=Paper=
{{Paper
|id=Vol-3405/paper8
|storemode=property
|title=What drives gamer toxicity? Essays from players
|pdfUrl=https://ceur-ws.org/Vol-3405/paper8.pdf
|volume=Vol-3405
|authors=Bastian Kordyaka, Samuli Laato, Juho Hamari, Tobias Scholz,Björn Niehaves
|dblpUrl=https://dblp.org/rec/conf/gamifin/KordyakaLHSN23
}}
==What drives gamer toxicity? Essays from players ==
https://ceur-ws.org/Vol-3405/paper8.pdf
What drives gamer toxicity? Essays from players
Bastian Kordyaka 1, Samuli Laato 2, 3, Juho Hamari 2, Tobias Scholz 4 and Björn Niehaves 1
1
University of Bremen, Bibliothekstraße 1, 28359 Bremen, Germany
2
Gamification Group, Korkeakoulunkatu 10, 33720 Tampere, Finland
3
University of Turku, Kiinamyllynkatu 13, 20500 Turku, Finland
4
University of Siegen, Adolf-Reichwein-Straße 2a, 57076 Siegen, Germany
Abstract
Negative online behaviors, such as toxicity, continue being issues in several popular multiplayer
online games. Related research suggests that there are individual differences in how players
understand the concept, and that various interconnected variables are relevant in understanding
the emergence of toxicity. To explore this topic further, in this study, we gathered 16 essays
from gamers regarding their experiences of toxicity in online games. Using the Gioia method
for qualitative analysis, we divided the concepts described in the essays broadly into
characteristics related to (1) the socio-technological setting in which the playing takes place;
(2) the stakeholders' individual disposition including personality and player relationships; and
(3) situational drivers, meaning events and actions that transpire during gameplay. As an
important meta-level implication, our findings raise concerns regarding the lack of a universally
shared view on toxicity, which were visible even with the rather homogenous sample of
participants in this study.
Keywords 1
Gamer toxicity, toxic behavior, League of Legends, video games, multiplayer online games
1. Introduction of Tahm Kench’s abilities, which is an indicator
of toxic escalation). Using R (the most important
ability of champions in the game), Fynn teleports
After a long day of work, Fynn comes home,
them both directly behind the enemy turret, killing
takes off their jacket and riles up an old desktop
both players almost instantly (illustrating sincere
computer. They click open the Riot client and start
behavioral toxicity). After this ordeal, Fynn reads
playing League of Legends (one of the most
a new message in the chat. It is the midlaner:
popular eSports titles at the moment). While in the
“fucking donkey”.
matchmaking queue (a pre-game environment to
The above description is a typical example of
decide what champion to play), Fynn envisions
toxicity in League of Legends. Perhaps starting
dominating the game with their favorite
from a misunderstanding or a minor provocation,
champion, Galio, and naturally, Fynn expresses to
team members end up spoiling each other’s game
their teammates intention to pick this champion.
through both in-game actions and messages in the
But oh no - a player from their own team bans
chat. Industry stakeholders as well as academic
Galio x(due to a communicative
researchers have studied this phenomenon
misunderstanding)! Angry, frustrated and
extensively (see, e.g. [5, 7, 24]), and designed
disappointed by this, Fynn starts plotting revenge
various counter measures for curbing such
picking Tahm Kench. When the game starts, Fynn
negative behaviors, including both (1) proactive
levels up top lane Tahm Kench normally, until
measures, such as removing certain interaction
reaching level 6 (reaching a relevant power spike
opportunities or offering players the option to
of champions within the game). Fynn then walks
shield themselves from unwanted actions [28],
to the midlaner (who banned Galio in the
and (2) post hoc measures, such as allowing
matchmaking queue) and eats him up (using one
players to report malicious actors [20, 22].
7th International GamiFIN Conference 2023 (GamiFIN 2023),
April 18-21, 2023, Lapland, Finland
EMAIL: Kordyaka@Uni-bremen.de (A. 1)
ORCID: 0000-0003-3495-6855 (A. 1)
©️ 2023 Copyright for this paper by its authors. Use permitted under Creative
Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
86
Despite these extensive efforts, toxicity remains a systematically observed what are the most
huge challenge in not only multiplayer online pertinent components of drivers of gamer toxicity,
games such as League of Legends, but also and whether there are outstanding fundamental
discussion forums and other online platforms epistemic or ontological differences between the
where people meet each other. A good example of players’ thinking. In order to guide this research
a recent development is the Zero Harm in Comms including data collection and analysis, we thus
project, an industry-driven initiative that seek to propose the following research question (RQ):
develop AI tools among other solutions for
mitigating gamer toxicity2. RQ: What factors from a gamer’s perspective
The first step to solving a problem is lead up to the occurrence of toxicity in multiplayer
accurately defining it. Rooted in theories of online games?
cyberbullying [2–4] and nurtured by newly arisen
technological opportunities to interact with others Through answering the RQ, we demonstrate
in real-time [13], online toxicity (or toxic how gamers perceive the various factors
behavior) is characterized as a prominent, yet still influencing the emergence of toxicity. We also
unresolved challenge in a variety of video games, look at the differences between players in their
such as multiplayer online battle arena games thinking and show that there is subjectivity
(MOBAs). Toxicity is generally understood as an involved in the interpretation of toxic intent.
umbrella term for negative behaviors in These findings have important implications on
multiplayer video games [1]. In contrast to better both academia and industry, such as highlighting
established and understood concepts such as the importance of communication for neglecting
cyberbullying and online harassment, toxicity is false positives in toxic intent interpretation. The
of short duration, non-systematic and fueled by rest of this study is structured as follows. First, we
situational frustration and anger and the high present our research methodology followed up by
levels of real time competition [16]. The toxic the findings. We then discuss the key results and
behavior has various forms of expression such as position our work back to real life situations in
insulting, criticizing, resource stealing, and which gamer toxicity takes place. We conclude
external attribution which are dependent on the the study by discussing the limitations and future
perpetrator’s actions, the players’ subjective research directions.
interpretation of these actions, and the affordances
of the online platform where the interactions take 2. Methodology
place. Within these tensions, toxicity is generally
accepted as negative and the umbrella of toxic
behaviors are associated with decreased positive As a methodological guide for our data
player experience and game atmosphere, and in collection and analysis, we selected the Gioia
method [12]. This method makes a few
the worst cases, enduring toxicity can even affect
players’ mental health [21]. assumptions that are important to clarify. First, the
While previous research has looked at toxicity method assumes that the participants are experts
in various settings and through multiple on the topic, and as such, their views and opinions
theoretical lenses, deriving insights related to are not critically evaluated in the analysis. This is
relationships between social exclusion, and group a distinction over alternative methods (e.g. [8]),
norms [10, 11], the role of social identity [18, 29], where the participants’ views are debated,
team composition [25], measurement instruments challenged and reflected against existing
[15] and many more, it remains unclear to what knowledge bases. In our case, since we were
degree the academic understanding of the concept specifically interested in discovering the
matches with players’ lived experiences and the participants’ views on toxicity, the assumption of
conceptions that gamers have regarding toxicity. participants as knowledgeable agents was
To address this research gap, in this study we sensible. Second, the Gioia method is an inductive
gathered structured essays from gamers, where method, where the data is coded, the codes are
they explain on a deep level how they understand then grouped together, and finally connected to
the emergence of toxicity in online video games. theory-guided aggregate dimensions. Because of
Through the analysis of these essays, we then this streamlined approach, the method has been
called “template-based” and “procedurally
2
Zero Harm in Comms industry research project for mitigating ubisoft-tackling-toxicity-in-games-with-new-project, visited
gamer toxicity: https://www.riotgames.com/en/news/riot-games- January 8, 2022
87
rigorous”, but also criticized for the lack of for research. Those students who did not give
interpretive rigor [23]. In our case, the clear permission were assessed for the course, but not
analysis procedure provided a framework within included in this study. Participants were explained
which we could compare individual differences that declining to partake in the research had no
between the participants. Despite qualitative impact on their grade.
research being inherently interpretive, the Gioia As the content of the course from where we
method helped bring structure and hence collected the essays was designed around
objectivity in the otherwise multi-layered and examples from the game League of Legends, we
iterative sense-making process. Regardless, the suggested the students also use the game as an
analysis process was iterative, and the authors example in their essays, but this was not
debated and refined the data structure multiple mandatory. After collecting the essays and
times through reasoning, interpretation and grading them, the essays which students had given
discussion along with increasing familiarization permission to use in research were anonymized
with the data. Continuing with the Gioia method and shared with the rest of the research team for
[12], we next describe our data collection, analysis. Altogether out of 18 participants, 16
introduce profiles of the research participants, and gave permission to use their responses in research.
describe the analysis process. Half of the students (n=8) were female, and the
age range of participants was between 20-38 (M
2.1. Data collection =26.06, SD = 4.78). All participants were familiar
with video games, were third year students, and
had been exposed to academic definitions of
In order to address our RQ, we collected data toxicity during the university course. All of the 16
from a sample of university students in the form participants also received a passing grade, with no
of written essays (three pages or ~2000 words). signs of plagiarism or computer-generated
The advantages of having a sample of university responses detected in their essays. Students were
students over anonymous samples were the
given the choice to write the essays in either
following. First, as the assignment was evaluated German or English, and we received essays in
and participants were scored based on their both languages.
essays, they had an additional incentive to provide
thoughtful and thorough essays. This is an
important distinction to alternative data collection 2.2. Data analysis
methods such as Prolific or MTurk samples,
where the users are incentivized to simply return The data analysis proceeded following the
passing works as fast and efficiently as possible Gioia method (Gioia et al., 2013) as follows. First,
with emphasis on producing not more than we labeled the essays with a number P1-P16. We
passing quality. Second, the participants of our shared the essays with the research team and
study were exposed to teaching about toxicity, proceeded with familiarizing ourselves with the
which gave them time and tools to conceptualize material by reading the essays. In this step we
the phenomena and potentially also express using made notes of interesting remarks, potential codes
the scientific theories and understanding of the or concepts related to the RQ. Next, we went
topic. Simultaneously this strength could also be through the essays, coding passages that discussed
a limitation, as the teaching the students received a specific concept related to the RQ, such as
related to e.g., the online disinhibition effect could frustration, provocation, social norms, self-
have also guided their thoughts to a more regulation and losing. At this stage we were not
narrowed direction. worried about looking at individual differences,
The instructions for the essays that the students but our concern was on identifying all unique
wrote were as follows. After a lecture on using concepts mentioned in the essays. Some of the
gamification to address toxicity in online codes were not clear, as students did not explain
environments, we asked students to write about their thoughts in a way that could be condensed
their personal experiences and understanding of into a few words or into one. In these cases, we
online toxicity, and to enumerate what they highlighted complete sentences, or in a few cases
thought causes online toxicity. Students were even paragraphs. Altogether, in the first step we
required to write at least three pages and were identified 30+ codes that describe the
asked whether they would provide us the participants’ understanding of gamer toxicity, and
permission to use their responses anonymously factors leading to the emergence of it. The coding
88
process was done by the first author due to a themes of game affordances, game context, social
language barrier, and key quotes were translated norms, and real-world environment.
and shared with the rest of the team.
In the second step of the analysis, continuing 3.1.1. Game affordances
to follow the Gioia method, we grouped the 1st
level concepts together based on similarity to
form 2nd order themes. This was done together by The first theme that showed itself described
affordances of the game located on a level of
the first three authors, who discussed the data
technology design. Specifically, several of the
structure and framework on multiple occasions to
form themes that best describe the data. This participants mentioned manifestations such as the
process was iterative, and the authors adjusted the chat function and pinging during games, where
themes and the grouping multiple times. As an sometimes no clear distinction can be made here
outcome, we ended up with ten 2nd order themes, between normal communication and toxicity. The
which are described in Figure 1. two subsequent passages from P3 and P7 describe
As the third and final step, Gioia et al. (2013) corresponding instantiations:
describes that the authors should take their “It's always a dilemma in ranked games to
choose between more communication by not
findings towards a more theoretical direction and
muting the chat and more toxicity or less toxicity
connect the 2nd order themes to abstract
and worse communication by muting the chat. I
aggregate dimensions. For this step, we looked at
factors related to (1) the setting, meaning things don’t really have an appropriate answer to this
related to the game or platform, social norms or challenge.” (P3).
the real world environment in where players sit “…another challenge is that there is often no
when accessing online content; (2) individual’s consistent use of the ping command, which leads
disposition, meaning things such as personality, to a variety of misunderstandings and ultimately
motivation to play and possible relationships with to irritation and toxicity.” (P7).
other players; and (3) situational drivers,
describing things such as emotions that spark 3.1.2. Game context
during gameplay, in-game events (winning or
losing) and between-players interactions. All ten Another relevant theme here was the game
2nd order themes could be connected to one of context comprising concepts such as the ranked
these three dimensions. game mode and its competitive environment that
had an impact on the likelihood of experiencing
3. Findings toxicity in different roles during gameplay, which
showed itself in statements such as the following:
Through the analysis process of the Gioia “…since the ranked game mode is very
method, we discovered multiple drivers of competitive by nature, the stakes are high as
toxicity, which we ultimately sorted into ten 2nd players invest a lot of time and effort into
order themes and further into three aggregate improving their gameplay and climbing the ranks.
dimensions. As we discuss the emerging themes, This high-pressure environment can lead to
we do so under the three above-mentioned players becoming more toxic.” (P1).
aggregate dimensions. We present some Another relevant notion that emerged were
illustrative passages from the participants’ essays, characteristics of the solo queue game mode,
which was mediated by the present anonymity in
which are direct quotes in case the essay was
written in English, or translations made by the the game.
authors in case the essay was written in German. “In solo-queue players always get frustrated if
they do not get the role they want during the
champ selection process before the games. As a
3.1. The toxic setting consequence, the perpetrate toxicity before the
game has even started.” (P10)
The first aggregate dimension that emerged
was the toxic setting, which sets the boundaries of 3.1.3. Social norms
the game and events within it, and consequently,
also toxicity. This dimension refers to events that
are taking place before playing the game. These References to the social surrounding were
events are rather static, and influenced by the frequent in the essays. This was expected, as
89
gamer toxicity remains an inherently and dimension, but this quote also introduces the idea
holistically social phenomena. In relation to the that real world social and ethical norms are less
theme at hand (the setting where toxicity occurs), relevant, or not relevant at all, in certain online
P11 expressed their thoughts about the social environments. For example, in League of Legends
influence as follows: the developer takes a strong stance in dictating
“That [the online disinhibition effect] what kind of behavior is acceptable in their game,
potentially leads to social and ethical norms being becoming the ultimate arbiter of socially
ignored online. Another important factor is the acceptable behavior in the online environment.
absence of education about online behaviour and Here we noticed that some participants were
communication.” (P11) against the idea that platform owners would have
“In my own experience the lack of such power over people (P3, P7), while others felt
consequences for toxic behavior is a sincere that it was necessary for the developer to take a
problem that can be even considered an accepted stance and interfere with toxicity, even more
part of the game related culture.” (P12) strongly than what they do currently (P2, P13).
The communication here refers to phenomena
discussed further in the third aggregate
Figure 1: The results of the qualitative analysis encouraged by Gioia et al. (2013)
physical world (such as network latency issues,
3.1.4. Real world environment lighting of the room, interference by roommates)
can translate into emotions and actions that
players experience in the online environment. In
Furthermore, the dimension encapsulates the the essays participants discussed various ways
real-world environment. As people go online, they consider the environment before playing, to
they are still simultaneously present in the
reduce interruptions that may lead to toxicity, but
physical world, and events happening in the
90
to also provide them with the adequate tools to personality that players carry with them to games,
deal with toxicity if it were to arise during a and which are not subject to change in the short
match. For example, P7 and P 14 wrote the term. Related to this theme a substantial part of
following: participants wrote about the influence of the
“During matchmaking I always use a process personality of players affecting toxicity as P10
consisting of three steps: first, I make sure to pick and P14 stated:
a suitable champion in relation to the opponent “Players have different personality
and the own team; second, I make sure I have the characteristics that hurt or make other players
right runes selected; third, I select the mad. As an example, if you are a very extroverted
appropriate summoner spells.” (P7) person this might increase the likelihood of
“…before every game session I mute my phone portraying toxicity during games.” (P10)
to make sure I don’t get interrupted.“ (P14). “Some players just lack resiliency to deal with
Another example comes from P1, who wrote challenging moments of conflicts during games,
about how they prepare for games by checking which oftentimes leads to toxic behavior.” (P14)
their settings:
“To avoid the problem [of having to endure 3.2.3. Social relationships
toxicity], I make sure that my chat- and ping
settings are accurate in relation to if I play normal
Furthermore, social relationships occurred as
or ranked.” (P1)
another relevant concept that occurred.
Accordingly, participants mentioned that social
3.2. Individual pre-dispositions that relationships are one relevant predisposition as
guide actions and reactions well, regarding the likelihood of the occurrence of
toxicity and the potential to deal with negative
The second aggregate dimension that emerged situations. Interestingly, some even stated that
were individual pre-dispositions that guide player they experienced higher levels of toxicity playing
actions and reactions during games that may lead with friends (opposed to strangers):
to toxicity. In accordance with the first dimension, “As I played these games with my friends, we
events are rather static, and influenced by the steadily improved and with that my ambition
themes of playing motivation, personality, and grew. In this situation and similar situations, it is
social relationships. easier to be toxic, as you know the other players.”
(P15)
However, we found the complementary
3.2.1. Playing motivation relationship in our data as well:
“One of my former boyfriends introduced me
The first theme, playing motivation, that had to the game and we played hundreds of hours in
an impact on the likelihood of experiencing duo queue together. Since I knew him quite well,
toxicity in different roles during gameplay, which it was much easier to avoid misunderstandings in
showed itself in statements such as the following: the game and it happened very rarely one of use
“The motivation before a game is a complex carried out toxic perpetration.” (P16)
topic but definitely has an influence how sensitive
I will react in relation to situations that drive me 3.3. Situational factors triggering
mad.” (P13).
“During the end of every season I want to toxicity
improve my Elo level. As a consequence, my
motivation is much more achievement related and The third aggregated dimension, situational
I react to losses much more sensitive, which factors, referred to events that happen during the
(probably) shows in my own toxicity game. These events were highly dynamic and
perpetration.” (P5) comprised the 2nd order themes in game events,
emotions, and perceived interactions.
3.2.2. Personality
3.3.1. In-game events
The second theme, players’ individual
predispositions, described a rather static pre-given Multiple participants expressed in their essays
characteristics of individuals such as their how frustrating in-game events such as losing a
91
match, dying, others not following could simply be the result of the team losing
communication or being provoked by the enemy (which happens roughly 50% of the time). The
team were often the catalysts for toxicity. As a participants also talked about insulting, a specific
rationale, participants stated that players feel form of toxicity, which was one of the most often
greater pressure to perform and can become mentioned expressions of toxicity. The following
frustrated when their team does not perform as two quotes highlights this:
well as they would like due to events during the “Another well-known way of Insulting is
game, which can lead to higher levels of toxicity (obviously) insulting the enemy team if they killed
in communication between players, such as someone or won the game itself or even if one of
blaming others for mistakes. the enemies or the whole team got outplayed in an
“The sad thing about ranked games in League unexpected way” (P8).
of Legends is that the outcome often depends on “What really drives me mad is behavioral
just a few key moments. For example, a baron toxicity I experience during gameplay such as if
fight after 30 minutes is often game-changing. others steal my experience by stealing camps in
Accordingly, it's hard to understand why players my jungle.” P3
don't listen to communication when preparing the
target, but just farm somewhere on the map.” (P9) 4. Discussion
“As a top laner it is really annoying if you have
three AP champions on your team and the 4.1. Key findings
opponent still buys lots of armor. As a
consequence, you’re pretty useless then and need Through our analysis of student essays from a
to burn off some steam.” P12 rather homogenous sample of gamers (n=16) we
identified ten 2nd order themes that are relevant
3.3.2. Emotions in the emergence of toxicity in online multiplayer
games, which we then connected to three
aggregate dimensions that all show references to
Another important theme that was ubiquitous previous work dealing with toxicity: (1) the
in the essays related to the situational drivers were setting in which toxicity occurs comprising game
players’ emotional states. Triggered by the above- related affordances and game content, social
discussed frustrating in-game events, or possibly norms, and real-world environment [6, 19, 26]; (2)
things that occur offline such as a boyfriend individual dispositions consisting of motivation,
nagging or having poor internet, participants players’ personality, and social relationships [14,
connected the resulting negative sentiment to 17]; and (3) situational drivers such as in-game
triggers of toxicity and subsequent malicious events and interactions that transpire between
actions. The following two quotes’ passages players such as in-game events, emotions, and
illustrate these ideas: interactions [9, 27].
“People get easily frustrated if the game does We now return to the illustrative story
not go how they expected it to go. That happens presented in the Introduction section. In Figure 2,
especially in higher ranked competitive games we show how the initial perpetrator of the story
which can have very long queue times and losing may have banned Galio from Fynn out of (a)
such games multiple times in a row because of malicious intent, (b) simply being clueless
someone else’s (they themself always play regarding the situation, or (c) through another
perfectly!) is frustrating and that frustration can reason which Actor 1 failed to communicate to
turn into anger” (P8) Fynn. The action of banning Galio can be
“The possibilities of spreading toxic behavior interpreted by Fynn (Actor 2) in multiple ways.
via an anonymous account and thus letting out For example, they can give Actor 1 the benefit of
frustration, stress and suppressed feelings are the doubt and assume a positive interpretation of
manifold.” (P4) the action such as that Actor 1 banned Galio as
they were afraid the opposing team would steal it.
3.3.3. Perceived interactions On top of the intention and interpretation, the
actors can choose to suppress or commit to their
Connected to the negative emotions was the impulses for actions. In Figure 2, we show how
idea that toxicity was provoked in some way or the three aggregate dimensions (to which our
another due to interactions during the game. The second order themes, and consequently the 1st
provocation did not have to be intentional and order concepts relate to) can be used to explain
92
this situation. First, we have the setting (e.g., the human interactions and relationships inherently
game and the affordances) that dictates the indicate behavior. Participants agreed that
interactions at a high level. Nested inside this are relationships and personality were critical factors
the actors and their interactions, which are in explaining gamer toxicity. Furthermore, these
impacted by the individual dispositions. There are factors are by large out of the developers’ control,
then the events and situational drivers that meaning that developers need to compensate in
transpire during games, that all ultimately their platform things that are fundamental human
contribute to the actions (toxic or not) that players issues by imposing rules and regulations for fair
take during the game. play and behavior. They also need to reinforce
those rules, which may lead to various issues. For
example, even in our homogenous sample not all
participants agreed on what was toxic and what
was not (see the first dimension). Furthermore,
games such as League of Legends are played
globally, with players coming from various
cultural background and having potentially very
different behavioral expectations and
understandings on what sort of behavior is
Figure 2: Relationships aggregated dimensions
allowed. All these factors combined; this
dimension showcased aspects related to
4.2. Implications for research and individuals’ predisposition and factors prima facie
practice disconnected from the technology platform, that
still need to be accounted for and dealt with by the
developer.
In this study we sought out to better understand
The quotes regarding the third aggregated
drivers of gamer toxicity through an analysis of 16
dimension suggest that players are creative in
essays that provide some added value for research
making use of various affordances in behaving in
and practice. Our purpose was not to produce a
a toxic fashion. For the victims, this is a difficult
new definition, but rather, to map and elucidate
situation as it is almost impossible to shield
the various circumstances that are relevant in the
oneself from all the possible expressions of
emergence of toxicity. Through this approach, we
situational toxicity. Even if the developer
were able to elucidate 10 themes which could be
punishes perpetrators retroactively, many of the
broadly divided into three dimensions.
toxic actions are not necessarily done with
The quotes regarding the first aggregate
malicious intention, hence punishing for such
demonstrate the participants’ lived experiences
behaviors would result in false positives. As
when playing League of Legends, where they are
players learn which malicious actions are
actively preparing themselves for situations where
punished and which are not, they gravitate
toxicity may occur. While participants have some
towards those actions that are not punished. For
leeway in controlling the environment (e.g.,
example, currently we are seeing the chat being
through arranging the offline environment and
heavily regulated in League of Legends, which
tweaking in-game settings), and even on a meta-
has simply moved the toxic expression more and
level selecting which game they play, when
more to the in-game actions.
committing to a match of League of Legends there
Summarizing, through Figure 2, we
are countless of environmental factors that are
demonstrate how the discovered framework can
beyond the participants’ control, such as who
be used to explain the occurrence of toxicity in
happen to be their teammates, what in-game
League of Legends. These findings contribute to
affordances there are and what are the social
the literature on online toxicity [1,5,6,12,13,14] as
norms and expectations of their teammates. Thus,
follows:
while there is personal responsibility involved in
First, the findings suggest that as there is
combating toxicity in terms of the setting where
subjectivity involved in the interpretation of
toxicity takes place, we cannot rule out the
toxicity. To counter this, stakeholders should
influence of other factors such as the game
investigate strategies for improving player
developer.
communication, and to also identify situations in
The given examples in relation the second
which misunderstandings happen in the first place
aggregate dimension highlight how fundamental
(such as Champion selection screen in League of
93
Legends) to break the cycle of toxicity at an early toxicity?” According to our findings, it is the
stage. interplay of the three dimensions a) the game
Second, the findings show that much of the related setting, b) dispositions of players, and c)
factors leading up to toxicity are beyond the situational factors that lead to actions that cause
control of the developer. Furthermore, the current negative emotion and sentiment to other players.
measures of developers (very strict chat rules, Participants in our data emphasized these
interaction disabling, judgement and report dimensions to varying degrees, highlighting
systems), may in fact overcompensate and step individual differences in understanding the
beyond the boundaries of what the developer drivers of toxicity. We encourage future research
should do, interfering with the territory of social addressing gamer toxicity to focus on dimensions
norms and other broader characteristics of culture of drivers of toxicity rather than individual
which arguably should be beyond the control of displays of actions such as swearing, stealing a
individual tech companies. resource or leaving the game.
Third, the findings illustrate that toxicity
occurs in various places throughout even an 6. References
individual match, and to various degrees, and that
the actions and reactions of individuals contribute
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Australia, 2018), 365–372.
4.3. Limitations and future work [2] Ang, R.P. and Goh, D.H. 2010.
Cyberbullying among adolescents: The role
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