“Next Episode Plays in 3… 2… 1”
Investigating social motivations of binge-watching entertainment media
Filip Klouda
Student ID: 12285897 Master’s Thesis
Graduate School of Communication Master’s programme Communication Science
Under the supervision of: Dr. Ine Beyens 30. 1. 2020
Abstract
This quantitative study explores social motivations of a current trend in entertainment consumption known as binge-watching or watching multiple episodes of a TV show in one viewing session. Three distinct social concepts of social influence, peer pressure and loneliness and their associations with binge-watching behavior are tested through a cross-sectional
questionnaire on a sample of 179 emerging adults from 18 to 30 years of age. The results suggest binge-watching tendencies to be driven by social influence, incorporating the individual’s will to keep up with their social environment (friends, family), current trends in entertainment media and not miss out on important pop-cultural conversation topics. In contrast, binge-watching tendencies are not elevated by higher levels of peer pressure, which means there is no support for the notion of individuals feeling pressured into binge-watching by their surroundings. Further, lonely individuals do not engage in binge-watching more than their counterparts in a state of social ease. The overall results solidify binge-watching as an activity with social significance and meaning, which transcends its mostly solitary nature. As a recommendation for future research, a comparison between the weekly and the “all-at-once” broadcasting strategies is suggested.
Keywords
Binge-watching, social motivations, social influence, peer pressure, loneliness, TV addiction, emerging adults
Introduction
The rise of streaming services across the entertainment industry has substantially changed the way we consume certain audiovisual media (Schweidel & Moe, 2016). It marked a new era of entertainment media consumption, starting by an evolution in TV distribution strategy from a traditional weekly episodic format that’s been in effect for previous decades to a new model that presented the viewers with all episodes of a new TV show at once (Hirsen, 2015). Netflix was the first to embrace this technique by releasing all episodes of the first season of their show House of Cards on their service at once (Zaccone, 2013), but other services soon followed and helped to create a new industry standard of the online streaming business. Thus emerged the phenomenon we understand as “binge-watching” – watching multiple movies or TV show episodes in quick, continuous succession (Schweidel & Moe, 2016). With the rise of subscription-based streaming services such as Netflix, Amazon Prime or HBO Go, binge-watching has become a ubiquitous way of binge-watching entertainment media. According to a
Morning Consult/Hollywood Reporter survey from 2018, 60% of American adults watch at least two TV episodes a week consecutively, with 15% engaging in this behavior every day (Sabin, 2018). A Radio Times poll from 2019 with 5500 responses from the UK estimated that 57% of respondents regularly engage in binge-watching, while about 50% had sometime in the past watched more than 8 hours of television content in one sitting (Glanfield, 2019). As of 2019, Netflix has over 158 million subscribers globally, adding another 6.7 million for the third quarter of the year (Lawler, 2019). In the meantime, new competitors are emerging on the market in the form of new subscription-based streaming services such as Disney+ (Sorrentino & Solsman, 2019) or Apple TV+ (Tambini & St. Leger, 2019), only cementing the current online streaming business as expanding and likely to continue its growth in both revenue and overall subscription
numbers (Forbes, 2019). In this sense, binge-watching is here to stay and will likely be experienced by more people in the future.
Naturally, this relatively newly popularized phenomenon has caught the attention of academic researchers from social or economic sciences. Previous studies done on
binge-watching investigated the role of binge-binge-watching interruption in terms of advertising, discovering that users are less likely to continue the binge-session after being disturbed by ads (Schweidel & Moe, 2016). Other explorations unraveled that the more people perceived binge-watching as a negative outcome of media consumption, the more likely they were to engage in it (Shim, Lim, Jung & Shin, 2018). Outcomes of binge-watching on psychological well-being have been investigated by Granow, Reinecke & Ziegele (2018), concluding that binge-watching can have a positive effect on our psychological state by boosting our perceived autonomy and enjoyment of audiovisual content, but also eliciting feelings of guilt over time lost watching TV and
postponing other necessary tasks in our daily life, which suggests the psychological outcomes to be ambivalent and conflicting. This is in line with the findings of Reinecke, Hartmann & Eden (2014), who posited that consuming media can trigger enjoyment and gratification, while also leading to regret if entertainment overshadows more important responsibilities.
Negative impact of binge-watching sessions has also been suggested in relation to addictive behaviors. The act of binging TV shows has been previously branded as an addicting outcome of on-demand TV consumption (Dvorak, 2013). Further, a positive link has been established between addictive symptoms (e.g., displacement, withdrawal from society) and binge-watching, occurring especially in unplanned binge-watching sessions (Riddle, Peebles, Davis, Xu & Schroeder, 2018). In this sense, binge-watching bears resemblance to other forms of unhealthy media consumption, such as addiction to videogames, where individuals can
experience an inability to stop playing or neglect real-life relationships (Griffiths & Meredith, 2009). Thus, an excessive amount of binge-watching can have long-term repercussions on health or general quality of life (Flayelle, Maurage, Vögele, Karila & Billieux, 2019).
In order to further inquire about the effects and possible outcomes of binge-watching, whether they are positive or negative, we must first understand why viewers engage in this rapid consumption of entertainment media in the first place. This can be done by expanding our knowledge on possible motivations of binge-watching. Previously, general motivations for binge-watching for American college students included escape from reality, easy accessibility and social engagement that incorporated their will to keep up with current trends and be a part of conversations with friends (Panda & Pandey, 2017). This gives us incentive to further explore the social aspects of binge-watching in more detail. This time revolving around the
developmental group of emerging adults, who are often considered to be the most active in terms of binging, with 37% individuals between 18 and 34 years of age engaging in binge-watching on a daily basis (Comscore, 2016). In addition, current academic research on the subject has yet to uncover the role of specific social constructs (e.g. peer pressure) in relation to binge-watching. Therefore, this thesis aims to investigate the associations between binge-watching and three separate social concepts of social influence, peer pressure and loneliness among emerging adults to enrich our current perspective on the matter.
RQ1: What are the main social motivations behind binge-watching among emerging adults?
Further, previous studies framed social influence in a mostly positive light, for instance highlighting the role recommendations of others play in individuals’ binge-watching tendencies (Shim & Kim, 2018). The influence of peers may come in many forms and some of them may be
considered involuntary. Hence, this thesis will also attempt associating binge-watching with the concept of peer pressure, which focuses more on individuals feeling pushed towards certain decisions and behaviors due to the actions of their peers (Cakirpaloglu, Lemrova, Kvintová & Vévodová, 2016). Therefore, the second research question is whether or not peer pressure could be a potential predictor of binge-watching.
RQ2: Do emerging adults engage in binge-watching because of peer pressure? With these newly gained insights, we could identify which social mechanisms enable binge-watching tendencies among emerging adults, leading us to a better understanding of how to tackle its potentially harmful outcomes, such as binging addiction (Riddle et al., 2018) or worsened psychological well-being (Flayelle et al., 2019).
Theoretical framework and hypotheses Theoretical framework of binge-watching
The desire to consume multiple episodes or movies in a short period of time has long been the subject of study by entertainment and media researchers. It can be categorized as a binge behavior, similar to binge-eating or binge-drinking, which are often considered addictive behaviors (Gold, Frost-Pineda & Jacobs, 2003). The characteristics of binge-behavior include a certain (often extreme) devotion to a specific activity that is done for a long period of time (Sung, Kang & Lee, 2018). With binge-watching, this can be explained by the users being
engaged with the content they are currently consuming (Pang, 2014). This is intertwined with the concept of transportation, where individuals become fully engaged with the narrative world they are currently occupying (Green, Brock & Kaufman, 2004). In this state, viewers can experience distancing themselves from the real world or not being aware of other people’s presence in the
room due to feelings of full immersion in a fictional world (Sung, Kang & Lee, 2018).
Consequently, this can lead to stronger enjoyment of the medium (Green et al., 2004). This is closely tied to a state of “flow”, which suggests the viewers give their full cognitive investment into watching TV, which results in lowered attention to external stimuli (Hoffman & Novak, 1996). As a result, individuals can get addicted to watching television and experience prolonged viewing times and problems with stopping (Kubey & Csikszentmihalyi, 2002). Panda & Padney (2017) later posited that an interruption of flow can negatively impact the viewer’s psychological state and prompt them to engage in binge-watching in the near future. Hence, binge-watching could be considered a repeating process of excessive consumption of audiovisual media that is unlikely to be experienced just once.
Other explanations of this phenomenon utilize a more user-centered approach, such as the uses and gratifications theory, stating that users seek out certain media that satisfy their specific expectations and needs (Katz, Glumler & Gurevitch, 1974). This is often used to pinpoint motivations that lead individuals to concrete media use (Shim & Kim, 2018). However, contrary to traditional television watching, streaming sites give users complete control over what type of content they watch and when, which means that some of the motivations for binge-watching are very likely to be completely new and unrelated to previous consumption of audiovisual media (Vaterlaus, Spruance, Frantz, & Kruger, 2018).
Motivations behind binge-watching
Initial explorations of motivations behind binge-watching identified many potential reasons why emerging adults would produce such behavior. Among emerging adults, some reasons were purely hedonistic, suggesting enjoyment or entertainment to play a significant role in choosing to watch a TV show in quick sequence (Shim & Kim, 2018; Sung et al., 2018).
Entertainment isn’t strictly tied to just having fun, but includes other characteristics of binge-watching, such as the user’s increased level of control that allows them to replay their favorite shows at will for pleasure or to prepare for the premiere of new episodes (Flayelle, Maurage, Billieux, 2017), which once again ties to the notion of binge-watching allowing for bigger user autonomy (Granow et al., 2018).
Combining socio-cognitive and marketing aspects, Panda and Pandey (2017) found four areas of motivation among American college students, namely social engagement, escaping from reality, advertising and easy accessibility. Social engagement was the strongest predictor,
highlighting the importance of binge-watching as a social experience that holds value for further conversations and relationships among peers or a need to belong to a specific social group. This is suggested to be partially caused by emerging adults experiencing a fear of missing out
(FoMo), causing them to fear they won’t be able to contribute to the conversations of their friends and share their experiences with entertainment (Conlin, Billings & Averset, 2016). For instance, it can lead individuals to organizing co-viewing binging sessions, where friends gather to watch a particular TV show in one instance (Dandamudi & Sathiyaselaan, 2018). Since this is seen as a group activity, individuals typically don’t experience a sense of guilt because they see it as meaningful time with their peers (Feiereisen, Rasolofoarison, De Valck & Schmitt, 2019). On the other hand, binge-watching is also often experienced in solitude (Flayelle et al., 2017), which could consequently negatively impact social skills when done in excessive amounts (de Feijter, Khan & van Gisbergen, 2016). In the case of college students, binge-watching was perceived to be the cause of decreased communication with friends and an increase in emotional distance from family (Vaterlaus et al., 2018). This brands binge-watching to be a specific activity
with a complex duality of being both social and solitary, with distinguishing implications for both concepts.
While exploring motivations for binge-watching, it was previously discovered that social reasons for binge-watching were significantly linked with planning co-viewing sessions in advance, emphasizing the importance of binge-watching as a social event (Pittman & Sheehan, 2015). Additionally, social engagement is the biggest motivator to binge-watch among American students, underlining the importance of recommendations of others and avoiding exclusion from social groups (Panda & Padney, 2017). In this sense, individuals being influenced by their social circle could be engaging in binge-watching because they feel the need to meaningfully contribute to their social circles. This later translates into engaging in pop-cultural conversations with friends or understanding when someone mentions or jokes about a particular TV show/movie (Vaterlaus et al., 2018). Therefore, based on previous findings on social aspects influencing binge-watching, we expect that:
H1: Individuals who are more socially influenced are more likely to binge-watch than individuals who are less socially influenced.
Peer pressure
But social influence doesn’t strictly need to be of positive nature. What may start as a friendly encouragement, can evolve into peer pressure, with both positive and negative impact (Calvó-Armengol & Jackson, 2010). In academic research, the impact of peer pressure is often explained by the workings of the social learning theory (Bandura, 1977), which assumes that individuals learn new behaviors by observing and imitating other humans, often with a specific social context. In this sense, peer pressure is explored in relation to substance use. For instance, adolescents experiencing peer pressure were more likely to drink alcohol (Kung & Farrell,
2000), use illegal substances (Simons-Morton, Haynie, Crump, Eitel & Saylor, 2001) and smoke (Kiran-Esen, 2003). Therefore, it is considered a risk factor for further substance use (Scull et al., 2010). Additionally, peer pressure has been identified as a predictor of compulsive technology use, such as browsing the internet or using social media (Balogh, Mayes & Potenza 2013).
Among adolescents, the impact of peer groups plays a substantial role in subsequent media use, including television watching (Nathanson, 2001). In this developmental period, individuals are also drawn towards consuming the same media as their peers because it may elevate their status with them (Suess et al., 1998). Especially if associating with a particular peer group inspires adolescents to consume the same media popular within the group (Arnett, 1995). This could continue into emerging adulthood, where socializing is one of the reasons for
engaging with media (Coyne, Padilla-Walker & Howard, 2013). For instance, when a particular TV show is really popular and everyone in their social circle already watched it, emerging adults could engage in binge-watching due to being pressured into it by their peers. This thesis will therefore extend the previous findings on adolescents to emerging adults. Even though susceptibility to peer pressure generally weakens with age (Gardner & Steinberg, 2005), individuals in this period are often still developing and exploring their identity, opinions, and lifestyles (Arnett, 2006; Waterman, 1999). Their media use preferences are also often considered unpredictable and unstable (Arnett, 2006). Considering the previous findings regarding peer pressure and media use, we hypothesize that individuals being peer pressured into binge-watching will be more likely engage in such consumption than their counterparts.
H2: Individuals who experience higher peer pressure are more likely to binge-watch than individuals who are being less peer pressured.
Social circles may influence our entertainment consumption habits even if they are severely lacking in our lives. More specifically, feelings of loneliness could alter how much content we decide to consume if we’re left out from our social environment. Loneliness has been detailed as a negative experience of feeling alone due to a lack of company or perceived isolation from family and friends (Weiss, 1973), which can be caused by the individual’s varying
perception of current social relations and their preferred social relations (Peplau & Perlman, 1982). Over the years, researchers have tried to investigate the relationship of loneliness with media use, most importantly television watching. According to Rook and Peplau (1982), about 60% “sometimes” use TV for relieving loneliness, while about 34% do it “often”. In addition, it was previously established that certain individuals regularly use TV watching as a tool for
conquering loneliness (Eggermont & Vandebosch, 2001). TV shows also seem to have a stronger impact on relieving individuals from loneliness than listening to music or browsing online, and individuals often keep returning to their favorite shows to raise their mood (Derrick, Gabriel & Hugenberg, 2008). In relation to binge-watching, the role of loneliness tendencies remains to be inconclusive, presenting two clashing perspectives. While some studies demonstrated that a lonely individual tends to watch more TV show episodes in one sitting (Sung, Kang & Lee, 2015), other explorations presented opposing results, disproving the connection of loneliness to binge-watching behavior (Ahmed, 2017). Nevertheless, solving mental health issues was
identified as the second biggest motivator for binge-watching among college students in a recent qualitative content analysis (Vaterlaus et al., 2018), with some individuals specifically
mentioning binge-watching as a way to avoid feelings of loneliness. Hence, based on previous quantitative and recent qualitative explorations in the field, it is hypothesized that:
H3: Individuals with higher levels of loneliness are more likely to binge-watch than individuals with lower levels of loneliness.
Methods
Procedure and sample
This study was devised around an online cross-sectional survey made with the Qualtrics survey software. The decision to commit to a cross-sectional time frame was made with financial limitations and time constraints in mind. We were also looking to determine associations
between three specific binge-watching motivations (peer pressure, loneliness and social influence) and binge-watching tendencies at a single point in time, which is why a cross-sectional survey was a satisfactory fit. The survey was distributed online and primarily through social media channels (Facebook and Instagram), to individuals in the proposed target group of emerging adults (18 to 30 years of age). On both social media channels, mainly the researcher’s social circle was reached, which included many potential participants of this age. Participants were expected to complete the survey individually and report on all measured concepts. At the start of the questionnaire, all participants were presented with a form of consent to confirm their answers were being used for research purposes only and were treated with the utmost
confidentiality.
Considering the design characteristics of this research and its dependency on recruiting participants on social media, the sampling method chosen for this study was non-probability convenience sampling. While collecting data for the research, the survey was targeted towards emerging adults between 18 and 30 years of age. Anyone above or below the targeted age range was filtered out at the beginning of the survey. In addition, survey responses with less than 89%
of items answered were treated as incomplete and were excluded from data analysis. 89% of completion was chosen as the threshold for acceptability for analysis because it includes all necessary measures, missing only the participant’s choice of NGO for a donation. There were no further exclusion criteria. As incentive for participation, the participants could vote for their preferred non-profit organization that would receive a 50 Euro donation at the researcher’s expense. The selection included 8 non-profit organizations (e.g. UNICEF, Hong Kong Free Press, Amnesty International, NFNZ), with UNICEF emerging as the winner (36.6%).
While the sample may not be representative of the population given its non-probability nature, the study aimed to provide an international sample of individuals of different
socioeconomic and cultural backgrounds. This was fulfilled by sampling not only from people closest to the researcher (social media contacts), but also expanding the pool of participants by drawing from social media fan groups and enthusiast forums of movies and TV shows. This included sending out the survey to users of local Czech movie and TV show forums
Moviezone.cz and Edna.cz, as well as distributing it in international fan forums Letterboxd and Resetera. In these groups, potential participants were expected to be fans of TV shows and movies who often engage in entertainment media consumption, therefore perhaps proving to be more relevant to the research topic. An additional number of participants was also found through Facebook groups for quantitative research and the service SurveySwap, which allows university students around the world to share their research in an international community of students.
Before data collection, a pilot version of the questionnaire was created to provide an initial test of all items and possible factors. The pilot survey was completed by 21 individuals. It helped at establishing the final appearance of all items and led to a switch of measurements for binge-watching. Originally, binge-watching was measured with a specific number in hours
determining either high or low levels of watching (Sung et al., 2018). In the end, a binge-watching tendencies scale by Granow et al. (2018) was utilized particularly due to focusing on binge-watching tendencies and behavioral urges for rapid consumption of media, which aligned more closely with the aim of our research.
The final version of the survey received 265 responses in total, including incomplete responses. After filtering out all participants above the age limit and deleting incomplete cases, 179 responses were used for the final data analysis. 53.1% of the sample identified as female, 43% as male, 1.7% as non-binary, while 2.2% of people preferred not to disclose their gender. Overall, a respectable representation for all groups was achieved, with two main gender groups approaching equality. The mean age of participants was about 24 years (M = 24.32, SD = 2.67). In terms of nationality, most participants reported being from the Czech Republic (28.4%), followed by individuals from the Netherlands (13.1%), Germany (10.2%) and the United States (8.0%). Further, the majority of our sample were university students (50.3%) or students
currently working in a part-time job (31.8%), while a smaller portion was occupied by sole workers (16.2%). Finally, 56% of sampled individuals reported being single, 41% noted being in a relationship and 3% were married.
Generally, the most used streaming services across our sample was Netflix (85.7%), which proved to be a near ubiquitous source of audiovisual entertainment among emerging adults. With considerable distance, other services used by our respondents included HBO Go (23.6%), Amazon Prime Video (22%), Youtube TV (17%), Disney+ (10.4%) and the anime streaming channel Crunchyroll (7.7%). Our respondents’ preferences varied dramatically across the spectrum of TV show genres, with many examples of shows listed in the survey, for instance Netflix’s Atypical, BoJack Horseman and The Crown or HBO’s Chernobyl, just to name a few.
Measures
Independent Variables
Social influence. Social influence was measured with a 9-item scale, which utilized items from two pre-existing scales used in previous research on binge-watching motivations,
specifically from Shim and Kim (2018) and Panda and Pandey (2017). In this research, three items measured recommendations of others and “word of mouth” as possible motivators of binge-watching. Two such items stated: “I engage in binge-watching because: I heard some TV shows were just fun to binge.” or “My friends recommended me a must-see TV show.” The six remaining items focused on social influence that treats binge-watching as a tool of socialization, contributing to a specific community and influence by peers. One example item included: “I engage in binge-watching because: I don’t want to feel excluded from my social group.” All 9 statements were measured on a 7-point Likert scale balancing between “totally disagree” and “totally agree.” A factor analysis with the method of principal axis factoring (Direct Oblimin rotation) was conducted to consider data reduction and explore factor loadings on all items. Sampling adequacy was substantially high (KMO = .92), with Bartlett’s test of sphericity being equally satisfactory, χ2 = 1251.73, p < .001. A single factor with an Eigenvalue above 1 was extracted, which explained 66.76% of total variance. Consecutively, all items achieved a Cronbach’s alpha of .94, implying a very solid reliability of measurement. Responses were averaged to create a social influence scale using the mean index in SPSS (M = 3.20, SD = 1.45). Higher scores were indicative of greater social influence.
Peer pressure. This scale was adapted from a pre-existing measure validated by Santor et al. (2000). The scale originally focused on adolescents but was conceptually adapted to this research and any youth-specific phrases were either altered or removed. In its final form, the
scale contained 8 items to measure peer pressure in regards to binge-watching. All statements were measured on a 7-point Likert scale balancing between “totally disagree” and “totally agree.” One example item included: “My friends could push me into just about anything.” A subsequent factor analysis was favorable in terms of sampling adequacy (KMO = .83) and Bartlett’s test of sphericity (χ2= 562.50, p < .001). In this case, factor analysis identified two factors, the first explaining 48.86% of the variance, while the second explained about 15.17%. However, we decided to keep it as one self-contained concept of peer pressure for purposes of this study. When the factor analysis was conducted a second time, after setting the limit of extracted factors to one, factor loadings for all items were between .52 and .71, confirming to be satisfactory as a unified scale. In this study, the scale reached a Cronbach’s alpha of .85,
confirming its use for further analysis. An average of all scores was created in SPSS (M = 2.68, SD = 1.06). Higher values signified individuals beingly more strongly affected by peer pressure.
Loneliness. Loneliness was measured through the UCLA loneliness scale (Russell, 1996), which was shortened to condense the size of the survey, but its specific wording remained the same. The altered scale included 10 items. It also incorporated a 7-point Likert scale ranging from “totally disagree” to “totally agree”, which differentiated from the original 4-point scale. As an example, one question stated: “I feel isolated from others.” An exploratory factor analysis unraveled all key components of the measure in check (KMO = .93, χ2 = 1618.82, p < .001), as well as only identifying one factor accountable for 70.52% of the variance. All items combined scored α = .95 on the reliability test, confirming the construction of a reliable scale. An average of all items was computed in SPSS (M = 2.84, SD = 1.45), greater values indicating greater levels of loneliness.
Items for all independent variables are included in Appendix A to increase replicability of the study.
Dependent variable
Binge-watching frequency. In this study, we use the definition of binge-watching
proposed by Pittman & Sheehan (2015), identifying binge-watching as an act of watching two or more TV episodes (or two or more movies) in quick, continuous succession. Our measure of binge-watching frequency was adapted from an existing scale used by Granow et al. (2018). The KMO test of sampling adequacy on this measure was successful (KMO = .84), as was the Bartlett’s test of sphericity χ 2
(10) = 674.59, p < .001. Further, only one factor was extracted, which explained 69.73% of the variance. The questions aimed to measure the behavioral tendencies and attitudes towards engaging in binge-watching, which were found to be
substantially high in this sample (M = 4.63, SD =1.51). One item (“When I watch a TV show, I prefer to watch 1 episode at a time.”) had to be reverse coded due to lower values actually implying an increase in binge-watching behavior, not a decrease. After recoding, the scale achieved a solid Cronbach’s alpha of .88. Additional questions were asked about the
respondents’ preferred streaming services and the last show they remember binge-watching, as a way to further explore binge-watching tendencies.
Control variables
TV watching frequency. This measure is adapted from a scale introduced by Lee, Hornik and Hennessy (2008), which was later altered and utilized by Kühne and Opree (2019). It
determines participants’ average amount of time spent watching TV offline and online during the week. However, instead of differentiating between weekdays and weekends, the participants
were asked to list the approximate number of hours spent watching TV content per the whole week. On average, the participants watched about 11 hours of TV content weekly (M = 11.19, SD = 8.74).
Multiple demographic details were collected as additional control variables, including age, gender, nationality, current occupation (e.g. student, working, working student) and relationship status (e.g. single, in a relationship, married).
Table 1: Descriptive statistics of key independent and control variables and the dependent variable of binge watching.
Variable (N = 179) M SD Binge Watching Overall TV Watching Social Influence Peer Pressure Loneliness Age 4.63 11.19 3.21 2.68 2.84 24.32 1.51 8.74 1.45 1.06 1.45 2.67
Notes: All variables measured on a 7-point Likert Scale from 1 (Strongly Disagree) to 7 (Strongly agree).
Results
As an initial indicator of results, we explored the variables by conducting a correlational analysis. We discovered that binge-watching tendencies are positively moderately correlated with overall weekly amount of time spent watching TV (r = .35, p < .001). Thus, respondents
who spent more time in a week watching TV also had higher tendencies to binge-watch certain programs. Moreover, binge-watching also produced a positive moderate association with social influence (r = .31, p < .001), uncovering that more socially influenced individuals had increased tendencies for binging TV shows. Additionally, social influence was also expectedly strongly positively correlated with peer pressure (r = .67, p < .001), explaining that individuals more influenced by their social environment also reported an increased amount of peer pressure in their lives. Lastly, loneliness was surprisingly weakly positively correlated with social influence (r = .16, p < .005) and peer pressure (r = .25, p < .001), suggesting an increase in feelings of loneliness for both socially influenced and peer pressured individuals.
Hypothesis testing
In order to test the pre-set hypotheses (H1, H2 and H3), a hierarchical multiple regression was conducted to analyze and compare two models of binge-watching tendencies with and without our predictors of social influence, peer pressure and loneliness. The first model consisted exclusively of control variables of overall TV watching, age, gender and relationship status. For the latter two covariates, dummy variables were created to incorporate multiple categories into a linear regression model. Overall, the first model was significant F(7, 171) = 5.10, p < .001, while the covariates explained about 18% of the total variance. From the initial model, we can already observe significant results for a few of the variables. For instance, overall TV watching
positively predicted binge-watching (B = .06, SE = .01, t = 4.80, p < .001), only by a slight margin, with moderate strength (b* = .34). This indicates that watching more television content leads to a small increase in likelihood of engaging in binge-watching. Further exploration of the results also uncovered an interesting disparity in binge-watching tendencies between men and women. According to our first regression model, men were significantly less likely to
binge-watch than women (B = -.64, SE = .23, t = -2.83, p = .005). A more in-depth investigation of how binge-watching behaviors differ between genders could therefore uncover interesting developments when it comes to preferences for entertainment consumption among emerging adults. No other differences in how binge-watching relates to individuals of varying relationship status, age or gender were found.
The second model added all independent variables required to test our hypotheses. The regression model was also significant F(10, 168) = 6.05, p < .001, with 27% of the variance in the model explained by all the variables combined (R2 = .27), implying the remaining three predictors added an additional 9% of variance (ΔR2 = .09).
Hypothesis 1 posited that an increase in social influence would lead to higher tendencies to binge-watch entertainment. As expected, social influence positively predicted binge-watching (B = .39, SE = .09, t = 4.16, p < .001), while the effect itself was moderate in strength (ß = .37), with 95% confidence intervals estimating the increase in binge-watching between .20 and .57. This confirms our assessment that participants experiencing the influence of their social circles are more likely to binge-watch audiovisual content, thus corroborating H1.
Hypothesis 2 suggested that individuals experiencing high levels of peer pressure in their social environment would be more likely to turn to binge-watching when consuming
entertainment. When we looked at results in our regression table, there didn’t seem to be a relation of peer pressure to binge-watching tendencies (B = -.19, SE = .13, t = -1.47) due to statistical insignificance (p = .144). Therefore, there is no support for the notion that highly peer pressured individuals would engage in binge-watching more than people with lower levels of peer pressure. Hence, H2 is rejected.
Hypothesis 3 proposed that loneliness, often associated with feelings of isolation and helplessness, would boost tendencies to binge-watch certain shows or movies, further cementing binge-watching as a solitary activity. However, the current results cannot provide a definitive answer. Loneliness produced a statistically insignificant association with binge-watching (B = .08, SE = .08, t = .98, p = .330), declaring there to be no connection between the two concepts. Hence, H3 couldn’t be supported.
In terms of associations established in the first model, there were only very minor
changes to unstandardized coefficients in both cases. After the inclusion of our main predictors, a slightly smaller increase of binge-watching tendencies for heavy watchers of TV was found out (B = .05). In a similar way, men were slightly more unlikely to bingewatch than women (B = -.69). All remaining changes can be observed in Table 2.
Table 2: Models 1 and 2 of multiple regression predicting binge-watching tendencies (N = 179). Binge-watching tendencies Model 1 Model 2 B B Constant 4.08*** 3.61** Age 0.01 0.00 Gender – Male -0.64** -0.69** Gender – NonBinary -.48 -.66 Gender – Undisclosed -1.39 -1.32 Single -0.08 -0.31 Married 0.04 -0.13 Social Influence 0.39*** Peer Pressure -0.19 Loneliness 0.80 Overall TV Watching 0.06*** 0.05*** R2 0.17 0.27 F 5.10*** 6.05*** ΔR2 0.09 ΔF 0.95*** Notes: * p <.05. ** p <.01. *** p <.001.
Variables „In a relationship“ and „Gender – Female“ kept as reference for dummies included in the model.
Discussion
The aim of this study was to inquire about various social motivations for the rapid media consumption phenomenon known as binge-watching. Previous research investigating these relationships pointed towards binge-watching being a substantially complex activity, possessing features of both solitary and social entertainment. An individual can engage in binge-watching out of many hedonistic motivations, such as enjoyment, relaxing, escape from reality (Flayelle et al., 2017), either alone or with company. Further, considering binge-watching as a social event for friendly or family gatherings adds another layer to the current pool of behavioral motivations
(Pittman & Sheehan, 2015). In this sense, it was our goal to further investigate social aspects and the relationships binge-watching holds with concepts of social influence, loneliness and peer pressure.
The results unraveled a positive connection between binge-watching and social influence, leading us to believe that individuals can engage in an excessive consumption of entertainment media due to the influence of their social environment, confirming the findings of Panda and Padney (2017). This includes expected factors of recommendations from peers or family, contributing to a specific social space (groups of friends, romantic relationships), reacting and adapting to newest trends in entertainment media, or avoiding exclusion from a specific social group due to being out of touch with currently airing TV shows and movies. Therefore,
individuals engage in binge-watching not only in order to relax (Vaterlaus et al., 2018) or have fun (Shim & Kim, 2018), but also to appeal to certain social norms created by the environment around them. In addition, tendencies to binge-watch entertainment may also be elevated by the individual’s perception of how their social circle expects them to consume media. While peer recommendations and word-of-mouth in popular media may play a vital role in considering binge-watching, we shouldn’t underplay the possibility of binge-watching being a societal expectation among current emerging adults.
In a similar vein, the relationship between binge-watching and peer pressure was examined, essentially highlighting the possible negative sides of social influence, focusing on involuntary social encouragement to engage in media consumption or feelings of pressure to catch-up on certain TV shows and movies. However, this connection was not confirmed by the results. What’s a bit more surprising – the results hinted at a negative (albeit insignificant) trend, suggesting that peer pressure may actually decrease tendencies to binge-watch, despite social
influence hinting at the opposite. A possible explanation of the result could be that an overt emphasis on recommending certain programs actually turns away individuals from engaging in binge-watching, especially if they feel pressured by their peers to watch them. It must be noted that the overall levels of peer pressure in our sample were fairly low, possibly due to the fact that peer pressure slowly disappears with adulthood (Gardner & Steinberg, 2005). It is also important to consider the wording of peer pressure items in this study as a possible factor of the results. Only 3 out of 9 items were related to binge-watching, while the remaining 6 tied more closely to general peer pressure experienced in real-life situations outside of entertainment activities. Nevertheless, we cannot yet disprove the existence of an association between peer pressure and binging behavior. Different results may be produced while investigating this phenomenon in environments more prone to peer pressure (e.g. high school) and with a different age group, such as young adults or adolescents.
In terms of binge-watching and loneliness, our findings failed to establish a link between the two. This further supports the findings of Ahmed (2017) and stands in stark contrast to the findings of Sung et al. (2015). The role of loneliness in binging behavior remains inconclusive, yet this study serves as an indicator of loneliness playing a limited to minimal role in binge-watching television. This comes as a mild surprise after a history of positive relations of
individuals’ loneliness to watching television (Eggermont & Vandebosch, 2001) and returning to favorite TV shows as a way of coping with isolation or mood swings (Derrick et al., 2009). The differentiating results highlight the contrast between binge-watching and regular TV watching, which should be treated as separate concepts of entertainment consumption, each with their specific motivations and outcomes.
Combining the results of all three concepts, we can see a narrative forming in favor of binge-watching being a more social activity than originally suggested, with elements pointing towards a solitary activity being diminished, as well as individuals not perceiving
binge-watching as a forced activity they’re pressured into, but rather encouraged by their social circles. This could be crucial in understanding why binge-watching is currently as omnipresent in the modern world. Despite individuals sometimes anticipating feelings of guilt over a long binge-watching session (Walter-Pattison et al., 2016), treating binging TV shows as a social event of sorts (even if performed alone) could in turn designate that time as socially meaningful. Especially if it means discussing plots and twists of TV shows with friends, checking live reactions on Twitter or engaging in online debates on TV show forums.
It is only fair to assess some limitations of this study. First and foremost, this study only utilized a cross-sectional survey, which makes inferences of specific effects and their directions impossible. Similarly, any claims of causality aren’t viable. Therefore, the presented research serves primarily as groundwork for upcoming studies that could introduce methods of
experimentation or conduct their testing over a longer period of time with multiple points of exposure to examine changes over time (e.g. a longitudinal study). Another option is to consider using newer methods of tracking media users such as experience sampling with event-based contingency, where participants would fill out a short questionnaire every time they experienced a binge-watching session. Typically, implementing this research method leads to bigger
ecological validity, considering the real-life setting of all measurements, and reduction in memory bias, which often plagues self-reporting in questionnaires (Scollon, Kim-Prieto & Diener, 2003).
Further, due to non-probability sampling being the main method of recruiting participants for this study, we’re unable to draw generalized conclusions to a wider population. Despite obtaining an international and substantially diverse sample, participants were mostly recruited through related social circles, movie websites and discussion forums through invitation letters without any element of randomness. In addition, as seen in the Methods section, most of the sample consisted of students (50.3%) or working students (31.8%), leaving workers (16.8%) to be a bit underrepresented. In other words, students (with part-time jobs or not) were a
predominant entity in the sample (82.1%), thus suggesting that the sample may have been skewed towards one particular demographic group. Binge-watching research is often conducted with university students (Dandamudi & Sathiyaselaan, 2018; Panda & Padney, 2017), often due to easy accessibility. But in this case, students may be more prone to binge-watch due to not yet fully accustoming themselves to adult life and operating with more robust time options.
Especially when timing and personal scheduling are taken into account as one of the main factors of length in a binge-watching session (Riddle et al., 2018). Therefore, individuals with more limited time possibilities might tell a different story. Emerging adulthood is a transitional period where the lines between studying and a steady working occupation may often be blurred, but future research should aim for an even distribution of occupations or focus on a different subgroup within emerging adults to help fill the blank spots in our current knowledge of the subject.
Similarly, we must not forget the impact of social desirability when conducting survey research, as the questionnaire included personal themes of loneliness and peer pressure, which could prompt some users to answer in a more favorable way. We cannot deny this possibility, since the means of both concepts were considerably low in our sample, loneliness (M = 2.84, SD
= 1.45) and peer pressure (M = 2.68, SD = 1.06), respectively. Self-reporting presents certain dangers to validity of the study, which could be alleviated by an experimental approach.
In the future, a handful of streaming services are contemplating the idea of returning to a more traditional broadcasting schematic of airing episodes weekly. For instance, Apple TV+ releases some of its shows all at once and others in a weekly manner (Maas, 2019). The current streaming service frontrunner, Netflix, was experimenting with weekly releases in the fall of 2019 (Schomer, 2019). Although Netflix doesn’t currently plan to alter its business model of releasing whole seasons of shows at once (Radulovic, 2019), other services will be more likely to do so, as is the case with Apple TV+ and the upcoming HBO Max (Burch & Baysinger, 2019). Since binge-watching was often labeled as a direct product of Netflix’s release strategy, future research could focus at the differences in binge-watching motivations and outcomes across multiple streaming services, which dynamically vary in content roll-out. While some
characteristics of binge-watching may be identical among all services, such as easy accessibility of content and increased autonomy of the user, we may observe shifts in tendencies to
excessively consume content, if there are changes to pacing its release. This way, future research can further explore the unique role that simple business strategies play in consumer behavior in terms of (addictive) consumption, enjoyment and motivations to watch more than a single episode at a time.
Conclusion
This thesis interlinked three relevant social concepts of social influence, loneliness and peer pressure with a currently surging trend of binge-watching TV shows and movies on streaming services among an international sample of emerging adults. According to the results, individuals with higher levels of social influence are more likely to binge-watch entertainment content, which further emphasizes how our social environment can impact our behavior and decision-making as consumers of entertainment. Willingness to engage in group discussions and avoidance towards missing out on conversations likely play a substantial role in increasing the likelihood of watching certain television content in rapid succession. While peer pressure was a newly introduced concept, not yet covered by the literature in relation to excessive consumption of TV among this developmental group, its association with binge-watching couldn’t be
established within this study. Similarly, binge-watching wasn’t confirmed to be an activity favored by lonely emerging adults. Thus, the study provides evidence pointing in favor of categorizing binge-watching as a social activity, rather than strictly lonesome. In this sense, people who value their position within their social group and want to contribute to it, are more likely to quickly consume TV content, and subsequently proving to be more susceptible to both positive and negative outcomes of binging entertainment.
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Appendix A: Items for all independent and dependent variable measures
Binge-Watching Tendencies (Granow et al., 2018)
1. I often watch multiple episodes of one series in a single session.
2. Binge-watching, where I watch 2 or more episodes of a TV show in a single session, is typical for me.
3. Typically, I watch TV shows straight from first to last episode. 4. When I watch a TV show, I prefer to watch 1 episode at a time. 5. I binge-watch a lot.
Social Influence (Panda & Padney, 2017; Shim & Kim, 2018) I engage in binge-watching because:
1. It makes me feel like a part of a group. 2. I want to contribute to my social group.
3. I don’t want to feel excluded from my social group. 4. My friends suggest that I do it.
5. My friends expect me to do it. 6. My friends do it.
7. I heard some TV shows are just fun to binge.
8. My friends recommended me a must-watch TV show. 9. I want to see that show everyone is talking about right now. Peer Pressure (Santor et al., 2000)
1. My friends could push me into just about anything. 2. I give into peer pressure easily.
3. If a close group of people would ask me to do something, it would be hard to say no. 4. At times, I’ve done dangerous or foolish things because others have urged me to. 5. I often feel pressured to do things I wouldn’t normally do.
6. If my friends are watching a TV show, it would be hard for me to resist binge-watching the same show.
8. I’ve felt pressured to catch up on a TV show because a lot of people from my social circle watch it.
Loneliness (Russell, 1996) 1. I feel alone.
2. I lack companionship (friend, partner, family). 3. There is no one I can turn to.
4. My interests are not shared by those around me. 5. I feel left out.
6. I feel isolated from everyone else. 7. People are around me but not with me. 8. I have no one to talk to.
9. No one really knows me well. 10. It is difficult for me to make friends.
