Content uploaded by Maciej Behnke
Author content
All content in this area was uploaded by Maciej Behnke on Dec 28, 2020
Content may be subject to copyright.
Emotions and gaming 1
© 2020, Elsevier. This paper is not the copy of record and may not exactly replicate the final, authoritative
1
version of the article. Please do not copy or cite without authors' permission. This manuscript version is
2
made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
3
The final article will be available, upon publication, via its DOI:
4
https://doi.org/10.1016/j.entcom.2020.100397
5
Emotions and gaming 2
RUNNING HEAD: Emotions and gaming
6
7
What makes male gamers angry, sad, amused, and enthusiastic while playing violent video
8
games?
9
10
Maciej Behnke1, Patrycja Chwiłkowska1, Lukasz D. Kaczmarek1
11
1Faculty of Psychology and Cognitive Science, Adam Mickiewicz University
12
13
Author Notes
14
Correspondence concerning this article should be addressed to Maciej Behnke, Faculty of
15
Psychology and Cognitive Science. Adam Mickiewicz University, 89 Szamarzewskiego Street,
16
60-658 Poznań, Poland. E-mail: macbeh@amu.edu.pl
17
CRediT author statement: Maciej Behnke: Conceptualization; Data curation; Formal
18
analysis; Investigation; Methodology; Project administration; Writing - original draft; Writing -
19
review & editing; Patrycja Chwiłkowska: Data curation; Formal analysis; Writing - review &
20
editing; Lukasz D. Kaczmarek: Conceptualization; Formal analysis; Methodology; Supervision;
21
Writing - review & editing. All authors had full access to all data in the study and take
22
responsibility for the integrity of the data and the accuracy of the data analysis.
23
Funding sources: This research did not receive any specific grant from funding agencies
24
in the public, commercial, or not-for-profit sectors. This article's preparation was supported by
25
doctoral scholarships from the National Science Centre in Poland (UMO-2019/32/T/HS6/00039)
26
and Adam Mickiewicz University Foundation to MB.
27
28
Emotions and gaming 3
Abstract
29
Gaming elicits strong emotional responses. However, little is known about which situations
30
within the gameplay elicit specific emotions. Thus, we aimed to identify which gaming situations
31
elicit positive and negative emotions. We asked Counter-Strike: Global Offensive gamers (N =
32
652) to recall and write about a situation when they felt amused, angry, enthusiastic, or sad. In
33
our analysis, we used semantic coding and affective words analysis using Linguistic Inquiry and
34
Word Count (LIWC). We found that gamers described emotional situations (e.g., clutch, victory,
35
or hacking) that we clustered into 12 broader categories (e.g., positive performance outcomes,
36
underperforming, and technical issues). Gamers reported similar (rather than specific) situations
37
for anger and sadness and similar for amusement and enthusiasm. We documented a wider than
38
usually considered range of positive and negative emotions related to gaming along with specific
39
gaming themes that produce these emotions. These findings contribute to a broader and more
40
specific (events-based) understanding of the emotional aspects of video gaming.
41
Keywords: video games, positive emotions, negative emotions, LIWC
42
Emotions and gaming 4
Highlights:
43
• We identified which gaming events produce anger, sadness, amusement, and enthusiasm.
44
• Semantic coding and affective words analysis documented the validity of identified
45
events.
46
• These findings can be used by game developers to make informed decisions regarding
47
emotions elicited by their games
48
49
Emotions and gaming 5
1. Introduction
50
Gaming offers diverse emotional experiences ranging from intense positive emotions (e.g.,
51
amusement) to intense negative emotions (e.g., anger)[1]. However, research on gaming and
52
emotions has been biased towards the negative consequences of playing videogames [2]. Studies
53
have identified the game-design as one factor that elicits strong negative emotions [3,4,5,6]. For
54
instance, the game's violent content (e.g., graphic presentation of death) is associated with
55
increased emotional arousal observed at physiological and subjective level [3,4,5]. Whereas the
56
darkness, presence of disfigured humans, and zombies are the most common stimuli eliciting fear
57
while gaming [6]. Furthermore, studies identified specific gaming behaviors that elicit negative
58
emotions such as poor communication, criticism within the team, underperforming, and losing
59
matches that were expected to win [7, 8].
60
More recently, studies have started to emphasize the positive influences of video gaming
61
on human emotional experience [9]. For instance, playing some videogames make gamers happier,
62
less distressed, and less frustrated [10,11]. Gamers identified that making progress and successful
63
performances elicit positive emotions [12]. Even playing violent games has the potential to increase
64
positive emotions [1,13]. Gamers indicated that playing against 'evil' elicit positive emotions [14].
65
Although the emotions elicited by gaming situations might seem intuitive, studies on the emotional
66
experience of playing first-person shooter games show its complexity. For instance, wounding and
67
killing an opponent causes an increase of positive emotions that could result from the game's
68
progress [15] but also leads to an increase of negative emotions like fear and anger that could result
69
from shooting the rivals [16]. Similarly, wounding or killing one's character (a negative event in
70
the game) leads to positive emotions that could result from alleviating the stress associated with
71
playing [1], but also leads to negative emotions that could result from the game's failure [15].
72
Emotions and gaming 6
Despite the growing body of research on video-gaming emotional consequences, little is
73
known what scripts or specific in-game triggers elicit specific positive and negative emotions.
74
Establishing a link between the behavioral content of gaming and specific affective outcomes is
75
important to make informed decisions regarding the game use, game development, and treatment
76
of gamers that exhibit problematic gaming patterns. For instance, in anger management therapy
77
for gamers, practitioners might use the list of gaming situations that cause problematic behavior,
78
such as rage-quitting - the act of disconnecting gaming equipment, sometimes violently [17].
79
Furthermore, gamers and their coaches might use a specific situation to train emotion regulation
80
skills to enhance future performance. Finding new methods and strategies to facilitate
81
performance is essential in esports. Players often present similar gaming skills, and winning or
82
losing depends on peripheral factors such as emotions [18,19].To address these problems, we
83
aimed to examine what behavioral scripts gamers associate with specific emotions using semantic
84
coding. Furthermore, we investigated the descriptions of emotional experiences with
85
computerized affective language analysis. Thus, our secondary aim was to determine whether
86
gamers would use specific affective language to describe the emotional experiences.
87
In studying emotions, we focused on four types of emotions that resulted from the
88
combination of two dimensions of emotional experience, namely valence and approach-
89
avoidance tendencies [20]. Thus, we targeted amusement (positive affect, low approach
90
tendency), enthusiasm (positive affect, high approach tendency), sadness (negative affect, low
91
approach tendency), and anger (negative affect, high approach tendency). Considering both
92
dimensions of emotional experience – valence and approach-avoidance tendencies - it is not yet
93
clear which one is responsible for affective costs and benefits that gamers reap from gaming. This is
94
not an extensive list of dimensions that characterize emotional experience (e.g., arousal or
95
dominance)[21]. We start with valence because it is the most basic aspect of the emotional
96
Emotions and gaming 7
experience. We contrasted it with the motivational tendency that is a rather novel and not fully
97
investigated dimension that might be crucial in a gaming context. A recent study has shown that
98
approach motivation directly influences gaming performance [22].
99
We expected that the gaming situations' descriptions would fit the core theme of the
100
examined emotions. Amusement would be linked to humorous events that are mostly elicited by
101
events that violate expectations due to others' actions [23]. Enthusiasm would be linked to
102
opportunities for imminent resource acquisition [23]. Anger would be triggered by external
103
factors that may harm (physically or psychologically) something important for an individual and
104
impede the pursuit of a valuable goal [24]. Sadness would be linked to losses of an object or
105
person to which individuals are very attached [24].
106
To study emotional scenarios that were related to gaming, we focused on one of the most
107
popular PEGI 18 games Counter-Strike: Global Offensive (CS:GO). CS:GO is a multiplayer
108
team-based first-person shooter where two teams compete against each other in simulated
109
military combat. CS:GO is one of the leading games in the esports team-play category that
110
engages up to 600,000 daily active players worldwide [25]. In this game, individuals form two
111
teams with opposing motives: counter-terrorists vs. terrorists. The mission of the counter-
112
terrorists is to disarm explosives planted by the terrorists or eliminate all terrorists.
113
2. Material and Methods
114
2.1 Participants
115
Participants were 652 CS:GO players (617 male gamers) in the age between 18 and 39
116
years (M = 20.75, SD = 3.58). Participants reported how many years ago they started to play
117
CS:GO (M = 5.20, SD = 4.19), and how many hours per week they usually played (M = 19.57,
118
SD = 19.81). A power analysis using G*Power 3.1 [26] indicated that detection of expected effect
119
sizes [27] of d = 0.30 for the difference between the conditions, with the power of .80, would
120
Emotions and gaming 8
require a sample size of 536 participants (139 per group). The study was in accordance with the
121
Declaration of Helsinki and ethical guidelines provided by the National Science Centre in Poland.
122
All participants were informed about the study, and all provided signed informed consent.
123
2.2 Procedure
124
Players were recruited via a Facebook advertisement targeted at CS: GO players in
125
English-speaking countries. We created four groups and asked players to recall the moments of
126
enthusiasm (n = 162), amusement (n = 169), sadness (n =146), or anger (n =175) that they
127
experienced during CS:GO playing. Gamers were asked to think about moments of amusement
128
(enthusiasm or sadness or anger) related to playing CS: GO. Furthermore, gamers were asked to
129
think about situations when they felt intensely excited or zealous (enthusiasm), amused or
130
entertained (amusement), sad or miserable (sadness), enraged or angry (anger) during the
131
gameplay. We asked participants to write about one such situation focusing on emotions they felt
132
while gaming.
133
2.3 Open Coding
134
To determine which situations elicited specific emotion, the gaming event descriptions
135
were submitted to open coding. First, two judges coded the situations with keywords, to sum up
136
what participants were sharing. In open coding, the text is coded to find as many codes as
137
possible without considerations of relevance (e.g., "clutch", "hacking", “playing with friends” or
138
“victory”) [28]. The specific events and situations constituted for identification of broader events
139
categories based on their conceptual similarity (e.g., “successful performance”, “performance
140
context”, “underperforming”, and “technical issues”) [28]. Raters assigned the statements to the
141
appropriate categories. The interrater agreement was high (Krippendorff’s α = .84). Finally, the
142
raters resolved disagreements by consensus.
143
2.4 Affective Language Analysis
144
Emotions and gaming 9
Measures of affective expressions were obtained by analyzing text (events descriptions)
145
produced by gamers with Linguistic Inquiry and Word Count (LIWC) [29]. The program counts
146
target words or word stems from an extensive dictionary and categorizes them into linguistic and
147
affective dimensions. The software converts the raw counts to percentages of total words. Several
148
research studies (involving the generation, expression, and regulation of emotions) have shown
149
the validity of the LIWC [27,30]. To determine the characteristic affective style of reported
150
situations, we performed multivariate ANOVAs with emotion categories as the independent
151
variables and 12 LIWC categories as the dependent variables using SPSS 23 (Inc., Chicago,
152
Illinois). Post hoc tests with Bonferroni correction for multiple comparisons were used to
153
determine differences between the conditions. To account for multiple comparisons (e.g., the
154
difference in positive emotions between amusement and enthusiasm, amusement and sadness,
155
amusement and anger), we adjusted probability values using the false discovery rate (FDR)
156
formula [31]. This resulted in adjusting confidence intervals to balance Type I and Type II error.
157
3. Results
158
3.1 Open Coding
159
Participants used from 1 to 229 words (M = 20.04, SD = 27.19) to describe events that
160
elicited emotions during the gameplay. Gamers listed unique 87 situations clustered into 12
161
broader categories (Table 1). Amusing gamers' scenarios were related to performance context,
162
humorous events, positive performance outcomes, successful performance, and underperforming
163
(Table 1). Gamers mostly mentioned victories, skillful kills, winning clutch situations, playing
164
with friends, and ridiculous shots. For enthusiasm, gamers described situations related to their
165
successful performance, positive performance outcomes, performance context, and positive team
166
performance (Table1). The most frequent situations were clutch play (a player wins a round after
167
being the last man standing for their team), victories, and competitive matches.
168
Emotions and gaming 10
Angry scenarios described by gamers were related to negative behaviors of own-team,
169
negative performance outcomes, negative behaviors of rival-team, communication issues,
170
underperforming, and technical issues (Table 1). Gamers pointed out situations such as playing
171
with weak teammates, playing against hackers, someone sabotaging a team-play, internet lagging,
172
losing the match, dying, or teammate throwing a game. Gamers reported sad situations that were
173
related to negative performance outcomes, underperforming, negative behaviors of own-team,
174
negative behaviors rival-team, and communication issues (Table 1). Gamers described losing
175
situations, playing with weak teammates, losing the game that should be won, and
176
underperforming. Sad events were characterized by more expressions related to sadness (e.g.,
177
grief, sad, miserable), risk (e.g., danger, doubt) compared to other conditions.
178
[Table 1 near here]
179
3.2 Affective Language Analysis
180
We found that participants characterized situations related to discrete emotions by using
181
specific affective language, F (36, 1917) = 7.51, p < .001; Pillai’s Trace = 0.37, partial η2 = .12.
182
(Table 2). Because of the significant results of the null hypothesis testing of equality of
183
covariance matrices, Box’s M = 3515.12, F (234, 870444.56) = 14.54, p < .001, we interpreted
184
Pillai’s Trace, not Wilks’ λ. We observed differences between conditions for twelve affective
185
language subcategories (Table 2). Descriptions of amusing situations had a higher percentage of
186
expressions related to positive emotions (e.g., happy, relax, fun, laugh) than for anger conditions
187
and more expressions related to friends (e.g., friend, mates, team) compared to sadness (Table 2).
188
Descriptions of enthusiastic events had the highest percentage of expressions related to
189
achievements (e.g., win, competitive, playing very well, comeback) compared to other conditions
190
(Table 2). Situations related to enthusiasm were described with more positive emotions (e.g.,
191
Emotions and gaming 11
pleasure, happy, amazing, ecstasy) compared to anger and sadness, and more expressions related
192
to power (e.g., kill, fire, hit) compared to anger.
193
The description of the anger-provoking situation was characterized by more expressions
194
of negative emotions (e.g., toxic, weakness, losing), anger (e.g., kick, smash, kill, annoyed, f**k),
195
and social words (e.g., teammate, they, team) compared to enthusiasm (Table 2). Furthermore,
196
situations related to sadness were described with more expressions related to negative emotions
197
(e.g., bad, losing, rude), feelings (e.g., choke, feel), achievements (e.g., better, beat) compared to
198
amusement (Table 2). Sad events were described with more words related to negative emotions
199
compared to enthusiasm, and with more words related to feelings compared to anger.
200
[Table 2 near here]
201
4. Discussion
202
We aimed to identify gaming situations that elicit specific emotions while CS:GO
203
gaming. We found that gamers produced descriptions that were grouped into several unique
204
categories. We identified several core scenarios that are common in generating specific positive
205
and negative emotions among gamers, such as ridiculous shots (amusement), clutching
206
(enthusiasm), playing with weak teammates (anger), or deranking (sadness). Furthermore, we
207
found meaningful differences in affective language used to describe these situations. These
208
findings present a novel perspective on affective experience among gamers.
209
We found that specific gaming scenarios that elicited emotions in gamers fit the core
210
characteristics of targeted emotions. For amusement, gamers reported mindless game mistakes or
211
ridiculous shots during recreational gaming, whereas for enthusiasm, gamers reported successful
212
games in competitive or tournament settings. For anger, gamers often reported unfair situations -
213
hacking, cheating, trolling, smurfing. Finally, gamers reported losing as the most common
214
saddening scenarios. In sum, we found typical situations that elicited amusement, anger,
215
Emotions and gaming 12
enthusiasm, and sadness. Although it is not surprising, we found the replicative part of this
216
research is essential because several analyses indicate that the effects reported in the
217
psychological literature often fail to replicate [32].
218
Furthermore, we applied computerized text analysis to complement semantic coding that
219
examined affective language used to describe gaming situations. In our study, gamers used
220
specific language to characterize different gaming moments. Our findings extend the
221
methodological perspective that language is an effective tool in detecting individuals’ emotional
222
states. We presented that this method is adequate for studying affective experience in video
223
gamers. Future studies might progress with our findings to identify gamers’ emotions from within
224
the game communication between gamers. With new research technologies' maturation, their
225
common use is likely to contribute to more versatile evidence and new research ideas.
226
Although we found several specific situations that elicited targeted emotions, we also found
227
several similar situations that elicited anger and sadness (e.g., underperforming) and enthusiasm
228
and amusement (e.g., successful performance). For both positive emotions, gamers mostly
229
mentioned victories, skillful kills, and good performances such as the clutch play. For both negative
230
emotions, gamers usually described defeating scenarios due to their poor performance, weak
231
teammates, or other gamers' unfair behavior such as hacking. Furthermore, not all affective
232
expressions categories presented expected patterns. For instance, there were no differences
233
between amusement and sadness in positive words or anger and amusement in negative words.
234
These findings are consistent with a constructionist view of emotion [33]. Within a constructionist
235
framework, people construct emotions in their minds based on the similarities and differences in
236
functions and purposes of specific actions. Therefore, affective reactivity is expected to vary within
237
the discrete emotion and overlap with other discrete emotions from person to person. It is not the
238
automatic, inherent response to the stimuli.
239
Emotions and gaming 13
This study has practical implications. We presented situations that elicit specific emotions
240
in CS:GO. Game developers may implement our findings to make games such as CS:GO more
241
emotionally arousing or to streamline the affective experience towards specific emotions. For
242
instance, by targeting a wider range of specific emotions, video games might offer a means to
243
maintain high-quality entertainment. This is particularly important in increased social isolation
244
and deficits in real-world entertainment, such as during the COVID-19 pandemic. Furthermore,
245
gamers and their coaches might use our findings to create pre-performance emotion regulation
246
strategies to enhance future performance. For instance, gamers might create personal clips
247
presenting their best plays to elicit enthusiasm, which is effective tool for esport performance
248
optimization [22]. Finally, our findings might be relevant to practitioners. Using our list,
249
practitioners could target situations within gaming that cause problematic behavior. Practitioners
250
might select specific situations related to problematic emotions and evaluate gamers’ treatment
251
progress when facing these situations.
252
4.1 Limitations and Future Directions
253
This study has several limitations. First, individuals self-selected to participate in our
254
study. Thus, this study is more likely to overrepresent players highly involved in gaming. Second,
255
we examined four emotions accounting for positive-negative and approach-avoidance dimensions
256
of emotional experience. Including additional discrete emotions into the analyses (e.g., pride or
257
fear) would provide a complete repertoire of emotional situations within the gameplay. Future
258
studies may provide evidence, which specific moments make gamers experience pride, gratitude,
259
contentment, or awe. Third, this study included participants from countries where English is the
260
first language, such as the US, UK, or Australia. There are, however, likely cultural differences
261
that might produce different results in participants residing in other countries and using different
262
languages. Fourth, our participants were mostly male gamers. It reflects the situation among first-
263
Emotions and gaming 14
person shooter-type gamers, where the vast majority, up to 93%, are male [34]. Therefore, our
264
results apply to male gamers, whereas future studies might focus on whether the results
265
generalize to female gamers. Female participants might reveal different experiences. Fifth, in this
266
study, we focused only on the single-game context, namely CS: GO gamers. Although CS:GO
267
represents the leading genre in esports competition – first-person shooter genre - future studies
268
may examine whether emotional events are likely to translate well to other competitive games.
269
This would help to identify emotion eliciting general situations for esports (i.e., problems with
270
the computers) and specific situations for the particular games. Finally, we used self-reports
271
while controlling for physiological or behavioral emotional reactions that would have provided
272
further insights into the specific situation that elicit emotional experience.
273
4.2 Conclusion
274
Our research offers novel evidence and a detailed description that playing video games
275
offers a versatile affective experience. With this study, we defocused from negative emotions
276
typically studies in the context of first-person shooter games and extended the scope with positive
277
emotions. We demonstrated that playing CS:GO offers a positive experience from recreational
278
and competitive matches with other players. Using semantic coding and computerized affective
279
text analysis, we found that similarities outweighed the differences within positive and within
280
negative emotions. Gamers reported similar (rather than specific) situations for anger and sadness
281
and similar for amusement and enthusiasm. Our study broadened the understanding of the
282
affective costs and benefits that gamers reap from gaming. Knowing which specific gaming
283
situations elicit specific emotions is important for the gaming community. Our findings may help
284
make informed decisions regarding esport performance optimization and the treatment of
285
problematic gaming behaviors.
286
287
Emotions and gaming 15
5. Disclosure Statement: No potential competing interest was reported by the authors.
288
289
Emotions and gaming 16
6. References:
290
[1] N. Ravaja, M. Turpeinen, T. Saari, S. Puttonen, & L. Keltikangas-Järvinen, The
291
psychophysiology of James Bond: Phasic emotional responses to violent video game
292
events. Emotion, 8 (2008) 114—120. https://doi.org/10.1037/1528-3542.8.1.114
293
[2] T. Greitemeyer, & D.O. Mügge, Video games do affect social outcomes: A meta-analytic
294
review of the effects of violent and prosocial video game play. Personality and Social
295
Psychology Bulletin, 40 (2014) 578-589. https://doi.org/10.1177%2F0146167213520459
296
[3] C.P. Barlett, R.J. Harris, & C. Bruey, The effect of the amount of blood in a violent video
297
game on aggression, hostility, and arousal. Journal of Experimental Social Psychology, 44
298
(2008) 539-546. https://doi.org/10.1016/j.jesp.2007.10.003
299
[4] M.J. Fleming, & D.J. Rick Wood, Effects of violent versus nonviolent video games on
300
children’s arousal, aggressive mood, and positive mood. Journal of Applied Social
301
Psychology, 31 (2001), 2047-2071. https://doi.org/10.1111/j.1559-1816.2001.tb00163.x
302
[5] E.F. Schneider, A. Lang, M. Shin, & S.D. Bradley, Death with a story: How story impacts
303
emotional, motivational, and physiological responses to first-person shooter video
304
games. Human Communication Research, 30 (2004) 361-375.
305
https://doi.org/10.1111/j.1468-2958.2004.tb00736.x
306
[6] T. Lynch, & N. Martins, Nothing to fear? An analysis of college students’ fear experiences
307
with video games. Journal of Broadcasting & Electronic Media, 59 (2015) 298-317.
308
https://doi.org/10.1080/08838151.2015.1029128
309
[7] M. J. Smith, P. D. Birch, & D. Bright, Identifying stressors and coping strategies of elite
310
esports competitors. International Journal of Gaming and Computer-Mediated
311
Simulations, 11 (2019) 22-39. https://doi.org/10.4018/IJGCMS.2019040102
312
Emotions and gaming 17
[8] Y. Kou, & X. Gui, Emotion Regulation in eSports Gaming: A Qualitative Study of League of
313
Legends. Proceedings of the ACM on Human-Computer Interaction, 4 (2020) 1-25.
314
https://doi.org/10.1145/3415229
315
[9] I. Granic, A. Lobel, & R.C. Engels, The benefits of playing video games. American
316
Psychologist, 69 (2014) 66-78. https://psycnet.apa.org/doi/10.1037/a0034857
317
[10] C.V. Russoniello, K. O’Brien, & J.M. Parks, The effectiveness of casual video games in
318
improving mood and decreasing stress. Journal of Cyber Therapy and Rehabilitation, 2
319
(2009) 53-66.
320
[11] J.G. Snodgrass, M.G. Lacy, H.J. Francois Dengah, J. Fagan, & D.E. Most, Magical flight
321
and monstrous stress: technologies of absorption and mental wellness in Azeroth. Culture,
322
Medicine and Psychiatry, 35 (2011) 26-62. https://doi.org/10.1007/s11013-010-9197-4
323
[12] B. Hoffman, & L. Nadelson, Motivational engagement and video gaming: A mixed methods
324
study. Educational Technology Research and Development, 58 (2010). 245-270.
325
https://doi.org/10.1007/s11423-009-9134-9
326
[13] W. Bösche, Violent video games prime both aggressive and positive cognitions. Journal of
327
Media Psychology, 22 (2010) 139-146. https://doi.org/10.1027/1864-1105/a000019
328
[14] M. C. Carras, A. Kalbarczyk, K. Wells, J. Banks, R. Kowert, C. Gillespie, & C. Latkin,
329
Connection, meaning, and distraction: A qualitative study of video game play and mental
330
health recovery in veterans treated for mental and/or behavioral health problems. Social
331
Science & Medicine, 216 (2018).124-132.
332
https://doi.org/10.1016/j.socscimed.2018.08.044
333
[15] M. Shin, R. Heard, C. Suo, & C. M. Chow, Positive emotions associated with “Counter-
334
Strike” game playing. GAMES FOR HEALTH: Research, Development, and Clinical
335
Applications, 1 (2012) 342-347. https://doi.org/10.1089/g4h.2012.0010
336
Emotions and gaming 18
[16] N. Ravaja, T. Saari, M. Salminen, J. Laarni, & K. Kallinen, Phasic emotional reactions to
337
video game events: A psychophysiological investigation. Media Psychology, 8 (2006)
338
343-367. https://doi.org/10.1207/s1532785xmep0804_2
339
[17] J.T. Brook, The Psychology of the Online Shooter (or, Why Someone Might Rage Quit)
340
Retrieved from: https://venturebeat.com/2009/12/18/the-psychology-of-the-online-
341
shooter-or-why-someone-might-rage-quit/, 2009 (accessed 10 July 2020)
342
[18] I. Pedraza-Ramirez, L. Musculus, M. Raab, & S. Laborde, Setting the scientific stage for
343
esports psychology: a systematic review. International Review of Sport and Exercise
344
Psychology, (2020) 1-34. https://doi.org/10.1080/1750984X.2020.1723122
345
[19] M. Behnke, M. Kosakowski, L.D. Kaczmarek, 2020. Social challenge and threat predict
346
performance and cardiovascular responses during competitive video gaming, Psychology
347
of Sport and Exercise, 46, 101548. https://doi.org/10.1016/j.psychsport.2019.101584
348
[20] P. Gable, & E. Harmon-Jones, The motivational dimensional model of affect: Implications
349
for breadth of attention, memory, and cognitive categorisation. Cognition and
350
Emotion, 24 (2010) 322-337. https://doi.org/10.1080/02699930903378305
351
[21] A. S. Cowen, & D. Keltner, (2017). Self-report captures 27 distinct categories of emotion
352
bridged by continuous gradients. Proceedings of the National Academy of
353
Sciences, 114(38), E7900-E7909. https://doi.org/10.1073/pnas.1702247114
354
[22] M. Behnke, J.J. Gross, L.D. Kaczmarek, The Role of Emotions in Esports Performance.
355
Emotion, 2020. https://doi.apa.org/doi/10.1037/emo0000903
356
[23] M.N. Shiota, B. Campos, C. Oveis, M.J. Hertenstein, E. Simon-Thomas, & D. Keltner,
357
Beyond happiness: Building a science of discrete positive emotions. American
358
Psychologist, 72 (2017) 617-643. https://doi.org/10.1037/a0040456
359
Emotions and gaming 19
[24] P. Ekman, & D. Cordaro, What is meant by calling emotions basic. Emotion Review, 3
360
(2011) 364-370. https://doi.org/10.1177%2F1754073911410740
361
[25] SuperData Research, Number of players of selected eSports games worldwide as of August
362
2017. Retrieved from https://www.statista.com/statistics/506923/esports-games-number-
363
players-global/, 2017 (accessed 10 July 2020)
364
[26] F. Faul, E. Erdfelder, A. Buchner, & A.G. Lang, Statistical power analyses using G* Power
365
3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41 (2009)
366
1149-1160. https://doi.org/10.3758/BRM.41.4.1149
367
[27] M. Settanni, & D. Marengo, 2015. Sharing feelings online: studying emotional well-being
368
via automated text analysis of Facebook posts. Frontiers in Psychology, 6, 1045.
369
https://dx.doi.org/10.3389%2Ffpsyg.2015.01045
370
[28] T. Giske, & B.A Artinian, Personal experience of working with classical grounded theory:
371
From beginner to experienced grounded theorist. International Journal of Qualitative
372
Methods, 6 (2007) 67-80. https://doi.org/10.1177%2F160940690700600405
373
[29] J.W. Pennebaker, R.L. Boyd, K. Jordan, & K. Blackburn, 2015. The development and
374
psychometric properties of LIWC2015. Austin, TX: University of Texas at Austin.
375
https://doi.org/10.15781/T29G6Z
376
[30] K. Sylwester, & M. Purver, 2015. Twitter language use reflects psychological differences
377
between democrats and republicans. PloS One, 10, e0137422.
378
https://doi.org/10.1371/journal.pone.0137422
379
[31] Y. Benjamini, & Y. Hochberg, Controlling the false discovery rate: a practical and powerful
380
approach to multiple testing. Journal of the Royal Statistical Society: series B
381
(Methodological), 57 (1995) 289-300.
382
Emotions and gaming 20
[32] Open Science Collaboration, Estimating the reproducibility of psychological
383
science. Science, 349 (2015), 6251. https://doi.org/10.1126/science.aac4716
384
[33] L.F. Barrett, Psychological construction: The Darwinian approach to the science of
385
emotion. Emotion Review, 5 (2013) 379-389.
386
https://doi.org/10.1177%2F1754073913489753
387
[34] N. Yee, The gamer motivation profile: What we learned from 250,000 gamers.
388
In Proceedings of the 2016 Annual Symposium on Computer-Human Interaction in
389
Play, 2016 2-2. https://doi.org/10.1145/2967934.2967937
390
Emotions and gaming 21
Table 1
Emotional Categories, Events and their Frequency
Emotion
Category (Frequency)
Most popular events (Frequency)
Gamers quote
Amusement
Performance context
(37%)
Playing with friends (15%), good communication
(12%), close games (8%), recreational matches (7%),
playing with low ranks (3%), kids yelling (2%)
“When I was playing in a team of 4 with my
friends and one stranger. We were losing by a
significant margin but decided to just have fun
with it, so we joked along with the other player
on our team and just tried to kill people in
funny ways or would all play with a generally
unadvisable strategy. It was funny and
enjoyable/amusing because of how wrong the
game was going but since we disengaged with
trying our hardest to win (we weren’t just
throwing the game, just playing in
unconventional ways) and instead just had a
laugh.”
Humorous events
(36%)
Ridiculous shots (15%), other stupid mistakes (7%),
team-kill (5%), wall bang (2%)
Positive performance
outcomes (35%)
Victory (34%), learning (2%)
Successful
performance (33%)
Skilful kill (18%), clutch (15%), ninja defuse (3%)
Underperforming
(11%)
Defeat (4%), death from falling (4%), whiffing (3%)
Enthusiasm
Successful
performance (71%)
Clutch (45%), skillful performance (24%), skillful kill
(10%), bomb defuse (4%),
“This was my first time playing in a league
with a real team, we had spent a good portion
of the previous week practicing for this
specific match. The match didn’t end up going
so well, we ended the half down 12-3. We
rallied together and came back and made it to
match point. We couldn’t seem to close out the
match and eventually 15-14. I was the last one
left alive versus 4 other enemies. The intensity
of this 1v4 was insane. My heart was
essentially beating out of my chest. I clutched
the round and we won. The feeling of
excitement that was flowing through me was
unreal, my team was enthusiastic the whole
time, and after clutching we allot you screams
Positive performance
outcomes (38%)
Winning (32%), up-ranking (5%), learning (1%)
Performance context
(33%)
Competitive games (12%), close matches (10%),
playing with friends (7%), match beginning (2%)
pressure (2%),
Positive team
performance (13%)
Successful team performance (10%), good
cooperation 6%)
Emotions and gaming 22
and yells of excitement. Such an enjoyable
moment of victory.”
Anger
Negative own team
(43%)
Weak teammates (27%), team sabotage (15%),
throwing the game (7%)
“When I play against a cheater. I can’t leave
the game because I risk a temporary ban, I
can’t win the game because the enemy
cheating. Only wait and rage. I feel really
angry in this situation because I can’t do
anything, and I think about Valve who do
nothing against cheats. Sometimes I only want
to teleport myself in the cheater room and
destroy his face in his computer.”
Negative performance
outcomes (28%)
Defeat (10%), dying (9%), killed by headshot (4%),
losing a clutch (3%)
Negative rival-team
(20%)
Hacking (18%), trolling (2%), smurfing (1%), exiting
the game (1%)
Communication (16%)
Cursing and criticizing (7%), toxic behavior (7%),
racism (2%), power abuse (1%)
Underperforming
(14%)
Silly mistake (6%), losing a game that should be won
(4%), lack of control (2%)
Technical issues (13%)
Internet lagging (10%), game-bugs (3%), invisible
shots (2%)
Sadness
Negative performance
outcomes (45%)
Defeat (29%), derank (8%), losing close match (6%),
losing a clutch (2%)
“A game on overpass where we almost beat a
hacker. It had been fairly obvious from the
start of the game but due to them being a bad
player that is just aim botting me and my
friend could easily out play them with game
sense. When we got to 14-11 to our team, he
began rage hacking meaning we couldn’t win,
very saddening knowing we could have won
even when he was cheating. It made me so sad
I didn’t want to play anymore.”
Underperforming
(25%)
Underperformance (12%), losing a game that should
be won (9%), tilt (3%), silly mistake (3%), killing
teammates (1%)
Negative own team
(17%)
Weak teammates (15%), throwing the game (3%)
Never (10%)
Negative rival-team
(9%)
Hacking (7%),
Communication (7%)
Toxic behavior (6%), racism (2%), insulting (7%)
391
Emotions and gaming 23
392
Table 2
Text Analysis of the Emotional Situations During the Gameplay
LIWC
subcategories
F
η2
Post hoc
Positive emotions
15.70***
0.08
E>An***, E>S***, Am>An**
Negative emotions
28.21***
0.12
An>E***, S>Am***, S>E***
Anger
6.55***
0.03
An> E***
Sadness
37.40***
0.15
S>E***, S>Am***, S>An***
Social
6.33***
0.03
An>E***
Friend
5.44**
0.02
Am>S***
Feeling
8.29***
0.04
S>Am***, S>An***
Achievement
10.64***
0.04
S>Am***
Power
7.66***
0.04
E>An***
Reward
11.41***
0.05
E>Am***, E>An***, E>S***,
Risk
18.13***
0.08
S>E***, S>Am***, S>An***
Work
4.92**
0.02
Note. Significance adjusted for FDR. Am = Amusement, An = Anger, E = Enthusiasm, S =
Sadness. Dfs for ANOVAs = 3, 648.
**p < .01, ***p < .001.