Assessing the social media landscape: Online relational use-purposes and life satisfaction among Finns
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Assessing the social media landscape: Online relational use-purposes and life satisfaction among Finns by Teo Keipi, Ilkka Koiranen, Aki Koivula, and Pekka Rasanen



Abstract
This study examines the social Internet use-purposes of Finns along with links to perceived life satisfaction. Here, associations between life satisfaction and various online behaviors linked to socialization are explored among the Finnish adult population, sigh data coming from nationally representative surveys focused on adult populations in Finland (N=1,600). Analysis shows that social media use is linked to both higher and lower levels of overall life satisfaction with differences between platforms used. The use of Instagram and different social messaging applications, such as WhatsApp, was linked higher life satisfaction while Facebook and Twitter use did not show any significant association; notably, Internet forum use showed a negative association with life satisfaction.

Contents

Introduction
Life satisfaction and the social Internet
Similarities and differences across social media platforms
Research design
Data and methods
Results
Discussion
Conclusion

 


 

Introduction

Individuals’ life satisfaction continues to be a central component in research concerned with assessing ideal conditions for societal health through individual fulfillment (Schiffrin and Nelson, 2010; Proctor, et al., 2009). The positive emotions commonly associated with having a sense of happiness contribute to relationships, health (Lyubomirsky, et al., 2005) and task performance, and ultimately overall life satisfaction (Gamble and Gärling, 2012; Uusitalo-Malmivaara, 2012). Individual life satisfaction is indeed closely linked to both personal capability and relational factors; notably, those living in Western societies increasingly carry out fundamental aspects of daily life that contribute to well-being online, especially in countries leading in technological integration such as Finland (Lindblom and Räsänen, 2017). Here, how the Internet is used facilitates task performance and socialization according to individual preferences.

The social and expressional component of the online experience is encapsulated by social media, which has become central to interaction in the Western world. Social media are comprised of various platforms including content-sharing sites such as Instagram or online text-based forums and social networking sites such as Facebook. Notably, these platforms are each structured uniquely to facilitate specific use-purposes. Whereas Facebook is more focused on social network management, interaction and communication, Instagram facilitates self-presentation and taste expression (Phua, et al., 2017; Sheldon and Bryant, 2016). Various text-based platforms fall between the two, where users carry out self-expression either with or without an associated platform based social network. Furthermore, these platforms afford users with various tools to maintain, discover and reinforce both strong and weak social ties in unique ways (Keipi, et al., 2017; Phua, et al., 2017). As such, social media can be used in any number of ways to seek out experiences that might bolster well-being and life satisfaction as a whole (Lönnqvist and Itkonen, 2014; Kim and Lee, 2011).

Although unequal access to technology has lessened a great deal in countries leading in consumer technology adoption, variances in use-purposes and social media platform navigation exist. Indeed, the ways in which social media are used can reveal a great deal about personal preferences in terms of visibility, identifiability and modes of socialization online. As such, Finland represents a particularly interesting case due to being a nation where global technology use trends are set and platform adoption and innovation are high (see Keipi, et al., 2017; Vicente and López, 2011). Associations between demographic factors and certain use purposes can also offer new insight into possible disparities, especially when combined with the life satisfaction of various population groups. This study is focused on bringing new understanding to these important areas of research through the perspectives of the Finnish population and its online social media behavior.

In this paper, we assess the relational Internet use-purposes of Finns to highlight the existing variances between social media platform use and life satisfaction. While the actual research problem is not entirely novel, this article offers a new approach to existing literature by comparing several different social media applications simultaneously, which in turn provides an interesting contrast due to platform differences. In addition, the included life satisfaction measure, termed “overall life satisfaction” is particularly comprehensive, consisting of happiness, life satisfaction and self-esteem. The implementation of this combined measure allows for an added perspective on how social media use is associated with overall life satisfaction for various population groups. In addition, we take into account the possible associations that online activities have with off-line social relations.

 

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Life satisfaction and the social Internet

Central to our assessment of social use-purpose associations is life satisfaction, which is linked to subjective assessments of personal well-being (Diener, 1994; Diener, et al., 1999). In social sciences, there are several compelling traditions in the field that substantially deviate from each other on their respective theoretical and methodological foundations. In most approaches, however, the structure of well-being is made up of three primary areas, and its assessment involves a gauging of emotional responses made up of positive and negative affect, and judgment of life satisfaction (Proctor, et al., 2009; Schiffrin, et al., 2010; Demir and Özdemir, 2010). Notably, these components of well-being can overlap extensively. Although this overlap complicates the assessment of well-being, each component is a valuable contributor to an accurate understanding of happiness (Diener, et al., 1999). Here, positive evaluations of life satisfaction, an overall assessment of one’s quality of life, point toward a state of happiness while negative evaluations of life satisfaction are associated with depression, for example. Affect here refers to moods and emotions that represent individual evaluations of some life event or circumstance (Oishi and Diener, 2001). Examples of positive affect include joy, affection, happiness and even ecstasy. Negative affect is comprised of instances of guilt or shame, sadness, anxiety or stress, and depression or envy (Diener, 1996). These affects interact in the area of satisfaction, namely overall life satisfaction.

In past research, several material and subjective emphases on well-being have been put forth (Kouvo and Räsänen, 2015). For instance, it has been argued that material circumstances create different well-being possibilities. According to that approach, life satisfaction is not so much a result of an individual’s own evaluation, but of different structural circumstances whose effects are observable. In contrast, others argue that individuals’ own evaluations are relevant indicators of well-being. Balancing these two approaches, assessing happiness always involves both individual disposition and social context; environment and temperament together construct the relevant variables to the evaluation of one’s well-being (Diener, et al., 1999; Proctor, et al., 2009). Detriments to sources of positive affect are feelings of stress, anxiety and depression (Proctor, et al., 2009; Schiffrin, et al., 2010; Demir and Özdemir, 2010). Notably, esteem, extraversion, health of social relationships, emotional stability, anxiety and popularity are all predictors of life satisfaction (Gilman and Huebner, 2006; Rigby and Huebner, 2005; Holder, et al., 2010).

When addressing different components of life satisfaction, there are also terminological disputes. For instance, expressed feelings of happiness and emotions, such as satisfaction with life, have been considered a more relevant estimate of people’s own life situation than other measures, despite its subjectivity (Lane, 2000), It has also been emphasised that both widely-used indicators of well-being, structural and personal, should be taken into consideration when addressing life satisfaction (e.g., Gundelach and Kreiner, 2004; Kouvo and Räsänen, 2015). As such, we also take a look at the social context available online for users in terms of social media. Notably, as social media take many forms, a framework for understanding the social interaction becomes helpful.

Much like the off-line setting, the social context of the Internet is made up of both strong and weak social ties (see Granovetter, 1973; Wellman, et al., 1996). Here, strong ties tend to be longer term, involving mutual investment and accountability. On the other hand, weak ties are more instrumental in nature, more short-term interaction with fewer effects on reputation, for example (Wellman, et al., 1996). This spectrum is ever-present online as; online social networks are complex, with the possibility to control both identifiability and visibility according to user preference. However, similarities exist both online and off-line. The enhancement of communication through social media platforms increases opportunities for interaction that can complement off-line methods (Livingstone, et al., 2011; Näsi, et al., 2011; Davidson and Martellozzo, 2013).

Social media can widen the relational spectrum, allowing for the expansion of one’s social network far beyond what is possible off-line, with varying levels of relational intimacy, or social tie strength (Livingstone, 2008). Here, weak social ties are abundant as well. Social networking sites, a key component of social media, are particularly useful in managing social networks, including user flexibility in self-presentation; namely, users can present themselves as they wish to be seen which can enhance the socializing process (Keipi and Oksanen, 2014). Here, aspects of self mix with the capabilities of the online social environment, making for a dynamic environment.

These factors are central in the use of social media, as various platforms act to reinforce desirable social needs, for example in term social validation, expression and self-presentation through text or images (Seidman, 2013). Access to platforms among users and navigational skill in taking advantage of online social offerings can benefit population groups regardless of class or status (e.g., Lindblom and Räsänen, 2017). These benefits can come in the form of both strong and weak ties; some may seek benefits from instrumental relationships while others work to reinforce strong off-line relationships online. Despite this, however, past research also shows that different media applications have different implications for life satisfaction.

 

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Similarities and differences across social media platforms

In earlier research, use of social media has been found to interact with life satisfaction in different ways. This is because different media applications are used for different purposes. For example, using Facebook has been found to have a positive relationship with life satisfaction since it offers a tool to be in touch with family and friends (Valenzuela, et al., 2009). On the other hand, others have found links between general social media use and lower life satisfaction (Correa, et al., 2010). This contradiction can be partly explained by different use purposes between and within the platforms. Again, the social spectrum within social media is broad; notably, many studies reveal that not all uses of social media are based on actual interaction (Ellison, et al., 2011). As such, different social media platforms have different use purposes and they appeal to varied users according to preference. Social messaging applications such as WhatsApp or Facebook Messenger are mainly used with close relatives and friends for instant messaging between individuals or small groups, reinforcing strong ties. Other social media platforms such as Instagram, Facebook and Twitter, are also mainly used to interact with people users already know. On the other hand, various discussion forums, virtual gaming environments and text based chat platforms without usernames leverage more anonymous methods and tend to focus on weak ties and personal expression.

Naturally, there are many differences between these communication platforms and applications especially in terms of self-presentation, types of ties in different platforms, level of identifiability and method of interaction. Platforms such as Instagram are mainly focused on self-presentation through visual means (Sheldon and Bryant, 2016) while the micro-blogging site Twitter is focused on short messages, or ‘tweets’, meant for self-expression and information sharing through text (Kwak, et al., 2010). Furthermore, various online discussion forums provide outlets for expression and communication with varying degrees of user identifiability. Social media platforms also diverge in users’ network structure and amount of bonding and bridging social capital. For example, in Twitter and Instagram to a lesser extent people are more likely interacting with weak ties, while on Facebook and, surprisingly, in Snapchat, users are more likely connected with their strong ties, such as real-life friends (Phua, et al., 2017). The surprise in terms of Snapchat here arises due to the lack of information history being at the core of the platform, as interactions are deleted after concluding which might be considered favorable for weak tie exploratory interaction where lower accountability persists. Between these popular modes of social media use, a prominent difference concerns the balance between control over one’s audience and how self-presentation is carried out. While users of social messaging applications have full control over whom they are communicating with, discussion forum participation can involve large anonymous communities. Compared to social messaging applications, social media platform networks and especially discussion forums are typically wider scale with a larger body of weak ties.

A key difference between platform user experiences mentioned here has to do with self-presentation and level of anonymity. Anonymity here has to do with a lessening of social presence, or the degree to which users experience on another physically (Rourke, et al., 1999). Here, anonymity can bring two primary characteristics, namely lessening of identifiability and diminished visibility. Notably, these components can be relationally functional as users navigate in social media. For example, after the boom of personalized social media platforms such as Facebook, Twitter and Instagram, higher level of users’ anonymity have emerged, for example through the mobile social networking platform Jodel (https://jodel.com), which was launched in 2014. In Jodel, users can send messages and participate in conversations with full anonymity and without fear of revealing their identity. These various levels of anonymity are not mutually exclusive, as various combinations of anonymous activities are possible in the interactive environment online.

Notably, the scale effects of anonymity are tendencies rather than strict rules, as they illustrate what is possible as one moves from one end of the spectrum to the other. Visual anonymity is the most prevalent among social media users, namely any situation where users’ physical characteristics are hidden even in cases where participants are otherwise known to one another (Barreto and Ellemers, 2002; Lea, et al., 2001; Postmes, et al., 2001). Pseudonymity refers to any interaction where usernames, social profiles or avatars are developed by the user and implemented in an instrumental fashion. Finally, full anonymity exists in interactions where no reputation effects nor the ability to identify the user are possible once that interaction is completed (Pfitzmann and Köhntopp, 2001). These interactions based on full anonymity tend to be text based, excluding the use of any identifiable profile or username. Movement from fully anonymous to visually anonymous and finally face-to-face interaction typically infers a greater degree of relational timescale, social tie strength and reputation effects (Westlund and Bjur, 2014; Keipi and Oksanen, 2014).

Online social space is complex, despite it being made up of a similar dynamic of weak and strong ties found off-line as well. Life satisfaction is a central component to psychological health and as such become a valuable area of research, especially in the online environment where increasing numbers of users spend much of their socializing time. Furthermore, due to variances in use purposes and the different functions of social networking sites and communication applications, it is important to recognize that the connection between the different platforms and users’ life satisfaction is not clear. For example, previous research suggests that Facebook might offer greater benefits for users who have low self-esteem and low life satisfaction (Ellison, et al., 2007). On the other hand, having supportive and positive interaction via social network sites has been found to associate with higher life satisfaction (Oh, et al., 2014).

While there is a plethora of preceding studies looking at social media and its behavioral and attitudinal consequences in different population groups (e.g., Keipi, et al., 2017; Perse, 2016), systematic comparisons across different applications are rare. This is especially true when we think about population representativeness of past research. Most studies focus on teenagers and young people, and do not typically cover adult populations, residential areas or various different living arrangements. In the next section, we aim at contribute to this key gap in the research by utilizing nationally representative data from Finland while also implementing a more comprehensive measure of life satisfaction than has been used in most preceding studies on online life satisfaction and well-being.

 

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Research design

The focus of the empirical analysis of this study is on the social Internet use-purposes of Finns according to various socio-demographic factors in addition to any associations between life satisfaction and specific online social media platform use. The following research questions guide the analysis:

1. How does the use of different social media platforms associate with social media users’ overall life satisfaction?
2. How does the controlling of sociodemographic background and social ties of participants affect these associations?

With regards to the first research question, we hypothesize (H1) that certain social media platforms associate clearly with higher life satisfaction, while others do not. This assumption is based on previous research on how specific social media platform use has been linked to life satisfaction and well-being in cases of having strong social ties (e.g., Keipi and Oksanen, 2014; Valenzuela, et al., 2009). Here, we expect to find this effect especially on platforms that require active commenting and participating with other people (such as social messengers, Facebook or Instagram) where relational upkeep is carried out. Social media that require less interaction and tend to be anonymous, such as discussion forums where longer-term strong tie reinforcement is less likely, will not show positive associations with life satisfaction.

In previous studies, social media use have been shown to be linked to various contextual factors. As such, we expect that younger, highly educated and those with stable social relationships will be more likely to use social media in high amounts compared to others (e.g., Schradie, 2011; van Deursen and van Dijk, 2014). In addition, educated people and those who live in a committed relationship tend to report higher life satisfaction than others (e.g., Oishi and Deiner, 2001; Kouvo and Räsänen, 2015). Despite this, however, we assume that the associations between life satisfaction and control variables will not significantly weaken the life satisfaction associations of different social media platforms. Therefore, our second hypothesis (H2) is that the detected effects remain significant after taking the other independent variables into account.

 

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Data and methods

Our analysis is based on the nationally representative survey data, “Everyday life and appearance” (n=1,600) collected in spring 2016. The data were collected in the spring of 2016 at the Unit of Economic Sociology, University of Turku. The survey was distributed by mail to a simple random sample of 4,000 15–74–year–olds who live in Finland and speak Finnish. The final sample included 3,994 Finns, as those who could not be reached were omitted from the sample. The final data, amounted to a 40 percent response rate, represent the Finnish population relatively well. In order to correct a minor sample bias in terms of both age and gender distribution, we used a weight factor variable (for details, see Sarpila, et al., 2016).

We conduct an explanatory regression analysis using ordinary least squared (OLS) models. The aim of the explanatory analysis is to evaluate the effect of the use of various social media platforms on respondents’ overall life satisfaction. The models are shown separately for different social media platforms in the Table 2.

As for dependent variables, we use a sum-variable measuring respondents’ overall life satisfaction. The applied variable was conducted by combining three common indicators of subjective quality of life and well-being, namely “satisfaction with one’s own life”, “happiness” and “self-esteem”. We implemented this measure based on past research and the assumption that life satisfaction is generally approachable by different indicators selected and indeed complemented by including factors commonly linked to the phenomenon. In addition, we can justify using a joint-measure due to all empirical indicators eventually having their own possible error source. After all, the key interest in our analysis lies in the question of whether the same or different explanatory factors are emphasised in analysing different social media platforms. These indicators were originally asked in the questionnaire as “How do you describe your 1) happiness 2) life satisfaction and 3) self-esteem”. Respondents were given a 10-point scale, ranging from 1=very dissatisfied/unhappy/low and 10=very satisfied/happy/high.

In preceding literature, life satisfaction and happiness are sometimes linked to different psychological phenomena (see Lane, 2000). However, as empirical measures, different survey items are often used together to better capture the underlying dimensions of life satisfaction in general (e.g., Inglehart and Klingemann, 2000; Kouvo and Räsänen, 2015). In our study, these three items correlated strongly with one another (inter-item α=0.89).

Our central independent variables consist of five different social media platforms including Facebook, Twitter, Instagram, Forums and Social messaging applications (SMAs) such as WhatsApp. In the original question, participants were asked how often they use these five social media platforms by giving six different options: 1) never, 2) once a month or less frequently, 3) once a week, 4) many times a week, 5) daily and 6) many times a day. Here we developed binary variables to measure use of different platform “At least sometimes”. Regarding the first one, a value of 0 represented those participants who had not used at all the platform and 1 represented those who had carried out such activity at least once a month or less frequently.

As mediating variables, we used respondents’ real-life social ties by measuring their relationship status and amount of social meetings. Social meetings were originally asked with how often respondents met their friends, relatives and colleagues. Six different options were given: 1) never, 2) once a month or less frequently, 3) once a week, 4) many times a week, 5) daily and 6) many times a day.

We also controlled for respondents’ gender, age and education. Education is categorised on the basis of ISCED classification into four groups according to whether he or she had completed lower-secondary, upper-secondary, bachelor’s or at least master’s level education. Before entering the variables into the regression models, we created dummies from the original categorical variables and omitted the first categories because of the collinearity. The summary of applied variables is shown in the Table 1.

 

Table 1: Descriptive statistics for dependent and independent variables, means and standard deviations.
 NumberMeanStandard deviationMinMax
Dependent variables     
Satisfaction with one’s own life1,5737.71.5110
Happiness1,5757.71.6110
Self-Esteem1,5677.61.8110
Overall life satisfaction (sum variable)1,58122.84.5330
Independent variables     
Facebook1,4840.60.501
Twitter1,4790.10.301
Instagram1,4790.30.401
Forums1,4840.20.401
Social messaging applications(SMAs)1,4760.70.501
Gender1,5950.60.501
Age1,58948.317.41574
Lower-second education (Max)1,5720.20.401
Upper-second1,5720.50.501
Bachelor’s1,5720.20.401
Master’s (at least)1,5720.10.301
Relationship status1,5280.70.401
Social meetings1,5803.71.017

 

 

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Results

In our analysis, we first assessed links between overall life satisfaction and different media platforms. Figure 1 is made up of illustrated social media platform and applications effects representing the predictive margins for different platform users. The figure also shows a line representing a population mean. As seen in the figure, there are relatively large differences in how different platform users perceive their life satisfaction. Instagram and SMAs were the only social media platforms that had a positive association with life satisfaction. Discussion forums had the strongest and only negative association with life satisfaction.

 

Overall life satisfaction by the use of different social media platforms
 
Figure 1: Overall life satisfaction by the use of different social media platforms. Means and 95% CIs.

 

In the second stage of analysis we took into account the effects of respondents’ background and off-line social ties. Table 2 shows the results of the regression analysis as OLS estimated coefficients by different communication platforms and applications. We separately carried out five models, each of which included the use of different social media platforms. We first analysed effects of background factors, whose effects can be found from the M1 columns in Table 2.

Background variables had varied associations with life satisfaction. However, we did not find notable changes in the effects of social media platforms after controlling for respondents’ backgrounds. In previous studies education was considered as a crucial factor in its association with the use of social media and life satisfaction: people who had graduate-level education were likely to have higher life satisfaction (e.g., Oishi and Deiner, 2001; Kouvo and Räsänen, 2015). Interestingly, various education levels and gender did not have any significant effect in any of the included use purpose.

Next, we turn to the effects of off-line social ties, which are presented in the M2 columns in Table 2. The effects of off-line social ties and relationship status were strong predictors in every platform. Respondents who had many off-line social ties and those who were in a relationship were more likely to feel better about their personal lives. Interestingly, these off-line social ties did not have any mediating effects on different communication use purposes’ effects. Final models explain respondents’ life satisfaction relatively well, which enable us to draw reliable conclusions on the associations between social media platforms and life satisfaction in the discussion section.

 

Table 2: OLS estimated coefficients for overall life satisfaction by different social media platform and background variables.
Note: Standard errors in parentheses; ***p<0.001; **p<0.01; *p<0.05;Omitted “Not use”, “Male”, “Max Lower-Second Education”, “Single”;c=continuous variables.
VariablesM1M2M1M2M1M2M1M2M1M2
Facebook-0.18
(0.28)
-0.24
(0.27)
        
Twitter  -0.34
(0.34)
-0.18
(0.33)
      
Instagram     0.95**
(0.29)
0.74**
(0.29)
    
Forums      -1.52***
(0.30)
-1.28***
(0.29)
  
SMAs        1.47***
(0.30)
1.17***
(0.30)
Female-0.16
(0.24)
-0.22
(0.23)
-0.23
(0.23)
-0.30
(0.23)
-0.35
(0.24)
-0.40
(0.23)
-0.44
(0.24)
-0.49*
(0.23)
-0.31
(0.23)
-0.35
(0.23)
Age [c]0.01
(0.01)
0.01
(0.01)
0.01
(0.01)
0.01
(0.01)
0.03**
(0.01)
0.02**
(0.01)
0.01
(0.01)
0.01
(0.01)
0.03***
(0.01)
0.03***
(0.01)
Upper-second0.36
(0.33)
0.01
(0.33)
0.41
(0.33)
0.07
(0.33)
0.39
(0.33)
0.08
(0.33)
0.49
(0.33)
0.16
(0.33)
0.18
(0.33)
-0.09
(0.33)
Bachelor’s education0.97*
(0.40)
0.51
(0.40)
1.11**
(0.40)
0.64
(0.40)
1.04**
(0.40)
0.62
(0.40)
1.21**
(0.40)
0.76
(0.40)
0.76
(0.40)
0.41
(0.40)
Master’s education2.03***
(0.42)
1.55***
(0.42)
2.12***
(0.42)
1.63***
(0.42)
2.00***
(0.42)
1.57***
(0.42)
2.19***
(0.42)
1.73***
(0.42)
1.62***
(0.42)
1.28**
(0.42)
In a relationship 2.26***
(0.27)
 2.17***
(0.27)
 2.18***
(0.27)
 2.10***
(0.27)
 2.02***
(0.27)
Social meetings [c] 1.21***
(0.12)
 1.20***
(0.12)
 1.18***
(0.12)
 1.20***
(0.12)
 1.19***
(0.12)
            
Constant22.25***
(0.59)
16.63***
(0.77)
22.12***
(0.54)
16.48***
(0.73)
21.46***
(0.55)
16.04***
(0.73)
22.73***
(0.53)
17.05***
(0.73)
20.49***
(0.62)
15.28***
(0.77)
            
Number1,4481,3831,4431,3781,4441,3791,4481,3821,4411,377
Adj. R-squared0.020.120.020.120.030.130.040.130.030.13

 

 

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Discussion

This study examined the social use purposes of Finns’ social media activity while also delving into associations with overall life satisfaction. In addition, various contextual factors were taken into account in the analysis. Central here was the implementation of a three-level overall life satisfaction variable combining happiness, life satisfaction and self-esteem items. The analysis of social online use-purposes was divided into various groups. These included direct messaging used for communication with known others, Instagram, which is focused on self-presentation through visual means with followers, discussion forums based around community or shared interest where text is used for self-expression and interaction and, finally, Facebook and Twitter, which are focused on social network management, interaction and communication both visually and through text. Together, these categories formed a comprehensive framework representing the current online social media landscape in terms of popular activity.

We hypothesized that certain social media platforms would associate with higher levels of overall life satisfaction based on past research that has shown that social media use has been linked to higher life satisfaction where use-purposes were linked with having strong social ties (e.g., Keipi and Oksanen, 2014; Valenzuela, et al., 2009). Specifically, using platforms involving effective tools for commenting and interaction with other such as social messengers, Facebook and Instagram were expected to be associated with higher levels of perceived overall life satisfaction. Results showed that Instagram and direct messaging application use were indeed associated with higher levels of life satisfaction, confirming our hypothesis. On the other hand, Facebook and Twitter did not carry statistically significant associations with overall life satisfaction. This comes as a bit of a surprise in the case of Facebook, given its popularity in maintaining both online and off-line strong ties. However, a mitigating effect may involve the wide scope of social tie strengths involved in that platform, which may muddle the effect of potential strong tie benefits therein. Twitter, as a primarily wide scale text-based platform with a focus on outward production rather than in-depth relationship maintenance was somewhat in line with our expectations given its primary role as a distribution mechanism rather than one designed for relational maintenance of strong ties (Phua, et al., 2017; Kwak, et al., 2010).

Discussion forums showed a negative association with life satisfaction, which is in line with our hypothesis. This finding is a stark contrast to other social media platform findings, yet is in line with our expectations due to the significant difference in the social aspects of text-based platform dynamics. Here, these forms of social media involve less direct interaction due to different levels of identifiability or visibility linked to anonymity as mentioned earlier. As such, level of reputation effects, relational timescale and strength of social ties tend to be diminished, resulting in less social cohesion which has, in turn, been linked to lower life satisfaction in past research (e.g., Ellison, et al., 2007; Oh, et al., 2014). Here, longer-term strong social tie reinforcement is less likely. These platforms involve a departure from more interactive sites such as Facebook or Instagram. Notably, though also text-based, direct messaging services differ significantly here as well due to interacting partners there tending to be known to the participant.

As such, level of familiarity with network members and openness of content sharing by users seems to be linked with level of interaction and content sharing based on past research (e.g., Lönnqvist and Itkonen, 2014; Postmes, et al., 2001). On Instagram, Facebook and direct messaging applications, participants have more means to control with whom they are connected and who is able to see their published content. On the other hand, Twitter and text-based discussion forums tend to bring the common presumption that all content is public. This can in turn affect the level of relational and therefore personal benefits of specific platform use.

According to our results, those interacting with strong social ties via various direct messaging platforms also had higher overall life satisfaction. This is also in line with our hypotheses, as reinforcing of strong ties is central to the use-purposes of direct-messaging services such as WhatsApp. Instagram networks tend to also be made up of familiar partners, but cases there are less uniform given the possibility for unknown others to follow one’s content. In terms of familiarity, those operating through anonymous avatars or usernames, such as is the case on most discussion forums, may be more open to abusive content due to a lower threshold for damaging expression (e.g., Livingstone, 2008; Keipi, et al., 2017).

Overall, results showed that off-line strong social ties are in centrally important in self-assessed overall life satisfaction. In every statistical model of our analyses, relationship status and social meetings were the most important predictors of life satisfaction. This is in line with our hypothesis based on past findings that show similar effects (e.g., Kouvo and Räsänen 2015). Furthermore, higher education was also a significant predictor of overall life satisfaction in every model, which also confirmed our expectations and past research (e.g., Oishi and Deiner, 2001). However, it is noteworthy here that notable platform effects were statistically significant even after controlling for respondents’ demographic background and off-line social ties.

Notably, the study is not without limitations. Despite key findings on strong off-line social tie strength links to overall life satisfaction, the analysis did not directly test online social tie strength associations in a similar way. Although certain social media platforms are clearly linked to strong social tie management and reinforcement, our methods here focused on links between platform use and overall life satisfaction. As such, testing social tie strength associations with specific social media platform use is a valuable topic for future research based on the inferences made here. Also, social media platform usage should be used as a multi-category variable, which was not possible in this study due to the restricted sample size and a low number of reported usage on certain platforms. Added to this, this study was based on a representative sample of citizens from only one country. Cross-national perspectives would be encouraged in future research.

 

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Conclusion

Our findings support the idea that different use purposes are actively implemented among different population groups and that their implementation is linked to both online and off-line social relations Together, the various social media platforms assessed in addition to contextual factors help to add understanding to key areas associated with overall life satisfaction among users.

When considering off-line social ties and different social media platforms, strong ties were shown to be the most important predictors of high overall life satisfaction. Overall, the study showed that when social media use is connected to off-line social ties, they are likely contributing to improvements in self-assessed overall life satisfaction. On the other hand, in the case of those interacting with unknown participants in more anonymous social media platforms, lower satisfaction becomes more likely. End of article

 

About the authors

Teo Keipi is Senior Researcher in the Department of Social Research at the University of Turku, Finland. Keipi’s research interests cover cultural consumption, network studies and well-being.
Send correspondence to: teo [dot] a [dot] keipi [at] utu [dot] fi

Ilkka Koiranen is a doctoral candidate in the Department of Social Research at the University of Turku. Koiranen’s research interests involve population level statistics on media consumption and social network analysis.
E-mail: ilalko [at] utu [dot] fi

Aki Koivula is a doctoral candidate in the Department of Social Research at the University of Turku. Koivula’s research interests involve lifestyle and cultural consumption along with digitalization.
E-mail: akjeko [at] utu [dot] fi

Pekka Räsänen is Professor in the Department of Social Research at the University of Turku. Räsänen’s research interests involve societal consumption patterns, the economics of leisure and well-being.
E-mail: pekka [dot] rasanen [at] utu [dot] fi

 

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Editorial history

Received 30 October 2017; accepted 14 December 2017.


Copyright © 2018, Teo Keipi, Ilkka Koiranen, Aki Koivula and Pekka Räsänen.

Assessing the social media landscape: Online relational use-purposes and life satisfaction among Finns
by Teo Keipi, Ilkka Koiranen, Aki Koivula and Pekka Räsänen.
First Monday, Volume 23, Number 1 - 1 January 2018
http://firstmonday.org/ojs/index.php/fm/article/view/8128/6615
doi: http://dx.doi.org/10.5210/fm.v23i1.8128





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