Active and Passive Facebook Use and Associated Costly Off-line Helping Behavior

Abstract

This study examined active and passive Facebook use and the associated costly altruistic behavior. Results supported the hypothesis that social media use, particularly active use, can enhance the perceived relatedness of individuals in need and reduce the influence of genetic relatedness in helping. Passive social media users tended to help kin in both situations involving low and high biological cost, whereas they were less likely to risk themselves to help social media friends and strangers in extraordinary situations involving high biological cost. However, active social media users, who had a broader sense of connectedness with genetically unrelated individuals, were more willing to help social media friends and strangers in both situations involving high and low biological cost.

Keywords

Inclusive fitness off-line helping reciprocal altruism social capital social media

Introduction

Numerous studies have found that individuals connect with others on social media to gain reciprocal benefits (e.g., Aubrey & Rill, 2013; Ellison, Gray, Lampe, & Fiore, 2014; Ellison, Steinfield, & Lampe, 2011; Hofer & Aubert, 2013; Lee, Kim, & Ahn, 2014). That is, people invest in social relationships and provide aids to others who are expected to provide delayed benefits to oneself online and offline. However, it is unclear whether social media usage is correlated with costly off-line helping behavior without obvious immediate benefits. Furthermore, empirical findings have demonstrated that people are more likely to use social media to broaden and build social networks with new friends than bonding relationship with family members and close friends (Liu, Ainsworth, & Baumeister, 2016, for meta-analysis). Little is known about the difference between willingness to help kin and nonkin and the associated social media use. While online and off-line reciprocal behavior were investigated (e.g., Khang & Jeong, 2016; Wright & Li, 2011), only everyday helping behavior with low biological cost was tested. In this study, helping with low biological cost refers to everyday helping behavior that is not biologically significant, whereas helping with high biological cost refers to life-or-death helping behavior that is biologically significant, such as saving an individual from life-threatening danger (Graziano, Habashi, Sheese, & Tobin, 2007).

Social capital theory (Coleman, 1988; Putnam, 2000) has recently been adopted by social media researchers to explain how individuals perceive online connections as a social resource and gain monetary and emotional support through cooperation and reciprocal altruism on social media (e.g., Brooks, Hogan, Ellison, Lampe, & Vitak, 2014; Ellison, Steinfield, & Lampe, 2007; Hofer & Aubert, 2013; Liu et al., 2016). However, this line of research can only explain why individuals perform reciprocal altruism online and offline by providing everyday help. Social capital theory cannot explain the relationship between social media usage and costly off-line helping behavior without obvious immediate benefits. Indeed, through the lens of evolutionary theory, social media use (usage of social media platforms to connect to a broader range of people) can serve as a possible social-cognitive motivator to enhance the perceived relatedness of persons in needs and reduce the power of genetic relatedness in helping. Guided by evolutionary theories, this study aims to examine the associations between passive and active social media usage and helping kin and nonkin involving low and high biological cost.

Social media use and reciprocal altruism

According to theory of reciprocal altruism (Trivers, 1971), human beings have psychological mechanisms designed to help others because building and maintaining long-term relationships can create delayed benefits to oneself. If the cost of cooperation through repeated interactions is lower than the delayed benefits in the long term, individuals would continuously cooperate with other individuals who can provide a source of advantages (Axelrod & Hamilton, 1981). Similar to financial capital, people invest in social relationships in order to receive emotional and monetary support.

Interpersonal relationship or network is a resource that can provide emotional support or monetary benefits through cooperation, trust, and reciprocity. Social relations can be an investment with anticipated returns in the future (Lin, 2001). People are social actors who interact, create, and maintain a network of individuals (i.e., social network) forming positive affective bonds. Thus, interpersonal connections generate positive outcomes such as emotional, informational, and material support. Connecting to many individuals who can provide delayed help when in need is akin to retaining financial wealth, a metaphor of the term “capital.” Putnam (2000) proposed that individuals could acquire social resources from strong ties through the sense of intimacy within a small close group such as family members and from weak ties through the sense of belonging between people from different backgrounds such as friends and colleagues.

Although some research suggested that computer-mediated communication reduces real-life social interactions (e.g., Nie, 2001), numerous studies have found that social media favor social resources formation and maintenance (e.g., Ellison et al., 2007, 2011; Ellison, Vitak, Gray, & Lampe, 2014; Jin, 2015; Kwon, D’Angelo, & McLeod, 2013; Lee et al., 2014). People can connect with others on social media in a more easygoing way than via off-line face-to-face interaction (Williams, 2006), because the costs of meeting and leaving others online are lower than offline (Galston, 2000). For instance, individuals who use Facebook to keep contacts with others are more willing to integrate into the community and provide support to this community (Ellison et al., 2007). A meta-analysis showed that (1) posting status updates, photos, and other types of information about oneself; (2) liking, commenting, and sharing others’ posts on social media; and (3) searching information of other social media users contribute to both bonding and bridging social capital (Liu et al., 2016).

Facebook provides information including mutual friends that may facilitate users to broaden their social network and build weak and bridging ties. Because of the potential to establish “social supernets” of hundreds of social connections (Donath, 2007), Facebook can cultivate the benefits correlated with heterogeneous social ties such as broadened worldviews (Ellison et al., 2007, 2011). Because of its lower cost of keeping and communicating with a larger network of weaker ties, Facebook can empower users to retain broader and more diverse social networks. Maintaining interpersonal relationships with Friends of Friends may enable users to connect to diverse individuals, feel interested in the greater world, and perceive oneself as part of a larger community (Ellison, Vitak, et al., 2014).

Online and off-line social networks are overlapped (Ellison et al., 2007; Williams, 2006). Individuals generally employ social media to mirror off-line relationships (Boyd & Ellison, 2007). They extend social interaction from offline to online. Also, online interaction may generate changes in off-line social connection. For example, online and off-line social capital formation are intercorrelated (Ellison et al., 2007). Online prosocial behavior on social media was positively correlated with face-to-face prosocial behavior (Wright & Li, 2011). The more intensely people use Facebook, the more likely they connect with others offline to gain reciprocal benefits.

Social media use and perceived relatedness

According to theory of inclusive fitness (Hamilton, 1964a, 1964b), human beings have psychological mechanisms designed to be more likely to help relatives who carry their genes than nonrelatives who are less genetically related such as friends or strangers. Following Hamilton’s rule: rB–C > 0, in which r is degree of genetic relatedness, B is benefit, and C is cost, an individual would provide help if the cost of helping someone in need to self is lower than the benefit to the person weighted by the degree of genetic relatedness. It implies that natural selection favors a tendency to differentiate among the one in need according to their degree of relatedness. The higher the genetic relatedness, the more likely an individual pay higher cost to help.

While genetic relatedness is an important factor to predict helping behavior, perceived relatedness can be a social-cognitive factor for helping that reduces the influence of genetic relatedness (Burnstein, Crandall, & Kitayama, 1994; Graziano et al., 2007; Ng, 2016). When specific factors activate altruistic motives, those motives may arouse individuals to enlarge inclusion and perceive nonsignificant others as being closely related to oneself. For example, Graziano et al. (2007) found that agreeableness is a social-cognitive motivator that enhances the perceived relatedness of people in need. Agreeableness is a major personality trait of individuals who are cooperative and willing to sacrifice self-interest to help others (Graziano, 1994; McCrae & Costa, 1997). Similar to Burnstein et al.’s (1994) findings, people were more likely to provide aid to kin than nonkin. Following Hamilton’s (1964a, 1964b) rule of inclusive fitness, although willingness to help kin and nonkin may not be significantly different in everyday situations (low biological cost), kin received more help in the life-or-death situations (high biological cost) than did nonkin. However, while persons low in agreeableness followed the rule of inclusive fitness, individuals high in agreeableness were more willing to risk negative consequences to help nonrelatives in both everyday and life-or-death situations (Graziano et al., 2007). The results implied that agreeableness generates a sense of connectedness with a broader range of people regardless of the genetic relatedness.

While agreeableness serves as a social-cognitive motivator to heighten the perceived relatedness of persons in need, this study proposed that social media use can be another social-cognitive motivator that can increase the perceived relatedness of individuals in need and decrease the influence of genetic relatedness in helping. It is because instead of maintaining relationships with relatives, individuals who use social media are inclined to feel connected to genetically unrelated nonrelatives (Ellison et al., 2007; Ellison, Vitak, et al., 2014; Liu et al., 2016). Because of the features of social media, people can use them to enlarge connection, inclusion, cooperation, and reciprocity with nonsignificant others. The function of social media use that can generate prosocial outcomes is consistent with perceived relatedness as a social-cognitive motivator that can facilitate altruistic motives to expand reciprocity. A meta-analysis of 50 studies found that rather than bonding intimate relationships, social media use tends to make people feel connected to a larger community, evoke them that people in the world are attached, and urge them to connect with strangers (Liu et al., 2016). As social media use can generate a sense of connectedness with a broader range of individuals regardless of genetic relatedness, this study proposed that social media use can be a social-cognitive motivator to enhance the perceived relatedness of persons in need. As online and off-line reciprocal altruism are intercorrelated (Putnam, 2000; Williams, 2006) and online and off-line prosocial behavior are associated (Wright & Li, 2011), it is possible that social media use would moderate the patterns of off-line helping such that while persons low in social media use would follow the rule of actual biological relatedness, persons high in social media use would provide aid to nonkin offline even if biological costs were high.

Active and passive Facebook use and helping involving low and high costs

This study differentiated Facebook use into active and passive forms to advance the understanding of how the two types of Facebook use serve as the motivators to facilitate perceived relatedness of persons in need offline. Active usage contains online activities that involve direct exchanges with other Facebook users such as posting status updates, commenting on friends’ posts, and sharing links. Passive usage refers to information consumption without direct exchanges such as scrolling through news feed and looking at friends’ status updates, pages, and pictures (Verduyn, Ybarra, Résibois, Jonides, & Kross, 2017).

Passive social media use leads to negative outcomes, whereas active social media use is correlated with positive consequences. For example, passive Facebook use is related to social anxiety symptoms (Shaw, Timpano, Tran, & Joormann, 2015), body dissatisfaction (Rousseau, Eggermont, & Frison, 2017), and subjective well-being negatively (Verduyn et al., 2015), which are not associated with reciprocal altruism and perceived relatedness. In contrast, active social media usages such as posting status updates, liking, commenting, and sharing others’ posts favor bridging social capital (Liu et al., 2016). As passive and active Facebook use can be associated with different psychological and behavioral variables, it is reasonable to expect that the two types of use are two different constructs. Thus, it is predicted that passive Facebook usage would not affect the helping patterns, but active Facebook usage would enhance the perceived relatedness of individuals in need and broaden a sense of connectedness with genetically unrelated individuals, thus motivating active users to help them even if the biological costs were high.

To replicate and extend Burnstein et al. (1994) and Graziano et al. (2007), this study followed the previous two types of helping conditions and modified the person in need to include siblings, social media friends, nonsocial media friends, and strangers. The two helping vignettes were an everyday helping situation (stop to help the target whose car broke down on the side of the road) and an extraordinary helping situation (enter a burning house to save the life of the target). Consistent with previous results, it is hypothesized that individuals would be more likely to help people in need according to genetic relatedness: siblings more than friends (social media and nonsocial media) and strangers. It is also hypothesized that active Facebook use (but not passive Facebook use) would moderate patterns of helping: compared with individuals low in active Facebook use who would be more likely to help siblings than social media and nonsocial media friends and strangers, individuals high in active use would aid all targets regardless of the genetic relatedness. Specifically, active Facebook use would facilitate perceived relatedness of targets: helping would be less tightly affected by genetic relatedness for high active users than it would be for low active users in extraordinary helping situations; passive Facebook use would not elicit perceived relatedness of targets.

In the conditions involving low (biological) costs of helping, the delayed benefits of helping others should be higher than its cost. Thus, individuals would provide aid to others who can provide a source of advantages (Axelrod & Hamilton, 1981). The priority of helping is based on the degree of genetic relatedness (Hamilton, 1964a, 1964b). It implies that individuals are more likely to help genetically related others (e.g., siblings) than genetically unrelated others (e.g., friends) and then strangers. However, previous studies have shown that social media use can facilitate individuals’ sense of perceived relatedness of genetically unrelated others, evoke them that people all over the world are connected, and encourage them to connect with strangers (Ellison, Vitak, et al., 2014; Liu et al., 2016). As online and off-line altruism are associated (Putnam, 2000; Williams, 2006; Wright & Li, 2011), it is predicted that individuals who actively and frequently use Facebook as direct exchanges with others should have the psychological mechanisms to help siblings, social media friends, nonsocial media friends, and strangers in need regardless of their genetic relatedness when the (biological) cost of helping is lower than the delayed unobvious benefits.

Hypothesis 1: For ordinary helping situations involving low biological cost, active Facebook use would be positively associated with helping (1a) siblings, (1b) social media friends, (1c) nonsocial media friends, and (1d) strangers.

In the conditions involving high (biological) costs of helping, the delayed benefits of helping others may not be higher than its cost. Thus, individuals would be more likely to provide aid to others based on the degree of genetic relatedness. Active Facebook users who perform direct exchanges with others have the psychological mechanisms to generate a sense of perceived relatedness of genetically unrelated others. However, when the situations involve high (biological) cost, the mechanisms would adjust the behavioral intentions to help genetically related others (i.e., siblings) based on the rule of inclusive fitness (Hamilton, 1964a, 1964b) and social media friends because of the increase in perceived relatedness due to social media use (Ellison, Vitak, et al., 2014; Liu et al., 2016).

Hypothesis 2: For extraordinary helping situations involving high biological cost, active Facebook use would be positively associated with helping (2a) siblings and (2b) social media friends.

Passive Facebook use indicates indirect exchanges with other users. Thus, the increase in perceived relatedness with others in need would be lower than active use with direct exchanges. In the situations involving low (biological) costs of helping that its cost is expected to be lower than the expected delayed benefits, passive Facebook users would help genetically related siblings based on the rule of inclusive fitness and help social media friends who may provide delayed advantages. However, passive Facebook users who perform indirect exchanges with others would not have the psychological mechanisms to cultivate a sense of perceived relatedness of genetically unrelated others who will not offer delayed benefits, that is, nonsocial media friends and strangers. Thus, passive Facebook use would be positively correlated with helping siblings and social media friends but not nonsocial media friends and strangers in everyday helping situations.

Hypothesis 3: For ordinary helping situations involving low biological cost, passive Facebook use would be positively associated with helping (3a) siblings and (3b) social media friends.

In the situations involving high (biological) cost of helping that its cost may be higher than the delayed benefits, passive Facebook users would only follow the rule of inclusive fitness because the psychological mechanisms to increase perceived relatedness would not apply to passive Facebook use.

Hypothesis 4: For extraordinary helping situations involving high biological cost, passive Facebook use would be positively associated with helping siblings.

Method

Participants and procedure

This study employed 811 Amazon Mechanical Turk (MTurk) workers. The only selection criterion was that participants needed to be older than 18 years. The survey study was posted on MTurk, an open online marketplace for data collection (Buhrmester, Kwang, & Gosling, 2011). MTurk workers who saw this post and were interested in participating in this study clicked on the link of this online survey. They got US$0.4 in return for their participation after completing a 10-minute online questionnaire. Six questions were asked to recognize careless responses (e.g., “Please select ‘Always’ for this item”). Participants who did not correctly answer all the six questions were ruled out (34.53%). Finally 531 MTurk workers were included (42.94% females; Mean_age = 33.17, SD_age = 9.81, Min_age – Max_age = 18–78). Participants answered a questionnaire including the following measures after they read the informed consent statement, confirmed that they were more than the age of 18 years, and agreed to participate. The order of presentation of the passive and active Facebook use items and the two helping situations were randomized across participants. This study was approved by the Human Research Ethics Committee of the author’s university. Data are available online at https://osf.io/h4q76/?view_only=7b4c390245724b01960d871b43d95d62

Measures

Active and passive Facebook use

Participants were first asked whether they were a Facebook user (97.74% answered yes). If the participants answered yes, they were then asked to answer their passive and active Facebook use on seven-point Likert-type scales from 1 (Never) to 7 (Always). Active use involved direct communication with others on Facebook conveniently, such as posting status updates and commenting on friends’ walls. Passive use involved browsing Facebook conveniently, such as scrolling through news feeds and looking at friends’ status updates (Verduyn et al., 2015). Appendix 1 displays all the measurement items. Reliabilities of the passive and active use scale were good (α = .85 for active use; α = .86 for passive use).

Ordinary and extraordinary helping situation

Participants provided their responses to two hypothetical situations that were adapted by Graziano et al. (2007). In the first situation (ordinary or everyday helping), participants were told that a person’s car broke down on the side of the road. They might be late for an important meeting if they stopped to help. Participants were asked what percentage chance they would be willing to risk being late to help a (a) sibling, (b) social media friend, (c) nonsocial media friend, and (d) stranger. Choices ranged from 0% to 100%, in 10% increments. In the second situation (extraordinary helping), participants can enter a burning house to rescue the house’s owner. Participants were asked what percentage chance they would be willing to risk death or serious injury to help a (a) sibling, (b) social media friend, (c) nonsocial media friend, and (d) stranger. The order in which the helping persons were presented in each of the situations was counterbalanced.

Results

Preliminary analyses

First, a 4 (Relationship: helping sibling, social media friend, nonsocial media friend, and stranger) × 2 (Situation: ordinary helping and extraordinary helping situation) two-way repeated-measures analysis of variance was conducted. A significant interaction effect was found, F(3, 1515) = 24.60, p < .001, η²_p = .044. Participants were more willing to help a sibling (M = 74.58%, SD = 23.97% for ordinary helping situation; M = 75.33%, SD = 23.78% for extraordinary helping situation), followed by social media friend (M = 51.86%, SD = 26.55% for ordinary situation; M = 53.71%, SD = 27.26% for extraordinary situation) and nonsocial media friend (M = 53.15%, SD = 28.29% for ordinary situation; M = 55.50%, SD = 28.18% for extraordinary situation), and finally by stranger (M = 35.56%, SD = 28.33% for ordinary situation; M = 44.97%, SD = 29.23% for extraordinary situation).

Main analyses

Table 1 displays the regression analyses predicting helping across the four relationship types in the everyday help and extraordinary situation from passive and active Facebook use after controlling for gender and age. All the passive Facebook use × active Facebook use interaction terms were removed as none of them was significant. In the ordinary situation, active Facebook use positively predicted helping social media friend and stranger. Thus, H1b and H1d were supported. However, active use was not associated with helping nonsocial media friend. Active use was even negatively associated with helping sibling in the ordinary situation. Thus, H1a and H1c were not supported.

Table 1.

Regression analyses predicting helping sibling, social media friend, nonsocial media friend, and stranger in the ordinary and extraordinary situation from gender, age, and passive and active Facebook use.

				Ordinary situation					Extraordinary situation
Predictors	B	SE	β	t	p	B	SE	β	t	p
				Sibling					Sibling
Intercept	.55	.06		9.96	<.001	.58	.06		10.62	<.001
Gender	.02	.02	.03	.78	.44	.02	.02	.04	.88	.38
Age	.01	.00	.20	4.69	<.001	.00	.00	.15	3.54	<.001
Facebook passive	.05	.01	.24	3.79	<.001	.05	.01	.29	4.55	<.001
Facebook active	−.05	.01	−.27	−4.22	<.001	−.05	.01	−.30	−4.73	<.001
R²	.08					.07
Adjusted R²	.07					.07
				Social media friend					Social media friend
Intercept	.23	.06		3.73	<.001	.24	.06		3.80	<.001
Gender	.02	.02	.04	0.95	.34	.05	.02	.09	2.00	.046
Age	.00	.00	.03	.70	.48	.00	.00	.05	1.23	.22
Facebook passive	.03	.01	.15	2.29	.022	.02	.01	.09	1.35	.18
Facebook active	.03	.01	.13	1.98	.048	.03	.01	.16	2.46	.014
R²	.07					.06
Adjusted R²	.06					.05
				Nonsocial media friend					Nonsocial media friend
Intercept	.45	.07		6.61	<.001	.41	.07		6.15	<.001
Gender	.00	.03	.00	−.03	.98	.03	.02	.06	1.36	.18
Age	.00	.00	.02	.53	.60	.00	.00	.04	.86	.39
Facebook passive	.03	.02	.12	1.82	.07	.03	.02	.12	1.88	.06
Facebook active	−.02	.01	−.08	−1.15	.25	−.01	.01	−.05	−.80	.43
R²	.01					.01
Adjusted R²	.00					.01
				Stranger					Stranger
Intercept	.19	.07		2.94	.003	.25	.07		3.59	<.001
Gender	.00	.02	.00	−.04	.97	.04	.03	.07	1.53	.13
Age	.00	.00	−.10	−2.29	.023	.00	.00	.02	.51	.61
Facebook passive	.01	.01	.02	.35	.73	.00	.02	.01	.11	.91
Facebook active	.06	.01	.27	4.28	<.001	.04	.01	.17	2.54	.011
R²	.10					.03
Adjusted R²	.09					.03

*p < .05; **p < .01; ***p < .001.

Similar patterns were found in the extraordinary situation. Active Facebook use also positively predicted helping social media friend and stranger and negatively predicted helping sibling. There was no significant association between active use and helping nonsocial media friend. Thus, H2a was not supported and H2b was supported. For passive Facebook use, both H3a and H3b were supported that passive use was associated with helping sibling and social media friend in the ordinary situation. In the extraordinary situation, passive use only predicted helping sibling. Thus, H4 was supported.

To better understand the patterns of helping, mixed-design, repeated-measures analyses of covariance (ANCOVAs) (controlling for gender and age) were conducted to test the interaction effects. An active Facebook use (between-subject) × passive Facebook use (between-subject) × relationship (within-subject) × situation (within-subject) four-way mixed ANCOVA showed a significant interaction effect, F(510, 888) = 1.19, p = .013, η²_p = .41. An active Facebook use × relationship × situation three-way mixed ANCOVA also indicated a significant interaction effect, F(72, 888) = 1.55, p = .003, η²_p = .11. However, a passive Facebook use × relationship × situation three-way mixed ANCOVA did not demonstrate a significant interaction effect, F(72, 888) = 1.21, p = .12, η²_p = .09. To test the significant active Facebook use × relationship × situation three-way interaction more closely, follow-up ANCOVAs were conducted for ease of exposition. The analyses of the ordinary and extraordinary helping situation were separately conducted.

For the ordinary situation, the two-way active Facebook use × relationship interaction was significant, F(72, 888) = 1.99, p < .001, η²_p = .12. Independent t test showed that participants high in active Facebook use (1 SD above the mean score; M = 63.26%, SD = 22.83%) were more likely to aid a social media friend than participants low in active Facebook use (1 SD below the mean score; M = 45.05%, SD = 30.87%), t(182) = 4.63, p < .001, Cohen’s d = .66 (Levene’s test showed that equal variances were not assumed so the number of degrees of freedom and t value were adjusted). Also, participants high in active Facebook use (+1 SD; M = 51.05%, SD = 28.33%) were more likely to help a stranger than participants low in active use (−1 SD; M = 25.54%, SD = 28.79%), t(185) = 6.08, p < .001, Cohen’s d = .88 (adjusted df and t value). No significant differences were found between high and low active Facebook use in helping sibling, t(185) = 1.59, p = .11, Cohen’s d = .28; nor nonsocial media friend, t(185) = .38, p = .71, Cohen’s d = .07. (see Figure 1(a) and (b)).

Figure 1.

(a) Helping by relationship type and Facebook use for ordinary situation. (b) Helping by relationship type and Facebook use for extraordinary situation.

For the extraordinary situation, the two-way interaction active Facebook use × relationship, F(72, 888) = 1.84, p < .001, η²_p = .12, was also significant. Participants high in active use were more likely to aid a social media friend and stranger than participants low in active use, +1 SD (M = 66.74%, SD = 21.11%) versus −1 SD (M = 45.74%, SD = 31.82%), t(175) = 5.39, p < .001, Cohen’s d = .78 for social media friend (adjusted df and t value); and +1 SD (M = 57.79%, SD = 28.75%) versus −1 SD (M = 39.70%, SD = 32.05%), t(185) = 4.03, p < .001, Cohen’s d = .59 for stranger; but no difference between high and low active Facebook use in helping sibling, t(185) = 1.63, p = .11, Cohen’s d = .22; nor nonsocial media friend, t(183) = 1.60, p = .11, Cohen’s d = .24 (equal variances were not assumed) (see Figure 1(a) and (b)).

Discussion

This study shows that individuals high in Facebook use, particularly active use, are generally more willing to risk negative consequences to help other individuals in need in both ordinary and extraordinary situations than were the other individuals. Previous studies have focused on investigating online investment in social relations and the associated expected reciprocal altruism (i.e., social capital) on social media (e.g., Ellison et al., 2007; Liu et al., 2016; Williams, 2006). However, no study has examined the association between social media use and costly altruistic behavior. This study is among the first to illustrate the differences and interactions between active and passive Facebook use and off-line costly helping toward genetically related and unrelated others involving high and low biological cost. This study provided theoretical contributions to the social media literature.

The results support the hypothesis that social media use can raise the perceived relatedness of people in need and reduce the power of genetic relatedness in helping. Particularly, active social media use can strengthen the perceived relatedness of persons in need more strongly than passive social media use. Consistent with the previous studies (Burnstein et al., 1994; Graziano et al., 2007), the findings of the preliminary analysis showed that, following Hamilton’s (1964a, 1964b) rule of inclusive fitness, individuals are more willing to help siblings, followed by friends (social media and nonsocial media) and strangers. However, social media use, particularly active Facebook use, can serve as a motivator to decrease the influence of genetic relatedness in helping.

Active Facebook use can broaden a sense of connectedness with genetically unrelated others and can facilitate the perceived relatedness of individuals in need. Active Facebook users are more willing to help social media friends (H1b and H2b) and strangers (H1d) in both situations involving high and low biological cost. Because of its lower cost of establishing and widening a larger network of weaker ties instead of maintaining small group relationships with relatives, individuals can use social media to connect to genetically unrelated nonrelatives to enhance the chance of gaining delayed reciprocal benefits (Ellison et al., 2007, 2011). Active use can increase the perceived relatedness of genetically unrelated social media friends. Thus, people are more willing to help social media friends, even if the (biological) cost of helping would be low or high. Also, consistent with the previous studies that social media urge individuals to connect with stranger (Ellison, Vitak, et al., 2014; Liu et al., 2016), and online prosocial acts mirror off-line prosocial interactions (Wright & Li, 2011), active Facebook use is associated with helping strangers offline whenever the biological cost is low or high because of their increase in perceived relatedness of strangers.

This study predicted that active Facebook users would help nonsocial media friends when the biological cost is low (H1c). The results found no significant associations between active use and helping nonsocial media friends in both the ordinary and extraordinary situation. The findings imply that individuals utilize social media to gain social resources as an investment in social relations in order to obtain delayed benefits. Active users are more likely to help strangers because they have the potential to be social media friends and gain reciprocal altruism. However, nonsocial media friends are perceived as having less potential to obtain mutual benefits than strangers. According to theory of reciprocal altruism (Trivers, 1971), individuals provide help because initiating and keeping long-term relationships can cultivate delayed benefits. Strangers have the possibility to be social media friends later and thus offer delayed benefits via reciprocity; however, nonsocial media friends are “friends” that people already know but are not friends on social media. A possible explanation is that people already know that those nonsocial media friends have a lower chance to provide delayed benefits to oneself, so they do not “friend” each other on social media. As individuals perceive that nonsocial media friends would not provide delayed interests, their social media usages are not associated with helping those nonsocial media friends regardless of low or high biological costs.

According to Hamilton’s rule of inclusive fitness, individuals should be more willing to help genetically related others, that is, siblings. However, the findings showed no difference between high and low active users in helping siblings, and even negative correlation between active use and helping siblings in both situations (H1a and H2a). The increase in the sense of connectedness and perceived relatedness of genetically unrelated others in need due to active social media use could significantly reduce the perceived genetic relatedness. A possible explanation is that individuals “friend” their siblings on Facebook so they classify siblings who have been “friended” as social media friends. However, they identify siblings who have not been “friended” on social media as having a lower chance to offer mutual benefits to oneself. Thus, individuals predict that siblings, who share 50% of their genes (Burnstein et al., 1994) but are nonsocial media friends, would not favor the survival and reproduction of their own genes. Another possible explanation is that, as older participants are more likely to help siblings than younger participants (see Table 1), Facebook users would tend to help siblings when they get older. The above explanations and negative associations still need further investigations.

In contrast, passive Facebook users who only perform indirect exchanges with nonsignificant others follow the rule of biological fitness and tend to help kin in both ordinary (H3a) and extraordinary situations (H4). In ordinary situations when the biological cost is low and the delayed benefit is expected to be higher than the cost of helping, as expected (H3b), passive Facebook users are more willing to help social media friends to gain social resources. However, when the biological cost is expected to be higher than the benefit, passive users do not pay the cost to help. The results imply that direct communication on social media (e.g., posting status updates, commenting on friends’ walls) can be more successful in generating a broader sense of relatedness than indirect communication (e.g., browsing, scrolling through others’ posts). Previous studies have focused on the negative consequences of passive social media use (e.g., Rousseau et al., 2017; Shaw et al., 2015; Verduyn et al., 2015). Although many studies have examined positive effects of active social media use on subjective well-being (Verduyn et al., 2017, for a review), this study is the first to investigate the positive outcomes of active social media use on social behavior (i.e., broadening a sense of connectedness with others).

In terms of practical significance, the regression analyses showed that helping a social media friend explains 6% (ordinary situation) and 5% (extraordinary situation) of variation, and helping a stranger explains 9% (ordinary situation) and 3% (extraordinary situation) of variation. Figure 2 displays the scatterplot showing the observed percentage helping scores and predicted percentage helping scores for the most accurate model, that is, predicting helping stranger in the ordinary situation. These results suggest that Facebook usage predicts substantive helping behavior. In this condition, it is critical to recognize that helping behavior can be determined by multiple factors. The results provide empirical supports that Facebook usage (particularly active usage) is one of the significant predictors of real-life helping behavior. Because of the social significance of prosocial behavior, the small effect sizes shown in this study can still be valuable (Ferguson, 2009).

Figure 2.

Scatterplot of the regression of helping stranger in ordinary situation on gender, age, and active and passive Facebook use.

On a more general level, the findings appear to suggest that the association between Facebook usage and costly off-line behavior can be incorporated within the evolutionary perspective. Evolutionary theory has been widely used to unify incompatible models across the behavioral and social sciences because it explains the fundamental functions of the human brain in maximizing adaptation and fitness (e.g., Barkow, Cosmides, & Tooby, 1992; Gintis, 2007; Mesoudi, Whiten, & Laland, 2006; Price, Brown, & Curry, 2007; Tooby & Cosmides, 2007). By adopting the evolutionary approach as a unifying theoretical framework, results across different theories in different fields of social science can be predicted, compared, and replicated, and it is then possible that the replicability crisis can be alleviated (Muthukrishna & Henrich, 2019). In social media research, the evolutionary perspective can be adopted to explain social media use for cooperation. Human beings are ecologically successful because humans are evolved to be reciprocal and cooperative, and they can now perform reciprocity online and offline (Ng, 2019).

This study had some potential limitations. First, the measures of active and passive Facebook use and hypothetical costly helping situations were self-reported. Although measuring behavioral outcomes provides real reactions to help others in need, the vignette method avoids real biological risks to participants. However, future studies can contain behavioral measures of the participants’ social media usages to minimize biased responses. Second, as the active and passive Facebook use were not manipulated, this study can only show that the types of Facebook use and costly helping were associated. The causal influence of them on the intention to help others cannot be assumed. Future studies should conduct randomized experiments to test the causal effect of passive and active Facebook use (e.g., Verduyn et al., 2015) on costly helping behavior. Third, only one ordinary situation and one extraordinary situation were offered to the participants. The results may not generalize to other situations involving low and high costs. Future studies containing three to five ordinary and extraordinary situations should be of interest.

Fourth, the reason why active Facebook users were more willing to help others in need may simply be because they were more agreeable. Although agreeableness was only correlated with photos post but not other SNSs activities (Liu & Campbell, 2017, for meta-analysis), future research should consider the potential moderating effect of agreeableness on the association between Facebook use and costly helping behavior. Fifth, the findings indicated that older participants were more willing to help siblings in both ordinary and extraordinary situations, whereas younger participants were more willing to aid strangers in the ordinary situations (see Table 1). The results imply that older people would follow the rule of inclusive fitness to help genetically related siblings regardless of high or low biological cost and younger people have a higher level of perceived relatedness. It is worth further investigating how age would affect the Facebook use-helping relationships. Sixth, a meta-analysis showed that frequency of SNS use or duration time were associated with reciprocal altruism (i.e., social capital) (Liu et al., 2016). The frequency of Facebook use, which was not included in this study, should be controlled in future research to test the relationships between active and passive use and off-line helping. Finally, social media are often used for impression formation and active social media users may simply be more socially desirable. Future studies should take into account the potential mediating effect of impression formation that may explain the association being tested.

Appendix 1

Items of Passive and Active Social Media Use

Passive Facebook use (M = 4.72; SD = 1.26; α = .86)

How often do you look at your friends’ status updates?

How often do you scroll through your news feed?

How often do you look at your friends’ pages?

How often do you look at your friends’ pictures?

Active Facebook use (M = 4.16; SD = 1.36; α = .85)

How often do you post status updates?

How often do you react and comment on friends’ posts?

How often do you send private messages to your friends?

How often do you share links?

Footnotes

Article Notes

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