How To Measure Social Ties On Facebook

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1 Trust, Reciprocity and the Strength of Social Ties: An Online Social Network based Field Experiment Ravi Bapna 1, Alok Gupta 1, Sarah Rice 2, Arun Sundararajan 3 (VERY PRELIMINARY AND INCOMPLETE DRAFT) 1. Introduction A man's ethical behavior should be based effectually on sympathy, education, and social ties ~Albert Einstein Put not your trust in money, but put your money in trust. ~Oliver Wendell Holmes Sr. We study how the strength of social ties is related to economic choices made by pairs of individuals who share a social relationship. We draw our information about social ties from the Facebook social network which comprises billions of connections of varying strength between acquainted individuals. We employ an economic experiment using monetary incentives to examine whether trust and reciprocity in economic settings might vary as a function of the strength of these ties. Specifically, we conduct the investment game [henceforth IG, see Berg, Dickhaut and McCabe (1995)] between pairs of Facebook friends, using the rich prior interaction data contained in this online social networking platform as a source of variation in the strength of ties between players. We achieve our data collection using a specialized Facebook software application we have designed, developed and implemented 4 for the purpose of this experiment. The software application allows us to recruit subjects from Facebook using a range of randomization strategies, and to subsequently have randomly paired subjects with varying strength of social ties play the investment game. Briefly, our experiment comprises three treatments: a baseline anonymous treatment in which two individuals who do not know each others identity are paired to play the IG; a non-anonymous one-degree of-separation game in which two subjects who are friends on Facebook are paired to play the IG and are told each others identity, and a non-anonymous two-degrees-of-separation game in which two subjects who are not friends on Facebook but who share at least one common friend are paired to play the IG and are told each others identity. In the ensuing IG s, the monetary amounts sent by the senders are an 1 University of Minnesota 2 University of Connecticut 3 New York University 4 1

2 economic measure of trust, and the amounts returned by receivers are an economic measure of reciprocity. Our experimental data yields variation between these measures across the different pairings of subjects. We are also able to construct measures of the strength of the social tie between each of these pairs that is exogenous to our experiments and is based on prior Facebook interaction between the individuals. (We use established metrics to measure the strength of these social ties; see Gilbert and Karahalious (2010)]. We hope to shed new light on how trust and reciprocity in economic exchange relate to social distance and the strength of social ties. Our approach represents progress over prior experimental approaches that study the impact of strength of ties on individual trust. For instance, by using an exogenously created social network as our basis for inferring social ties, we avoid problems of endogeneity and generalizability which arise as a result of artificially created networks. For example, most prior experiments have attempted to build artificial social networks in a laboratory or in a similarly contrived on-line setting [e.g. Siddharth and Watts (2010)], leading to concerns regarding the robustness of the network as well as the nature of what are called social ties. An important distinguishing aspect of our study is that we utilize a pre-formed network that is exogenous to the experiment. This design choice allows us to use actual social relationships as the basis for our social ties. Moreover, given the popularity of Facebook and the fact that it is an online social network, we are able to establish a robust assessment of the strength of these preexisting ties without this measurement confounding our experiment in any way. We can then employ these measures to manipulate the Sender/Receiver pairings in the ensuing IG s. We also use a well established game which is widely used in experimental economics to generate quantifiable measures of trust and reciprocity. Thus, our study yields unprecedented data set for estimating the economic value of the strength of ties in an on-line social network context. The following section discusses our motivation and some related literature. We then provide a brief description of the investment game and the specific measurements that proxy for the strength of social ties within pairs. Next we report some very preliminary findings from our pilot study. This is a report of research in progress, and we do not draw too many conclusions from the limited amount of data gathered in the pilot study; however, we are encouraged by our preliminary results as we move forward with our larger data collection event. 2. Motivation, Background and Methodology Our work is motivated by two related observations. On one hand, despite the rapid growth of online social networking, the resultant social capital has not yet been shown to directly influence e-commerce activity; much of which continues to occur between anonymous strangers. This represents an opportunity 2

3 for a several reasons. First, there is a wealth of data available about social ties online, and one would expect such information to have vast potential in improving the efficiency of online markets. Second, a variety of exchange in the offline ( real ) world is often mediated by pre-existing social ties, and one of the promises of Internet commerce seems to be that it can bring these aspects of small community exchange to a larger and more dispersed group. Furthermore, the vast majority of experimental and theoretical work on trust has, paradoxically, involved one-shot games played between strangers. Perhaps, as we consider the possibility of integrating social networks into electronic markets, it is first necessary to have a better understanding of the role that social capital takes in reducing frictions for e-commerce activity. Our work contributes towards this end as we investigate the relationship between social distance and trust using robust experimental methods and credible measures of social distance. 2.1 Trust and Trustworthiness The dynamics of trust and trustworthiness have a wide array of applications, including the facilitation of social and political action, as highlighted by recent events in Egypt where much of the uprising was enabled by social media outlets such as Facebook and Twitter. Because the expression of alternative political views could have been potentially dangerous under the current regime, it was important for dissenting individuals to trust those with whom they were interacting in each respective online medium. Evaluating the trustworthiness of others within utilized social networks proved critical in trusting whether controversial political views would be met with agreement or dissent. The result was the evolution of a community where strength in numbers led to an uprising that will likely result in ongoing political and social reform. Trust and trustworthiness also play an important role in facilitating online economic exchange, as demonstrated when considering the dynamics within buyer and seller dyads. For example, upon deciding to engage in an online economic transaction a buyer must move first and pay for the good before it is shipped. In other words, the buyer must initially trust that the seller will deliver the good as promised, and in doing so allocate payment to that seller before receipt of the good. If a seller s trustworthiness is deemed to be low it is less likely the buyer will trust that seller and the exchange will not occur. Some notion of trust as an important determinant of outcomes permeates a variety of academic disciplines, including economics (e.g. Dasgupta 1988), social psychology (e.g. Leqwicki and Bunker 1995, Lindskold 1978), and marketing (e.g. Anderson and Weitx 1989, Dwyer et al. 1987). Universally, trust can be defined as the willingness of a party to be vulnerable to the actions of another party based on the expectation that the other will perform a particular action important to the trustor, irrespective of the ability to monitor or control the other party (Mayer et al. 1995). Trust has also been referred to as an 3

4 important lubricant of a social system (Arrow 1974) and has been shown theoretically to be important in economic exchanges. Trust has also been shown to reduce transaction costs by mitigating opportunistic behavior (Bromiley and Cummings 1995). There is precedent to viewing trust as that which ensues when an individual calculates the costs and/or rewards of cheating, and upon determining that it would not be in the best interest of one party to cheat the assumption is that party can be trusted (Lindskold 1978, Akerlof 1970). Evolutionary models suggest that trust maximizes genetic fitness and therefore is likely to eventually emerge, in spite of self-interested motives. This suggests that trust can be viewed as a behavioral primitive that guides behavior in new situations (Berg et al. 1995). Our conceptualization of the connection between trust and social ties draws from Burt (1992) who analyzes the (well known) observation that the presence of a shared friend between two friends (or in the language of social networks, triadic closure in the friendship) is likely to lead to a greater level of trust between them. Burt examines two competing hypotheses for this assertion: the bandwidth hypothesis, which suggests that the presence of the shared friend adds a channel of information exchange which facilitates greater trust, and the echo hypothesis, which theorizes that the shared friend acts as a credible threat which prevents reneging and thus increases trust. We do not aim to disentangle these two hypotheses in our study, although it is possible that our experimental platform might be used for this purpose in the future. However, we do account for a greater propensity for trust in triadic relationships, while not relying exclusively on it: one of the many inputs into our measure of the strength of a social tie is the number of shared friends. Prior empirical research examining differential trust (as opposed to absolute trust between strangers) [Leider et al. (2009)] has been restricted to highly specialized networks, or has been limited to revealing gender or ethnicity (Bohnet and Zeckhauser 2004; Eckel and Grossman 2006; Eckel and Wilson 2003; Fershtman and Gneezy 2001). Experimental work incorporating game theoretic design offers insights regarding factors that can impact individual levels of trust in economic exchanges (e.g. Bolton et al. 2001, Rice 2011). See Camerer 2003 for a more comprehensive review of experimental work with otherregarding preferences. 2.2 The Strength of Social Ties The concept of tie strength can be defined as the following: The strength of a tie is a combination of the amount of time, the emotional intensity, the intimacy, and the reciprocal services which characterize the tie (Granovetter 1973). Two types of ties are commonly referred to in the literature, weak ties and strong ties. A weak social tie exists between two individuals who are not closely connected, such as casual 4

5 acquaintances or co-workers who do not interact regularly, while strong ties exist between close friends who communicate frequently. Studies on the effects of tie strength show both strong and weak ties to have an impact on information dissemination (e.g. Granovetter 1973), job seeking (e.g. Granovetter 1974, Bridges and Villemez 1986), and even income levels (e.g. Simon and Warner 1992, Gorcoran et al. 1980). Experimental work that investigates the formation of social ties using a public good experiment shows that tie formation is contingent upon the success of the game (Van Dijk et al. 2002). The aggregation of individual ties comprises a social network, and the importance of social network structure on the formation of trust has been touted in the social psychology literature. Additionally, work by Karlan et al. (2009) models a setting where social structures are used as collateral in procuring loans, showing that networks can build trust when agents use their connections as social collateral. While the importance of social ties and network structure on social and economic outcomes is clearly of interest to the academic community, to date there are few empirical contributions to this body of literature. Recent studies on the effects of social structure on other regarding behavior include work by Leider et al. (2007), which maps a friendship network using self reported surveys to evaluate strength of ties between individuals. Trust is measured as a function of social distance and the authors find that friends exhibit higher levels of trust than non-friend pairings. Other experimental work investigating the effects of social ties on trust and altruism does so by first creating a network in the laboratory, and then testing behavioral effects on those same networks (Di Cagno and Sciubba 2008). Our work differs from these earlier studies in that we do not try to contrive an artificial network in a laboratory, or rely on self-reported measures regarding friend relations. Instead we turn to the already established network provided by Facebook and estimate strength of social ties based on quantifiable information found on individual Facebook pages. By employing a pre-formed network, such as Facebook, we avoid endogenity issues that arise from spurious network formation in a laboratory, or problems of self-reporting that often occur in survey responses.another unique aspect of this study is that we seek to establish primitives regarding the association between trust and strength of social ties using an economic experiment specifically designed to quantify measures of trust and trustworthiness. The following section discusses our Investment Game in greater detail, as well as our specific approach to measuring the strength of social ties. 3. Methodology 5

6 3.1 The Investment Game To address our questions regarding the relationship between social distance and trust we have developed a Facebook application which will be advertised using Facebook s application distribution mechanism. This will induce random exogenous variation in the network structure of the chosen participants. Once individuals sign up to play, our Facebook Investment Game (FIG) proceeds as follows. Subjects play in pairs where one person is called the Sender and the other person is called the Receiver. The senderreceiver pair could be matched anonymously, or between immediate friends (one-degree treatment), or between friends-of-friends (two-degree treatment). The design is between subjects, meaning participants only participate in one of the three manipulations (one degree, two degree, or anonymous). We measure the strength of ties between individuals to ensure consistency among social distance, ensuring that all onedegree treatments are relatively similar in strength, as are all two-degree treatments. At the start of the investment game each Sender is given $10 which can be sent to the Receiver. Any amount sent is tripled and upon receipt of this investment the Receiver decides how much to return to the Sender. This single shot game concludes after the Sender learns how much of the investment has been returned. Players are paid by depositing money into their designated PayPal account or by mailed check. 5 The game is depicted in Figure 1. Sender is given $10 and chooses amount to send Reciver Amount Sent is multiplied by 3 Receiver decides how much to return to Sender Amount Sent = The Trust Measure Amount Returned = The Reciprocity Measure Figure 1: Schematic of the Investment Game While the equilibrium for a single shot Investment Game is one where Receivers expropriate the entire amount invested by Senders (and so Senders opt not to invest), Berg, Dickhaut and McCabe (1995) show that reputation concerns can increase instances of cooperative behavior. In their study, when social histories were shared second movers were less likely to keep the entire investment amount and were shown to return on average between 1/3 and 1/2 of the total amount sent by first movers. With this in mind, we are interested in whether reputation concerns are more salient in a close tie relationship (one- 5 Sender payoffs: $10 (amount sent) + (amount returned); Receiver payoffs: 3x (amount sent) (amount returned) 6

7 degree separation) versus a loose tie relationship (two-degree separation), using an anonymous pairing (no social connection between players) as the control treatment. If this is the case, we expect both the investment and return amounts to vary as a function of the type of social connection. 3.2 Measuring The Strength of Social Ties A critical aspect of our study is that we need to quantify the strength of social ties between individuals who participate in our experiment. We use an approach developed by Gilbert and Kavahalois (2009) (hereafter GK) to estimate tie strength based on readily available information found on individual Facebook pages. The GK study finds two primary factors that can help explain the majority of their tie strength model and therefore we use these two pieces of information to proxy for the strength of social ties between pairs. One measure they call intimacy and it is measured as the number of mutual friends shared between two people. The other measure they call intensity and it is measured as the number of wall posts exchanged between two people. Our application allows us access to both of these measures, and this is what we use to estimate the strength of social ties between two players in the one-degree and two-degree separation treatments. As a manipulation check we also administered a post experimental survey where we asked subjects about their perceived closeness to their matched partner. Respondents chose from a seven point Likert scale, where 7 was very close and 1 was not close at all. In that same survey we also asked subjects to describe their general thought process in making game decisions, and whether they had any offline communication with their partner. If subjects did indicate offline communication occurred we asked them to describe the nature of that communication. 4. Pilot Test and Preliminary Results (Note to Carlson audience: New data is being collected now and will be presented on Friday 4/22!! The following section summarizes our pilot data only.) Our first pilot test was conducted among students at the Indian School of Business over a five day window. Solicitations were distributed via and a total of 52 users signed up for our experiment. We manipulated two primary treatments, the anonymous treatment where subjects do not have any information about the person they are paired with, and the non-anonymous treatment where subjects are told the name of the person they are paired with. The names of pairings are hot linked to the respective Facebook pages, allowing partners to easily access the page of the person they are paired with. We also collected metrics to estimate social distance between players (the number of shared wall posts) and to estimate centrality measures (the number of mutual friends). Of the possible 26 sets of pairings, we 7

8 allocated 13 to the anonymous treatment and 13 to the non-anonymous treatment. Figure 1 illustrates the social network of our subjects, as gleaned off the Facebook site. Figure 2: Facebook social ties of th experimental subjects in our pilot study Our results show mean investments and mean returns were higher in the non-anonymous treatments, indicating that cooperation was more likely when pairs knew each other. Tables 1a and 1b show the mean amounts sent and returned, as well as sender receiver profits respectively. Table 1a: Mean amounts Sent and Returned in Non-Anonymous vs. Anonymous Treatments Mean Amount Sent Mean Amount Returned 8

9 Non-Anonymous $7.79 $8.12 Anonymous $5.62 $6.71 Table 1b: Sender and Receiver Profits in Non-Anonymous vs. Anonymous Treatments Mean Sender Profit Mean Receiver Profit Non-Anonymous $12 $14 Anonymous $11.08 $10.17 Next we assess whether strength of ties, measured as the number of shared wall posts between pairs, has an influence on the economic decisions of Senders and Receivers. We find that the amounts sent and returned increase with the number of shared wall posts, suggesting a possible relationship between social distance and trust/reciprocity in this setting. Figure 2 illustrates this finding below. 9

10 Figure 2: Amounts Sent and Returned as a Function of Shared Wallposts While the trend shown is encouraging, this small data set requires caution when making any preliminary inferences as to overall findings. Still, we are hopeful these early results suggest we will find a more robust relationship between social distance and trust/reciprocity in the full-scale data analysis currently in progress. In addition to the relationships shown above, we also plan to look at the centrality of individuals within each network cluster and use this as an additional covariate in the analysis of Sender and Receiver decisions. IV. Conclusion Our pilot study has yielded encouraging preliminary results. Given the small number of observations in the pilot, we simply view this as a validation of our experimental approach, indicating that the strength of social ties is actually correlated with trust and reciprocity, and supporting the feasibility of our subsequent phases of broader data collection. Our research will contributes to the academic literature by further developing work in the area of on-line social networks. To date the literature is silent as to the potential sociological and economic differences 10

11 between well defined social networks. Developing a framework for discussing these differences, and testing their effects on behavior and decision making, is an important aspect of our study. We believe our study can serve to further lower frictions and improve the efficiency of Internet based commercial activity, while also speaking to practical applications in the areas of on-line product marketing and development. We also expect this research to serve as a foundation for designing the next generation of social capital based online trust and reputation mechanisms. Our Facebook application demonstrates a way to conduct other game theory experiments, such as the dictator game and the ultimatum game, within a social network. This raises possibilities for leveraging our platform to measure other behaviors such as altruism and distributional fairness as a function of the strength of social ties. References Akerlof, George A. (1970). "The Market for 'Lemons"; Quality Under Uncertainty and the Market Mechanism." Quarterly Journal of Economics, 84 (August), Anderson, Erin, Leonard M. Lodish. and Barton A. Weitz (1987), "Resource Allocation Behavior Conventional Channels." Journal of Marketing Research, 23 (February), Berg, Joyce, John Dickhaut and Kevin McCabe (1995), "Trust, Reciprocity and Social History". Games and Economic Behavior, 10, pp Bohnet, Iris and Zeckhauser, Richard (2004). Trust, Risk and Betrayal. Journal of Economic Behavior and Organization. 55(4), pp Bromiley, P. and Cummings, L.L Transactions costs in organizations with trust. In R. Bies, B. Sheppard and R. Lewicki (eds), Research on Negotiations in Organizations, Vol. 5: Greenwich, CT: JAI Press. Camerer, C. (2003). Behavioral Game Theory: Experiments in Strategic Interaction. Princeton University Press, Princeton. Dasguta, P. (1988). Making and Breaking Cooperative Relations. Basil Blackwell, New York. DiCagno, D., Sciubba, E. (2008). The Determinants of Individual Behavior in Network Formation: Some Experimental Evidence. Advances in Decision Making Under Risk and Uncertainty. 42(4). Dwyer. F Robert, Paul H. Schurr. and Sejo Oh (1987). "Developing Buyer-Seller Relationships." Joumai of Marketing, 51(April) Eckel, C. and Grossman, P. (2006). Differences in the Economic Decisions of Men and Women: Experimental Evidence in Handbook of Experimental Results, edited by C. Plott and V. Smith. Elsevier, New York. 11

12 Eckel, C. and Wilson, R. (2003) The Human Face of Game Theory: Trust and Reciprocity in Sequential Games, in Interdisciplinary Lessons from Experimental Research, edited by Elinor Ostrom and Jimmy Walker. Russell Sage Foundation. Fershtman, C. and Gneezy, U. (2001). Discrimination in a Segmented Society: An Experimental Approach. Quarterly Journal of Economics. 115(3), pp Gilbert, E. and Karahalios, K. Predicting Tie Strength with Social Media. CHI Conference proceedings Granovetter, M. (1973) The Strength of Weak Ties. The American Journal of Sociology, 78(6). Granovetter, M. Getting a Job: A Study of Contacts and Careers. University of Chicago Press, Iyengar,R. Han, S. Gupta, S. (2009). Do Friends Influence Purchases in a Social Network? Harvard Business School Marketing Unit Working Paper No Karlan, Dean. Mobius, M., Rosenblat, T., Szeidl, A. (2009). Trust and Social Collateral. Quarterly Journal of Economics. 124(3). Leider, Stephen, Mobius, M., Rosenblat, T. and Do, Q. (2009). Directed Altruism and Enforced Reciprocity in Social Networks. Quarterly Journal of Economics. Lewicki, R.J. and B.B. Bunker (1995). Trust in relationships: A model of trust development and decline. In Bunker, B.B. and J.Z. Rubin (Eds.). Conflict, cooperation and justice Jossey- Ba, San Francisco. Meyer, R. Davis, J. Schoorman, D. (1995). An Integrative Model of Organizational Trust. The Academy of Management Review. 20(3). Rice, S. Reputation and Uncertainty in On-line Markets: An Experimental Study. Information Systems Research (forthcoming 2011). Trusov, M. Bucklin, R. Pauwels, K. (2009). Effects of Word of Mouth Versus Traditional Marketing: Findings From an Internet Social Networking Site. Journal of Marketing. 73(5). Williamson, O. E. (1991). Calculativeness, trust, and economic organization. Journal of Law and Economics. 36 (1),