, gender is also moderately correlated to varying Likert scores using
median absolute deviation, a robust measure of variability. Essentially, female
participants were more likely to use the full range of the Likert scale over the
various survey questions, while many male participants tended to score using
only part of the scale, e.g., between 1 and 3. Non-binary gender participants
showed no distinguishable tendency. Elsewhere, participants who signified that
they are easily offended did indeed score higher and with more variability. Fi-
nally, participant location showed no significant correlation with scores.

5 Discussion

We now discuss the implications and limitations of the above results, and com-
ment on threats to validity.

5.1 Automated analysis of meme effect

Based on our findings in Section 4.3, the automated detection of potential offense
and, similarly, misinformation in memes might be easier than anticipated as
it is more dependent on the textual rather than visual elements of a meme.
Fortunately, textual analysis methods are more advanced and readily available
3
After removing those who withheld their gender (7), but keeping non-binary answers.
10 Elkhatib and Hill

than visual ones. Thus, we propose the development of systems to predict the
effect of a meme in terms of its offense as an important future direction. This
would be useful for detecting misinformation as well as commercial uses such
as advertising campaigns. Most efforts to date on automated analysis of memes
have focused on distribution, identification and clustering [8,27,7].

5.2 A meme as a humorous Trojan Horse
Some attribute the success of memes to its reliance on humor as a tool, which
allows its creator to ‘soften the blow’ of the contained message [17]. This is
certainly true for political use; Miltner comments that “the humorous nature of
memes [. . . ] makes them an ideal venue for political critique and commentary”
[17]. This is one reason why memes tend to be quite common in online political
culture [16,20,5,18,6].
This inherent property has the potential to be exploited to mask the offen-
sive disposition of the message, or equally political critique or misrepresented
information within. In other words, using memes makes it slightly more eas-
ier to ‘swallow the pill’ of a message that is otherwise less palatable due to its
offensive or misleading character.
However, there seems to be a limit to this capacity to subvert. Our results are
encouraging as they indicate that it is more difficult to dress a overtly offensive
message with the humorous visual elements of a meme. More work is needed to
investigate if this also applies to other emotions that a meme can trigger, and
the potential to carry misinformation.

5.3 Threats to validity
In our study, we do not aim to establish any causal relationships hence threats
to internal validity are minimal. Survey results are susceptible to be swayed by
any biases that the participants already have. This aspect is difficult to control
in an anonymous online survey without an additional step to calibrate perspec-
tives, and by significantly increasing sample size. Although we comment on the
correlations we observe, we are cautious not to generalize in order to mitigate
threats to external validity.
There are some threats to construct validity due to the nature of how memes
are created, and we did notice this effect with a few memes (see Section 4).
Furthermore, memes seldom live in isolation and are typically part of a wider
discussion that is context- and community-specific. As such, there will always
be a degree of threat to construct validity with synthesizing memes purely for
research purposes.

6 Conclusion and Future Work
Through a randomized controlled trial, we studied how different memes are re-
ceived as being offensive or otherwise. We established an understanding of the
Memes to an End: A Look into what makes a Meme Offensive 11

importance of a meme’s content as opposed to just its visual and cultural aspects.
We also uncovered some relationships between user demographics and how likely
they are to being offended by a meme. As such, our work helps address a gap in
terms of how sensitive or polarizing messages could be interpreted by different
audiences. This knowledge is important not just in understanding how the po-
tential of propagating certain messages through the medium of memes, but also
how controversial opinions (due to political, racial, religious, etc. perspectives)
can have varied effects. We also discussed the degree to which a meme could be
used as a delivery vehicle to normalize what is arguably controversial, extreme,
or misleading. However, this area requires more research which is a future target
of ours.
There are numerous other directions for future work. Further investigation
could be made into the relationship between the timeliness of a meme and its
offense effect. How this may vary across topics, online communities, and social
platforms are all interesting question. Another interesting direction is to inves-
tigate the possible dependency of the ‘memorability’ of a meme and its inherent
properties.

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