Exploring music-based attachment to video games through affect expressions in written memories

This is a self-archived version of an original article. This version may differ from the original in pagination and typographic details. Author(s): Title: Year: Version: Copyright: Rights: Rights url: Please cite the original version: CC BY 4.0 https://creativecommons.org/licenses/by/4.0/ Exploring music-based attachment to video games through affect expressions in written memories © 2024 The Author(s). Published by Elsevier B.V. Published version Tuuri, Kai; Koskela, Oskari; Tissari, Heli; Vahlo, Jukka Tuuri, K., Koskela, O., Tissari, H., & Vahlo, J. (2025). Exploring music-based attachment to video games through affect expressions in written memories. Entertainment Computing, 52, Article 100883. https://doi.org/10.1016/j.entcom.2024.100883 2025 Contents lists available at ScienceDirect Entertainment Computing journal homepage: www.elsevier.com/locate/entcom Exploring music-based attachment to video games through affect expressions in written memories Kai Tuuria,b,∗, Oskari Koskelab, Heli Tissaric,d, Jukka Vahloe,b aFaculty of Education and Psychology, University of Jyväskylä, FI-40014, Finland bDepartment of Music, Art and Culture Studies, University of Jyväskylä, FI-40014, Finland cDepartment of Language Studies, Umeå University, Umeå 901 87, Sweden dDepartment of Languages, University of Helsinki, FI-00014, Finland eCentre for Collaborative Research CCR, Turku School of Economics, University of Turku, FI-20014, Finland ARTICLE INFO Dataset link: https://urn.fi/urn:nbn:fi:fsd:T-FSD 3473 Keywords: Game music Attachment Memories Affect expressions Music psychology Cognitive linguistics ABSTRACT This paper presents an exploratory research on music-based attachment to video games, studied through personally valued game music memories. It focuses on people’s engagement with game music and game technologies, expanding previous research on the role of game music in people’s lives. We gathered 183 written game music memories and analyzed their contents and language. We focused on expressions of affect and sentiment, which we assumed would indicate affective involvement. However, we also explored the constitution of attachment by investigating how expressions of affect and sentiment were associated with other aspects in the stories that reflect personal valuation, focusing specifically on factors of autobiographical remembrance, conceptualizations of game music, and gaming technology related to memories. These investigations employed a mixed-methods approach that combined qualitative and statistical analyses. A major finding was that especially personal remembrances that involved an awareness of the self or related to the game music experience significantly predicted the use of expressions of affect and sentiment in the stories. In sum, the study outlines a framework for investigating people’s long-term engagement with technology as being intimately related to the context of everyday life and the constitution of self-understanding. 1. Introduction Video games are cultural and commercial media products that offer their players a wide range of recreational activities and experiences. For many people, games and their music may also become objects of affection. Emotional attachment to certain products or brands in general relates to their perceived value, that is, how strongly people want to hold on to them rather than discarding them easily [e.g.,1]. As the concept of attachment originally stems from the context of interpersonal bonding [2,3], it has also been defined as a ‘‘strength of the bond’’ between the person and attachment targets, such as people, places, as well as technological products like social media [4, p. 71]. The interpersonal framework is relevant for understanding attachment to media, as there is evidence that people’s engagement with music listening, watching TV, and reading fiction do function as social surrogates [5]. In sum, the concept of attachment is essentially about long-term commitment to an object of affection that a person considers valuable and meaningful. In regard to video games, such attribution of value and affection to a game may develop upon appreciating the game either as a cultural expression/artifact [6,7] or as a first-hand ∗Corresponding author at: Faculty of Education and Psychology, University of Jyväskylä, FI-40014, Finland. E-mail address: [email protected] (K. Tuuri). experience of the playful activity (i.e., meaningful play) it affords [8– 10]. Attachment to games has been studied mainly through the lenses of need satisfaction, as well as from the perspectives of preferences, gratifications, and addiction for playing [11–16], or as an attachment to specific elements in games, such as characters [17], places [18] or virtual commodities and possessions [19,20]. To this date, however, no studies on attachment to game music has been published. Sounds and music have been prominent aspects of engaging with games since the dawn of video games. While the awareness and appreciation of game music as a significant part of gameplay experience has increased over the past years, studies on the long-term implications of game music are still scarce. Most of the existing research on game music has focused on the immediate effects of game music, that is, the role and function of music and audio on the gameplay experience during playing [e.g., 21–23]. A recent anthology on game music research [24] acknowledges perspectives that extend beyond gameplay (e.g., synergies with commercial popular music, remix communities, and game music concerts), but these accounts do not try to broadly approach https://doi.org/10.1016/j.entcom.2024.100883 Received 16 April 2024; Received in revised form 14 August 2024; Accepted 22 August 2024 Entertainment Computing 52 (2025) 100883 Available online 28 August 2024 1875-9521/© 2024 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ ). K. Tuuri et al. everyday practices with game music, nor do they explore the potential factors being involved in attachment to game music. In terms of broader game music studies, we want to emphasize Diaz-Gasca’s [25] study on motivators in the consumption of video game soundtracks. Relevantly to the present study, Diaz-Gasca explored the experiential and sociocultural reasons for engaging with game soundtracks, highlighting the role of personal memory connections in the development of interest in game music. However, his study does not attempt to comprehensively investigate the constituents of personal game music attachment. Music is strongly interconnected with memories, especially the ones including biographical self-remembrance [26]. This linkage between music and memory has motivated us to investigate the long-term valuation of game music through written memories. Music has an ability to take the listener back in time, and vivid feelings and sensations, like the ones involving nostalgia [27], can accompany memories of a specific event remembered. Some memories may even relate to intensely strong experiences with music [28], which can partly explain why people also attach to and willingly carry and cherish memories of specific pieces of music in their mind [29]. In this paper we investigate people’s meaningful relationships and lasting engagement with game music and gaming technologies, extending the scrutiny on the role of music in the person’s life in the longer term. This is done through focusing on personally valued memories and, in particular, the expressions of affect in them. Our focus is on Game Music Memories (GMMs), that is, memorable experiences of game music that are spontaneously self-selected by the research participants as meaningful and valued. The GMMs analyzed in this study were personal game music stories collected from 183 people though an open writing invitation. Our study belongs methodologically in a continuum of music research, in which experiences with a personally important piece of music is explored through retrospective, written self-narratives. Gabrielsson [28], for example, asked people to write about the strongest experience with music they have ever had. His seminal study presented a very wide spectrum of ways in which music can be personally important, demonstrating that the phenomenon of musical attachment is multifaceted in nature. As another example, Saarikallio et al. [30] collected descriptions of how people use their favorite piece of music to evoke emotions in daily life, pointing out the relevance of psychological functions of music in developing an everyday relationship with music. Finally, in an ethnomusicological study, Kilpiö [31] investigated people’s personal memories about their C-cassette use in Finland. This research highlighted the social and cultural historical role of technology as part of intimately memorable experiences with music. On the basis of existing research on music and memory [26,27] and previous studies involving retrospective recollection of experiences with music [28,30,31], we assume that writing about fond memories of game music experiences provides the participants with an access to personally important events and contexts being associated to games and their music. We expect that such memories open up the diverse ways how games and their music are connected with people’s lives, self-understanding, and social relationships. In this way, stories of memorable and valued experiences of game music disclose aspects of the music’s personal meaningfulness that not only relate to video games but also extend beyond the actual gameplay. Such a retrospective approach based on memories is expected to reveal perspectives of everyday life in varying time-spans, which inherently emphasize a longterm engagement with music. Through analyzing various indicators that reflect personal fondness, affection and cherishing being incorporated in GMMs, the overarching aim is to explore people’s personal attachment to game music, as well as people’s musical attachment to games. Our investigation is initially done by analyzing affect expressions (AEs) in written memories of fond (i.e., personally valued) game music experiences. With affect expressions we mean words and multi-word expressions that refer to affect [32]. Our rationale for this approach is that the amount of expressed affect in the written stories is deemed as a key indicator of an emotional involvement in writing a GMM, presumably signifying personal valuation and attachment towards the memory. Earlier studies on product attachment have distinguished emotional involvement as a factor of attachment and demonstrated its ability to predict, for example, brand loyalty and longevity behavior [33,34]. After outlining how expressions of affect are distributed across the GMMs, we perform further analyses on the language and the content of the stories. These are done with a particular aim to identify domains of story contents that would provide meaningful frameworks in relation to AEs that would explain how the memories with game music are valued by their owners. These analyses in relation to the affect expression indicators comprise the main element of the study. Next, through reviewing theoretical approaches in the upcoming sections, we will outline three domains as hypothetical frameworks for the purpose of relational analyses. Through these domains, we will find out how AEs are displayed in association with (1) personal remembrance, (2) metaphorical conceptualizing of game music, and (3) gaming-technologies associated with the stories. These story-related domains provide thematic lenses for complementing the investigation of AEs, by explaining how game music memories are valued by their owners — also providing us with a human-centric framework in gaining understanding of people’s relationship with games and ways people are attached to their music. 2. Research framework and questions 2.1. Meaningfulness of autobiographical memories Music has been found to be an effective trigger of autobiographical memories [35]. A recollection of game music arguably provides a way for a person to get in touch with the meaningful events of the past. In other words, fond GMMs not only concern involvement with the music itself, but they should also incorporate various elements of gameplay experience as well as broader everyday meanings that extend beyond the actual situations of play. According to Diaz-Gasca’s [25] study, people value experiences of game music because of the memories they evoke. The study revealed that many of those evoked memories related to the gameworld, its events, feelings and aesthetics. But similarly to musically evoked memories in general [26,27], they also included broader remembrances and associations of past times: nostalgic memories of family, friends, places and other autobiographically and socially significant experiences. In general, it has been hypothesized that the sense-making of the self (i.e., what kind of person we are) and the others (how we relate to other people) are among the most prominent functions of autobiographical recollection in humans [36–38]. The retrieval of autobiographical memories can be either spontaneous or strategic in nature [37]. The former type is also called involuntary recall as it refers to becoming aware of a past experience without a conscious attempt to retrieve it [39]. Spontaneous and strategic retrieval also differ from each other in regard to the type of memory content. For example, spontaneous recall more often provides access to specific episodes of a personal past and the associated emotions [40]. On the other hand, strategic/voluntary retrieval is more often associated with problem solving and social sharing of memories, rather than daydreaming, thinking about a person, or identity, which were more frequently disclosed purposes in involuntary memories [37]. The way in which memories are sampled thus matters in studying GMMs. Specific and detailed episodic memories, characteristic of spontaneous retrieval, together with emotional associations [including connections to embodied memories, see 41] fit the purposes of this research better than more abstract and disembodied generalizations of past experiences. Our method for gathering the memories intentionally aimed at providing support for spontaneity in recalling personally meaningful game music experiences. Entertainment Computing 52 (2025) 100883 2 K. Tuuri et al. 2.2. Purposes of engaging with music memories DeNora [42,43] has emphasized the role of music as a personal and social resource that people use reflexively for constructing meanings and constituting themselves as certain types of individuals and social agents. The idea of ‘‘music as a resource’’ raises the question: in what ways do people, either consciously or unconsciously, use music in their everyday lives? In the field of music psychology, there has been a lot of research especially on functions related to the regulation of emotions and moods, social bonding, and evoking memories as well as developing one’s self and identity through music [44–48]. A recent study by Tuuri et al. [49] corroborates the relevance of this approach also in the context of game music. Because the number of different functions of music identified in music psychology studies is large and the functions relate to different research approaches, there have been efforts to synthesize and find the themes underlying the functions and connecting them. Schäfer et al. [50], for example, carried out a survey that included 129 descriptions of the functions identified in the literature. By using principal component analysis, three functional dimensions of listening to music were outlined from the responses. According to the results, people in general listen to music (1) to achieve self-awareness, (2) as an expression of social relatedness, and (3) to regulate arousal and mood. Arguably, these findings also promote a more general understanding of how the dimensions of music’s everyday meaningfulness and valuation could be structured. Considering that Shäfer et al.’s [50] functions relate to the context of listening to music, we expect to see some differences between them and the functions relating to reminiscing on musical experiences, which is the focus of the current study. While the former relate to utilizing musical sounds in everyday circumstances, the functions in reminiscing are about utilizing the past experiences to perceive and make sense of the present. In the context of reminiscing, the self-awareness function clearly relates to perception of the self through reminiscing and reflecting the experiences with music. Due to the private nature of reminiscing, the relatedness function apparently focuses on reflecting social relations through the past experiences with music, instead of expressing and displaying them through music in the present. These two dimensions of self-awareness and social relatedness align well with the similarly prominent functions of autobiographical recollection in general [36–38]. In regard to the third music listening function, arousal and mood regulation, our focus will be on the needs to re-experience the music through reminiscing — that is, the purposes of re-enacting the emotional and aesthetic past experiences of the music. From this viewpoint, relying on either spontaneous or strategic retrieval, reminiscing music arguably is closely related to the memory-related phenomenon of musical imagining. This refers to recalling and experiencing a familiar piece of music through the ‘‘mind’s ear’’ [29,51–53]. In the manner described above, the tripartite model of self-, socialand experience oriented purposes of engaging with music can be applied as dimensions of personal remembrance for analyzing the autobiographical and game music related experiential contents in the GMMs. 2.3. Conceptualizations of intimate relationship with game music The way DeNora [42,43] has framed music as a resource is already an example of metaphorical language, that is, a way of describing some abstract thing, a target domain, in terms of a more concrete conceptual source domain. In general, such metaphorical mappings relate to conceptualizing a given target domain through the characteristics of a chosen conceptual source, consequently constituting one’s understanding of the target domain [54]. Talking about music as a ‘‘resource’’ thus is about understanding music as a valuable commodity, while also bringing the focus on what it provides to a person when interacting with it. Rather than suggesting that metaphors are merely a rhetorical device, the theory of conceptual metaphors [54,55] highlights the cognitive-linguistic mappings incorporated in the processes of human sensemaking. It is well known that people tend to use metaphoric language when describing what they hear in music and what their musical experience is like [56,57]. Besides conceptualizing specific moments in music, metaphors can also operate on a larger scale, as is evident in the way whole musical works are treated as ‘‘stories’’ or ‘‘narratives’’ [58]. Moreover, it has been suggested that even the most fundamental aspects of our understanding of music, such as the pervasive idea of music as ‘‘movement’’, are largely metaphorical in nature [59]. According to the theory of conceptual metaphor [54], human thought is largely structured by different conceptual metaphors. For example, the metaphor MUSIC IS RESOURCE can be identified in metaphoric expressions, such as ‘‘I use music to relieve my stress’’, which employ the conceptual metaphor in question. With respect to the aims of this study, we consider this kind of cognitive-linguistic perspective insightful for describing how attachment manifests in language. Particularly, we investigate how the perspective of conceptual metaphors can be applied to discovering ‘‘ways of attaching’’, that is, what kind of conceptual metaphors people use in conceiving their intimate or fond relationship to game music. 2.4. Role of gaming technologies in music-based attachment Gaming technologies, different platforms and their interfaces are essential aspects of everyday gaming experiences. By investigating attachment to video games with a long-term perspective through written memories, aspects of an enduring attraction of the games and devices from different eras are likely to be revealed. It is easy to assume that fond memories of engaging with game music also disclose affection towards games and game devices of different time periods that relate to the music. Despite being rendered obsolete by newer ones, some games, gaming devices [e.g., 60], and even specific types of audio hardware [e.g., 61] attain a status as classics — or as objects of a certain ‘‘retro chic’’ fascination because of being outdated [62]. Besides cultural valuations of gaming technologies, seen, for example, in the discourses about the past ‘‘golden era’’ of video games and video game music, valuations also relate to a personal level of meaningfulness that entangle with people’s autobiographical histories involving gaming artifacts. This is in line with studies addressing how games and the related hardware from certain periods may serve as vehicles for nostalgia [63], venerated artifacts of retro sensibilities and different fan communities [64], loci for constructing one’s identity [65] or sources of appreciation for aesthetic features related to bygone technologies [61,66]. These notions imply how an affection to game music could relate to certain technologies or time periods. More generally, we can hypothesize that there are linkages between video games, gaming technologies and game music that potentially have implications on attachment. A person may have developed, for example, a particular fondness for the sounds, graphics, or physical interfaces of certain devices or specific technology brands. 2.5. Research questions The study is organized into research questions (RQs), which are formulated as follows. Affect expressed in written reminiscing of personal game music experiences is here deemed as a fundamental indicator of personal affection towards the memory. Therefore, the initial aim of the investigation is to detect how much affect is expressed across the game music memories (coined as RQ #0). The subsequent RQs (#1–3) relate to further investigations on the GMM contents that, in relation to the affect-component, provide complementary takes on how the valuation Entertainment Computing 52 (2025) 100883 3 K. Tuuri et al. Fig. 1. Research model for exploring music-based attachment to video games through affect expressed in written memories about personally valued game music. of the game music is displayed in these personal narratives. These RQs address how AEs are displayed in association with the thematic domains discussed in the previous sections. As a methodological premise, we expected stories about fondly reminisced game music experiences to reflect personal valuation of the memories, incorporating expressions and content relevant to musicbased attachment to video games. The overarching objective of this study is to find out which of the variables, outlined in investigations of RQs #1–3, are statistically the most important in predicting the use of AEs and positive/negative sentiment in the stories. By identifying the main precedents for expressing affect in reminiscing game music experiences, it is consequently possible to better understand their potential roles in constituting attachment to game music. The research model, as a whole, is illustrated in Fig. 1. RQ #0: What is the amount and valence of expressed affect across the GMMs? The first aim of the study is to get an initial grasp of an overall ‘‘affective landscape’’ of the stories in order to understand people’s attachment to games and their music. The target of the investigation here is in detecting how much affect is expressed across the personal narratives. We take explicit AEs as general indicators of affective involvement in recalling and writing GMMs, and therefore also as an indicator of importance of a memory and its experiential contents. An accompanying strategy here is to investigate the overall valence of the memories by measuring the amount of positive and negative sentiment in the stories [67]. While one would expect the fond memories to be mostly positive, previous research suggests [68] that affective experiences often consist of a mix of positive and negative valence. Both the measures of AE frequencies and the sentiment intensities across the stories comprise the dependent variables representing game-music based affection in the GMMs for the rest of the investigation. RQ #1: How do the dimensions of personal remembrance structure GMMs and how are these dimensions associated with AEs? Our investigation regarding this RQ is formed in accordance with the three dimensions of personal remembrance outlined above. Firstly, the dimension of Self-awareness captures cognitive reflection involving a person’s self and identity through reminiscing experiences with game music. The second dimension, Social relatedness, is about the social environment around musical engagement. In these two dimensions, the element of affection is hypothesized to involve the valuation of autobiographical remembrances and the associated reflections of the self and the others. The dimension of Game music experience focuses on the reminisced experiences of being involved with game music. Our take on this dimension not only includes game music, but it also extends to capture the lived-through experiences of the gameplay as a whole. Here, the affective element is expected to relate to the aesthetic enjoyment of the experience and the related practices [see 10,69]. RQ #2: How do metaphors of game music structure GMMs and how are these metaphors associated with AEs? This RQ relates to explaining attachment to game music trough metaphorical conceptualizations of game music in the stories. We first identify metaphoric expressions of game music and then explore the employment of different cognitive-linguistic source domains in them. The utilized source domains provide information on how the story writers conceive their relationship with the game music (e.g. by conceptualizing music as a ‘‘buddy’’ or a means of ‘‘traveling’’). RQ #3: How does involvement of gaming technology structure GMMs and how are technology relations associated with AEs? The reminisced experiences in stories relate to games and game devices from different historical periods, as well as different types of technological platforms (i.e., home computers and gaming consoles). Regarding this RQ, we explore these variations in technology types (i.e., the game titles and devices) across GMMs, and possible technology-related dependencies that may indicate the existence of technology-specific attachment and nostalgia. 3. Data and methods 3.1. Data gathering Stories about fondly reminisced game music were collected from Finnish participants via a publicly available writing invitation for GMMs, arranged in collaboration with the Finnish Social Science Data Archive. In the online form for story collection we asked: ‘‘Do you have memories related to game music that you feel are important to you – or even loved? We want to hear your story about just such memorable game music experiences’’. After the initial question, the topic of memorable game music experience was briefly described in an open and non-definitive manner. Adapting the idea of elicited writing [see 70], the intention of the call was to get spontaneous and freely formed personal narratives on the given topic from the people. In addition to the stories, background information of participants was asked. The form included questions about gender, age, gamer identity (options: ‘‘I’m an active gamer’’, ‘‘I’ve been an active gamer at an earlier stage of life’’, ‘‘I don’t consider myself an active gamer’’), and questions about the time a person uses daily for playing games. The writing invitation, together with the link to the online questionnaire form, was dispatched through various channels, including social media groups and emailing lists. A Facebook marketing campaign was also used for spreading the writing invitation to ensure that it would reach people from different demographic groups. There are indications that similar memory triggers about random topics, received during everyday activities, have provided support for spontaneous reminiscing [71]. Initially, 184 people responded to the writing invitation, of whom one had to be left out because of being under-aged.1 1The Finnish national board on research integrity states that the person’s own consent to participate is sufficient when the participant is 15 years old or older. Entertainment Computing 52 (2025) 100883 4 K. Tuuri et al. Table 1 Cross-tabulations of gamer identity with daily average gameplay, and gender. Active gamer Has been active gamer Not a gamer Total (n) Less than 15 min 5.4% 73.0% 21.6% 100% (37) 15–30 min 41.2% 41.8% 17.2% 100% (29) 30–60 min 82.1% 15.4% 2.6% 100% (39) 1–2 h 85.4% 14.6% 0.0% 100% (41) Over 2 h 100.0% 0.0% 0.0% 100% (37) Total 64.5% 27.9% 7.7% 100% (183) Female 51.5% 24.2% 24.2% 100% (33) Male 67.8% 28.0% 4.2% 100% (143) Total 64.8% 27.3% 8.0% 100% (176) 3.2. Participants The participants consisted of 183 people (Age 𝑀= 34.6years, 𝑆𝐷 = 7.81,𝑀𝑖𝑛 = 17,𝑀𝑎𝑥 = 59). Two individuals did not disclose their ages, and these are treated as missing values in the coming analyses. Of the participants 78% (𝑛= 143) were male and 18% (𝑛= 33) were female. It should be noted that the smaller portion of female respondents does not represent the Finnish population of game players, which should consist of more or less equal distribution of the male and female genders [72]. Five participants reported their gender as ‘‘other’’, and two participants did not want to tell their gender. Due to the small size of the latter two groups, these cases are excluded from further statistical analyses involving gender comparisons. Most of the participants (64.5%, 𝑛 = 118) reported that they are active gamers. The second largest group (27.9%, 𝑛 = 51) reported that they have been playing actively at an earlier stage of life. The rest of the participants (7.7%, 𝑛 = 14) did not consider themselves as being active gamers. This self-classification is consistent with the reported amount of daily gameplay in a statistically significant manner 𝜒2(8,183) = 98.50, 𝑝 < .001 (see Table 1). Participants that have been active gamers also appear to be moderately active game players in the present. The Chi-squared test reveals a significant dependence between gamer identity and gender 𝜒2(2,176) = 14.79, 𝑝 < .001. Compared to males, a bigger percentage of the female participants do not identify themselves as gamers. 3.3. Methodological approach on analyzing the data The analyses performed on the stories followed a mixed-methods approach combining both qualitative and quantitative elements. The qualitative elements essentially comprised the means of identifying and understanding the verbal expressions and thematic contents of the stories in relation to each research question. The rationale for the quantitative elements was to investigate the prevalence of the given qualitative dimensions in numerical form and outline them as variables to perform statistical analysis. The strategy was to first perform linguistic analysis of the stories for detecting the instances of displayed affect (RQ #0), as well as identifying the use of metaphoric expressions and their ways of conceptualizing a person’s relationship with the game music across the stories (RQ #2). Next, shifting the qualitative focus on story contents, we identified instances of the thematic dimensions of Self-awareness, Social relatedness, and Game music experience (RQ #1). From the stories, we also collected information about the mentioned games and gaming technologies (RQ #3). In qualitative analysis, coding generally refers to attaching labels to segments of data that describe their content and provide analytical handles for making comparisons with other coded data segments [73]. Through exploratory qualitative coding, we first identified specific key expressions and thematic contents from the textual data, and then investigated how affect expressed across the stories associates with the other elements identified in the stories. All of the coding was carried out manually, with the third author being primarily responsible for linguistic identification of affect expressions and conceptual metaphors, while the first and the second authors being responsible for thematic content analysis and additional parsing and grouping of metaphors. The qualitative codings were quantified for performing comparative between-participants statistical analyses. In addition to the quantification of qualitative analyses, numerical data about the expression of sentiment (RQ #0) was computationally extracted from the stories by the method of automated sentiment analysis. The ultimate aim was to explore how the affect expressed in the stories associates with the linguistic and content-related elements, also coded into the stories, and finally to model which of the elements are the most important predictors of affect expressions and sentiment intensities. Statistically this was achieved through a linear regression model, using the frequency of affect expressions as a target, and the other story related elements as independent variables. 3.4. Qualitative analysis The qualitative analyses were done with Atlas.ti software for indicating the presence of specific expressions, mentions, themes or concepts in the textual data. Quotations from the text data were coded in terms of each aspect of interest. Quotation length was freely determined by a researcher responsible for a given code, thus the unit of analysis was not fixed (e.g., to words or paragraphs). The validity of codes and coding was constantly controlled by evaluative discussions between the researchers during the process of content analysis. Our starting point of text analysis was to outline affect expressions (RQ #0). As a principle, we concentrated on wordings that were used to describe affective or emotional experience, thus not necessarily direct expressions or bursts of emotions [see 32]. In this manner, 853 quotations were identified as AEs. In order to illustrate the content of these identified AEs, their most frequent words were examined. Table 2 shows English translations of the original Finnish words2that were counted at least three times across all AE-coded quotations. Note that the words in the quotations that were deemed to be irrelevant noise in terms of the affect content (such as equivalents of ‘‘and’’, ‘‘which’’ or ‘‘that’’) were not included in the word count but were filtered out by using the stop-list function of Atlas.ti. Moreover, frequent words ‘‘music’’ and ‘‘game’’ as well as words that translate redundantly to the same English word were excluded from Table 2. The resulting list (see Table 2) includes a range of verbal means for either denoting emotions, moods and feelings, or describing the ways of being affectively engaged. In a similar manner to detecting AEs, another linguistically oriented analysis was carried out to outline metaphoric expressions of game music in the stories (RQ #2)3. The researcher responsible for the initial detection phase gave them preliminary names as conceptual metaphors, thus identified their conceptual source domains. A similar naming process is described by Stefanowitsch [75], which he calls metaphorical pattern analysis. In the next phase, the metaphors and the naming of their source domains were scrutinized together with the other authors. As a result of the discussion, the categorization of metaphors became both more precise and more diverse. Also, some of the expressions originally marked as metaphorical were excluded from the analysis, which resulted in the final number of game music metaphors across the stories being 555. In the final stage of the analysis, all metaphoric expressions of game music were parsed and 2An inflected Finnish word often needs to be translated into more than one English word. Whereas Finnish operates with endings, English operates with prepositions. 3This analysis of conceptual metaphors has been previously published. For a more detailed report, see [74]. Entertainment Computing 52 (2025) 100883 5 K. Tuuri et al. Table 2 A list of the most frequently used words across the 853 AEs (Finnish words translated into English). Emotions Emotion I liked Nostalgic It felt (like) To me I like Heart I got enthusiastic Excitement Mind Nostalgy Peaceful Feeling Melancholic Came To cause I got enthralled Happiness With eagerness Attached Rather Memories I enjoy Enjoyed Get Good Excited Exciting Experience Cold I remember Up Dear I love Dearest Dear ones Soothing To the heart My heart Feel Into a mood Shivers Anxiety Annoy Particularly Longing Evoked To my delight With some Grateful Towards Touch Tears Warm With warmth To my mind Gladly Pleasure Me In me Fear Sadness Sad Greatly Atmosphere Fig. 2. The main categories of metaphorical source domains, together with examples of the related image-schematic structures, in the conceptualization of game music. grouped into a more coherent model of metaphor types. The purpose was to clarify metaphorical similarities and differences by examining their image-schematic structures [76]. Through this process, 8 main thematic categories of metaphorical source domains were identified (see Fig. 2), in which game music is conceptually described in terms of Agencies, Forces, Spatial relations, Transference, Mediators, Linkages, Tangible objects, and Sensations.Fig. 2 also illustrate how each of the main categories incorporated varying image-schematic structures for manifesting the source domain. Regarding the content analysis on the three dimensions of personal remembrance (RQ #1), another set of coding was carried out for each thematic dimension (the number of quotations attributed to each theme is presented in brackets). For this we utilized combinations of previously done content-driven sub-codings that matched the theory-based dimensions. The theme of Self-awareness combined two separate subcodings: ‘‘autobiographical expressions’’ and ‘‘expressions reflecting or describing the self’’ (in all 586 quotations). The theme of Social relatedness consisted of a coding category ‘‘other people’’, which includes either explicit mentions or implicit indications of other people being involved in the experience (in all 559 quotations). And finally, the theme of Game music experience combined three sub-codes containing descriptions of ‘‘episodic experiences of activity’’, ‘‘experienced immersion, adventure and flow’’, and ‘‘qualities of music’’ (in all 1139 quotations). All mentions of gaming devices and game titles were detected and coded across the stories (RQ #3). These codings were used as the basis for categorizing GMMs according to a gaming device type (home computer memories, game console memories, or mixed/undisclosed), and for determining a median publication year of the game titles mentioned in the story. In addition, references to specific game music technologies were coded. Such type of explicit references mostly pointed at specific sound-producing technologies that were common in devices from the early 1980s to the mid 1990s [see 77]. By utilizing these codes in combination with the codes involving specific gaming devices and game titles, we were able to categorize all GMMs after the game music technologies they incorporate (vintage audio, modern digital audio, or both technologies). The vintage audio class here includes ‘‘chiptune’’ technologies (i.e., programmable sound chips and beepers), ‘‘tracker’’ or ‘‘MOD’’ format music technologies (based on short sound samples), and ‘‘Adlib’’ or ‘‘General MIDI’’ technologies (i.e., FM or wavetable synthesizers on sound cards) [see 78, pp. 7–61]. In contrast to the vintage game music, which is based on a sequenced playback of synthesized sounds, the modern digital audio class is characterized by a pre-recorded form of music playback. 3.5. Quantitative measures and analysis The frequencies of code occurrences and co-occurrences were obtained from the Atlas.ti software. Because the quotations of both AEs and Social relatedness were relatively short (often just a few words or even a single word), relational co-occurrences between the two were detected by using a five-word-long window of neighboring words both preceding and following the quotations. In this study, sentiment analysis functions as an indication of the general intensity of positive and negative valence in texts (RQ #0). Therefore, we do not expect that only explicitly expressed affect would have an effect on the sentiment intensity measures. Stories also contain, for example, opinions and evaluative expressions, as well as episodic descriptions of gameplay. The two example quotations4below demonstrate parts of stories that were not identified as explicit AEs but nevertheless get a high intensity score of sentiment. The latter example also illustrates how the reporting of gameplay experiences (of, e.g., fighting the aliens in a game) can denote negative sentiment, although the overall point of the writer seems to be in describing the positively impressive nature of the game music. ...In the 80s, game music was awesome! The C64 game ‘‘Forbidden Forest’’ by Paul Norman and the music he composed for the same game were really great. (+4 positive sentiment) ...However, the most impressive song always played when x-com soldiers attacked to destroy an alien base. The background music playing during the mission brought to the surface all the same sensations as during any horror film. (−4 negative sentiment) We used the SentiStrength [67] software to perform the analysis. It is a lexicon-based analysis program that also provides word lists for the Finnish language. SentiStrength has been designed to evaluate the intensity of sentiment in short informal texts (e.g., in social media) and has been used for analyzing texts in Finnish [79]. The software provides two scores to the texts: the intensity of positive sentiment (a score ranging from 1to 5) and the intensity of negative sentiment (a score ranging from −1 to −5). The dual scoring method is appropriate since texts often contain a mix of positive and negative sentiments. 4All quotation examples in this paper are translations of the original Finnish texts. However, all measures refer to the original texts. Entertainment Computing 52 (2025) 100883 6 K. Tuuri et al. Fig. 3. Frequencies of mentions of games and game series (n =664) ordered by publication year. For the sake of clarity in the further analyses, the scores of negative sentiment was converted to positive values. We also used the program’s ability to perfom a trinary classification of overall sentiment (a score of −1,0or 1, respectively denoting negative, neutral and positive overall sentiments). Statistical analysis was performed with SPSS 29 software. The number of affect expressions and the word count in stories were tested with a Kolmogorov–Smirnov test of normality, which indicates that the AE frequencies and story lengths do not follow a normal distribution, 𝐷(183) = .226, 𝑝 < .001 and 𝐷(183) = .205, 𝑝 < .001 respectively. For this reason, and due to the ordinal nature of some measures of this study, statistical analyses preferably utilize non-parametric tests appropriate for given variables, including Kruskal–Wallis analysis of variance and Spearman’s correlations. 3.6. Story data descriptions All but one of the stories were written in Finnish (one was in English). The length of the stories varied strongly from very short (𝑀𝑖𝑛 = 8 words) to relatively long (𝑀𝑎𝑥 = 2144 words), the mean and median lengths being 235.8 and 158.0 words, respectively. Gender seems to have an effect on the length of the stories, as the Kruskal– Wallis test indicates 𝐻(1,176) = 5.68, 𝑝 < .05). The median word count for female respondents (𝑀𝑑𝑛 = 192.0) was higher than the same figure for male respondents (𝑀𝑑𝑛 = 137.0). In all, 322 different games or game series were mentioned across the stories. The publication years of the titles were retrieved from a videogame database hosted by Kinrate Analytics.5Broad references to game series were common in the stories, which did not necessarily specify the exact titles of the series. In these cases, the specific sub-titles of the series were ignored in the analysis. The publication year of the most frequently mentioned specific game title (e.g., Final Fantasy VII) was selected to represent the whole game series (e.g., Final Fantasy). As we can see from Fig. 3, the overall emphasis in GMMs was on older games: games published in 1985–1987 received the greatest number of mentions across the stories. In further analysis we use the Median publication year of all the game titles mentioned within a story. Thus, in terms of games mentioned in GMMs, this figure represents the average time period that the story has its focus on. In terms of a Median publication year, the biggest number of stories were attributed to the years 1997 (12%, n =22) and 1986 (8.2%, n =15). For six stories, publication years could not be determined. There was a strong negative correlation with the median publication years and the age of the participants (𝑟= −.548, 𝑝 < .001), meaning 5Kinrate Analytics (https://kinrateanalytics.com) is an academic startup company that provides services in player analytics, and they hold a game database of some 100,000 entries. Table 3 Comparison of average median publication years (MPY) and ages across gaming device and game music technology groups. MPY (Mdn) Age (Mdn) Gaming device: Computer 1990 40 Console 1997 29 Mixed 1997 33 Music technology: Vintage 1987 41 Modern 2002 29 Both 1996 35 that older participants tended to reminisce about older games. Also, the median publication years are associated with gender 𝐻(1,170) = 6.65, 𝑝 < .05. However, the average values for men (Mdn =1995) and women (Mdn =1997) differed only a little. In regard to gaming devices, the GMM stories were divided into home computer memories (42.6%, n =78), game console memories (31.1%, n =57), and memories of mixed or undisclosed device types (25.7%, n =47). One of the stories was not based on digital game technology and it was excluded from the categorization. Yet another technology-related classification concerned how the stories related to either vintage (31.7%, n =58) or modern (36.6%, n =67) game music technology, or both of the technologies (30.1%, n =55). Three of the stories (1.6%) did not provide particular enough references to technologies and were excluded from these classes. The Chi-squared test reveals a significant dependence between these groupings (𝜒2(4,179) = 60.76, 𝑝 < .001). In particular, it seems that computer-based memories are associated more with vintage music technologies (61.5% overlap), and console-based memories are more affiliated with modern digital audio technology (59.6% overlap). From Table 3 we can observe how both of the technology-based categorizations differ in terms of a story’s Median publication year and a participants’ age. On average, computer-based memories were centered on older games and were written by older participants when compared to the other types of GMMs. The association between Gaming device and Median publication year is significant (𝐻(2,176) = 24.221, 𝑝 < .001). A post-hoc pairwise comparisons test (Dunn-Bonferroni) further indicated that, in particular, the scores of the Computer group were observed to be significantly different from those of group Console (𝑝 < .001) and group Mixed (𝑝 < .001). The Music technology groups also differed in terms of the Median publication years of the stories. The score differences were significant (𝐻(2,177) = 108.416, 𝑝 < .001). But unlike the Game device groups, in which only computer-based stories differed, post-hoc comparisons indicated that all three Music technology groups were significantly different from each other (𝑝 < .001). 4. Results 4.1. Indicators of affect (RQ #0) 4.1.1. Affect expressions Across the stories, 853 excerpts of text were identified as AEs. The mean frequency of AEs within a story was 4.66 (𝑆𝐷 =6.17). Their distribution was uneven, however, and not all stories even contained them: of the 183 stories, 24.6% (𝑛𝑛𝑜𝑛𝑒 =45) had no AEs, 35% (𝑛𝑓𝑒𝑤 = 64) had 1–3 AEs, and 40.4% (𝑛𝑚𝑎𝑛𝑦 =74) contained more than three AEs. The maximum number of AEs per story was 39. This is not to say that almost one quarter of the stories were without affect, but it was just not explicitly expressed in the text. Regarding gender related differences in the distribution of AEs, there is a statistically significant effect of gender, according to the Kruskal–Wallis test, 𝐻(1,176) = 12.31, 𝑝 < .001.Fig. 4 indicates that women (𝑀𝑑𝑛 =6) used AEs more frequently than men (𝑀𝑑𝑛 =2). As many as 72.7% of women used more than three AEs in their stories, compared to 32.2% of men in the same category. Entertainment Computing 52 (2025) 100883 7 K. Tuuri et al. Fig. 4. Boxplot showing distributions of AE frequencies for females (Mdn =6) and males (Mdn =2). We also found significant correlations both between Age and AE fq (𝑟= −.270, 𝑝 < .001) and between Word Count and AE fq (𝑟=.786, 𝑝 < .001). So there is a slight negative correlation with respondent’s age, and a strong positive correlation with the word count of the stories, both of which are observable in Fig. 5. The latter correlation seems obvious in a sense that longer stories afford more frequent use of AEs. 4.1.2. Sentiment intensities Across the stories, the values for positive sentiment (𝑀=2.53, 𝑀𝑑𝑛 =3, 𝑀𝑖𝑛 =1, 𝑀𝑎𝑥 =4) were generally higher than the negative counterparts (𝑀= −2.07,𝑀𝑑𝑛 = 1,𝑀𝑖𝑛 = 1,𝑀𝑎𝑥 = 5). As the median values imply, the most frequent score for positive sentiment was 3(54.6% of the stories) while the respective score for negative sentiment was 1(53.0% of the stories). In other words, more than half of the stories attested no negative sentiment, as the score of 1denotes no intensity. The portion of stories with no detected positive sentiment was much smaller, only 19.1% of the stories. The classifications of overall sentiment polarity provided further indication of a general bias towards positive valence in GMMs. As much as 121 stories (66%) were evaluated as positive, 33 (18%) as neutral, and 29 (16%) as negative. The Kruskal–Wallis test showed no significant differences of gender in positive sentiment scores, 𝐻(1,176) = 2.48, 𝑝 =𝑛.𝑠. Both women (𝑀𝑑𝑛 = 3, 𝑀 = 2.76, 𝑆𝐷 =.87) and men (𝑀𝑑𝑛 = 3, 𝑀 = 2.48, 𝑆𝐷 =.91) produced positive sentiment with almost an equal intensity, although the mean value is slightly higher for females. However, there is a statistically significant effect of gender in negative sentiment, 𝐻(1,176) = 3.885, 𝑝 < .05. It appears that women (𝑀𝑑𝑛 = −2,𝑀= −2.48,𝑆𝐷 =1.5) generally produced slightly higher intensities for negative sentiment than men (𝑀𝑑𝑛 = −1,𝑀= −1.92,𝑆𝐷 =1.19). No significant correlations were found between sentiment intensities and age. However, the word count of the stories had statistically significant correlations with both positive (𝑟=.487, 𝑝 < .001) and negative (𝑟=.532, 𝑝 < .001) sentiment. We also found a significant dependency between gamer identity classes and overall sentiment polarity classifications, 𝜒2(4,183) = 12.17, 𝑝 < .05. The most salient observation from the distributions is as follows: Of the 29 stories classified as negative, even 26 (89.7%) were written by active gamers. The negative sentiment stories were, however, only 22% of the active gamers’ stories in total (𝑛=118), the percentages for neutral and positive stories being 13.6% and 64.4% respectively. Although most of the negative stories were written by active gamers, 62.8% (𝑛𝑝𝑜𝑠 =121) of the positive and 48.5% (𝑛𝑛𝑒𝑢𝑡 =33) of the neutral sentiment stories were also written by this largest group of participants. Finally we tested if there are correlations between sentiment intensities and AE frequencies. The results yielded significant correlations, moderate for positive (𝑟=.444, 𝑝 < .001) and strong for negative (𝑟=.600, 𝑝 < .001) sentiment scores. The results imply that both types of sentiment intensities go hand-in-hand with AE occurrences across stories. 4.2. Dimensions of personal remembrance (RQ #1) Across the stories, contents relating to the dimensions of Selfawareness (586 instances in 88.5% of the stories), Social relatedness (559 instances in 63.9% of the stories), and Game music experience (1139 instances in 88.0% of the stories) were identified. The frequencies of each remembrance dimension per story were distributed as follows: Self-awareness (𝑀= 3.20,𝑆𝐷 = 3.16𝑀𝑖𝑛 = 0, 𝑀𝑎𝑥 = 19), Social relatedness (𝑀=3.05, 𝑆𝐷 =4.53 𝑀𝑖𝑛 =0, 𝑀𝑎𝑥 =32), and Game music experience (𝑀=6.22, 𝑆𝐷 =8.69 𝑀𝑖𝑛 =0, 𝑀𝑎𝑥 =73). Remembrances about game music experiences were about two times more common in comparison to the other dimensions. No associations with age or gamer identity with the distribution of remembrance types were found. There was, however, significant effect of gender on the story contents concerning Self-awareness (𝐻(1,176) = 11.517, 𝑝 < .001) and Social relatedness (𝐻(1,176) = 18.557, 𝑝 < .001), being observable in higher respective frequencies in the stories of women (𝑀𝑠𝑒𝑙𝑓 =4.48, 𝑀𝑠𝑜𝑐𝑖𝑎𝑙 =5.85) than men (𝑀𝑠𝑒𝑙𝑓 =2.91, 𝑀𝑠𝑜𝑐𝑖𝑎𝑙 =2.34). 4.2.1. Thematic sub-types of affect expressions For explicating the associations between the thematic dimensions and the AEs (RQ #1), we carried out a relational analysis of how AEs were thematically displayed in the stories. This was done through detecting three sub-types of AEs that represent co-occurrences of AEs with the story contents relating to dimensions of Self-awareness,Social relatedness, or Game music experience. For each sub-type, we provided some examples in the form of text quotations that illustrate how AEs were connected to each dimension of personal remembrance. In all, 404 Self-awareness related AEs (i.e., SELF-AE) were detected, hence this was clearly the largest of the three subclasses. The mean frequency of SELF-AEs within a story was 2.21 (𝑆𝐷 = 3.64), which is almost a half of the overall frequency of AEs. The distribution across the 183 stories was as follows: 40.4% (𝑛𝑛𝑜𝑛𝑒 = 74) had no SELF-AEs, exactly same amount of stories (𝑛𝑓𝑒𝑤 = 74) had 1–3 of them, and 19.1% (𝑛𝑚𝑎𝑛𝑦 = 35) contained more than three. The maximum number of SELF-AEs in a story was 26. The following examples show AEs within their thematic contexts including self-reflective remembrances of past times. These typically dealt with themes of personal growth, coming of an age, overcoming obstacles of life, as well as other kinds of relationships with the game music that reflect a person’s identity. In the quotations, AEs are highlighted with bold text, and emphasis is added to the game title. ...I began to think that this game [Child of Light], and also its music, taps into a feeling of how I took some key steps towards adulthood during that time. Many things are somehow associated with that feeling that the years of youth are over: Playing the title song yourself (just as was customary with Amelie’s theme back then); a return to video games after years of adolescence, and the difficult stages and losses in my close relationships that forced me to look at life in a new way...(male, 31) ...Sonic’s music is happy and helps me cope with everyday life. It cheered me up as a child when I was bullied at school...(female, 30) ...With that game [Legend of Zelda: Ocarina of Time], I learned to play, read, and learned a new language, because of course the game was in English. At the same time, I also went through a wide variety of emotions. You could say I kind of grew up with that game...(male, 26) Entertainment Computing 52 (2025) 100883 8 K. Tuuri et al. beyond gameplay (i.e., autobiographical memories of the game music) associate with video game music affection. This underlines the importance of game music, not only within games, but generally in how we engage with music for constructing our everyday experiences, and even our identity as the persons who we are. We thus consider this research as a step towards considering game music within a wider context of everyday musical activities and different dimensions of social and personal life. In more general terms, we hope to contribute to generating new discussion that lies in the intersection of player experience and the broader view of music psychology. We believe that studying game music through memories highlights how daily experiences of music are often meshed with and even obscured by the mundane contexts and activities they entangle with. Yet, upon a reflection – such as the participants have provided in their stories – the ‘‘unheard melodies’’ [cf. 89] that accompany video games may incorporate important and memorable experiences in our lives. CRediT authorship contribution statement Kai Tuuri: Writing – review & editing, Writing – original draft, Methodology, Investigation, Funding acquisition, Formal analysis, Conceptualization. Oskari Koskela: Writing – review & editing, Data curation, Conceptualization. Heli Tissari: Writing – review & editing, Methodology, Data curation. Jukka Vahlo: Writing – review & editing, Formal analysis. Declaration of competing interest The authors of this manuscript certify that they have NO affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers’ bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patentlicensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript. Data availability The codes and data that support the findings of this study are available upon reasonable request from the corresponding author. The full data is not publicly available due to consent restrictions by some of the participants. 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