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Quantitative Marketing and Economics

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23-05-2020

Displaying things in common to encourage friendship formation: A large randomized field experiment

Authors: Tianshu Sun, Sean J. Taylor

Published in: Quantitative Marketing and Economics | Issue 3/2020

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Abstract

Friendship formation is of central importance to online social network sites and to society, but can suffer from significant and unequal frictions. In this study, we demonstrate that social networks and policy makers may use an IT-facilitated intervention – displaying things in common (TIC) between users (mutual hometown, interest, education, work, city) – to encourage friendship formation, especially among people who are different from each other. Displaying TIC may update an individual’s belief about the shared similarity with another and reduce information friction that may be hard to overcome in offline communication. In collaboration with an online social network, we design and implement a randomized field experiment, which randomly varies the prominence of different types of things in common information when a user (viewer) is browsing a non-friend’s profile. The dyad-level exogenous variation, orthogonal to any (un)observed structural factors in viewer-profile’s network, allows us to cleanly isolate the role of individuals’ preference for TIC in driving network formation and homophily. We find that displaying TIC to viewers may significantly increase their probability of sending a friend request and forming a friendship, and is especially effective for pairs of people who have little in common. Such findings suggest that information intervention is a very effective and zero-cost approach to encourage the formation of weak ties, and also provide the first experimental evidence on the crucial role of individuals’ preference (versus structural embeddedness) in network formation. We further demonstrate that displaying TIC could improve friendship formation for a wide range of viewers with different demographics and friendship status, and is more effective when the TIC information is more surprising to the viewer. Our study offers actionable insights to social networks and policy makers on the design of information intervention to encourage friendship formation and improve the diversity of the friendship, at both an aggregate and an individual level.

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Several major SNs have made increasing the number of friends a key goal in their operations (Price 2012): e.g. Linkedin aims to get a user to reach X friends in Y days, and Facebook and Twitter use similar goal metrics.

The viewer may either have little information about the profile’s interest, or have an biased perception (Goel et al. 2010). In both scenarios, the displayed TIC information would help update the viewer’s belief.

Despite lively discussions on the importance of friendship diversity (Kossinets and Watts 2009; Eagle et al. 2010; Granovetter 1977) in facilitating interactions among different groups (Bakshy et al. 2015), very little is understood about how online social networks can actively help ‘build’ the weak ties among people with different background.

Finally, our study also extends a large stream of literature in Marketing and IS on the reduction of information friction in online platforms and marketplaces. Previous literature has focused on how IT artifacts (online reviews, product recommendations) can be used to reduce friction in user-product interactions Fradkin (2017), Forman et al. (2008), Oestreicher-Singer and Sundararajan (2012), and Fleder and Hosanagar (2009). Our study suggests a new route in which IT could reduce the friction in user-user interaction, and open up a new area of research on the role of IT in moderating the structure, evolution and value of user-user network (Oestreicher-Singer et al. 2013; Hosanagar et al. 2013).

For instance, those viewer-profile pairs with 2 TIC may have a higher friendship formation rate than those with only 1 TIC, not because of the additional TIC at display, but because pairs with 2 TIC are likely to have more mutual friends and more interaction opportunities (i.e. structural factors) than pairs with 1 TIC. In Online Appendix C, we confirm the above insight and empirically demonstrate that the correlation between number of things in common in a pair and the corresponding friendship formation rate is not only biased, but even opposite to the true causal effect in sign (Fig. 24)

Observational data often lacks of detailed information on the structural factor such as interaction history and friendship structure (McPherson et al. 2001), which is needed to control for meeting bias and triadic closure. Even more fundamentally, the endogenous correlation between things in common, meeting bias, and network structure makes it almost impossible to isolate the role of preference in friendship formation from observational studies (Currarini et al. 2010).

We use ‘articulated friendship’ to denote that the friendship on SN sites is a unique type of social network connection, which is valuable by itself (in the creation and spread of information) and may differ from the offline friendship. For instance, the interaction frequency and tie strength of articulated friendship on average may be lower (weaker) as compared to the offline friendship.

Specifically, the viewer and profile can be represented as two high-dimensional n × 1 vectors: each row representing the value of a profile field entry or a page like decision. Their TIC are calculated from the intersect of the two vectors.

We also check the balance of a series of user covariates (e.g. viewer/profile gender, friend count) across the control and treatment groups and do not find any significant differences. All tables are available upon request.

Treatment effect from variance estimators yields the same point estimate and more statistically significant results.

As discussed in the section above, we focus on discussing the treatment effect for those pairs with 1 or 2 TIC, and present the results for pairs with 3 TIC in Figs. 13 and 14

Same pattern holds for pairs with 3 actual TIC (Figs. 13 and 14) but sample size is too small as shown in Fig. 9.

We are unable to find any evidence that the treatment induces any significant positive or negative effects on the rate that requests are accepted (see Fig. 15 for detailed analysis).

For results in Figs. 16, 17 and 18, we also have tables with detailed regression results (available upon request)

Without loss of generalizability, we focus on the effect of one type of TIC (‘a’) in the discussion.

Social influence spread on existing ties is strongest when the tie shares mutual friends and multiple TICs.

Though preference over similar others is a underlying driver of homophily among weak ties, the preference, by itself, does not reinforce tie formation among people who already share mutual friends thus cannot lead to a significant level of structural homophily. Preference may connect people with different background, but the rest of network evolution might be driven by structural factor such as meeting opportunities and triadic closure

Another potential mechanism is attention disruption: showing TIC on a profile card would disrupt the monotonicity of seeing many profile cards in a row. Such additional attention may lead to an increase likelihood of friendship formation. The attention disruption explanation suggests that the effect of TIC is stronger in the early stage of browsing, especially during the transition between control and treatment. However, we perform an exploratory analysis on whether the effect of displaying TIC would vary across profiles with different positions in the browsing sequence but did not find any significant pattern. The evidence might indicate that attention disruption is not playing a major role underlying the process. We thank one reviewer for the suggestion.

The positive correlation is tapering off at the right end (in the area where surprisal> 9 shannons). Since the number of observations is much smaller in this area (as revealed from the wider confidence interval), it does not strongly affect the overall trend. The coefficient of surprisal is positive if we fit a linear relationship on the data.

Interestingly, at an aggregate ‘type’ level, the information across different types of TICs are likely to be substitutes for one another. We can identify such relationship by examining the effect of TIC display when the viewer-profile pairs share two TIC (Figs. 11 and 21). As shown from the 9 panels in Fig. 21, in most scenarios, the effect of displaying two types of things in common is not additive, demonstrating no clear positive complementarity between them is identified. Thus, SN sites could use the information-theoretic framework to guide the optimal display of TIC.

One exception is Phan and Airoldi (2015), in which the authors carefully design a long-term natural experiment of friendship formation and social dynamics in the aftermath of a natural disaster.

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Title: Displaying things in common to encourage friendship formation: A large randomized field experiment
Authors: Tianshu Sun
Sean J. Taylor
Publication date: 23-05-2020
Publisher: Springer US
Published in: Quantitative Marketing and Economics / Issue 3/2020
Print ISSN: 1570-7156
Electronic ISSN: 1573-711X
DOI: https://doi.org/10.1007/s11129-020-09224-9