How do your friends shape the information you see and read online? Social networking technologies like Facebook let us connect to hundreds, even thousands of people -- and have fundamentally changed how people get their information.
While much of our time is spent communicating with close friends about events in our personal lives [1], we also use online networks to share breaking news, discuss political issues and learn about new trends. In 2010, my colleagues Itamar Rosenn, Cameron Marlow, Lada Adamic and I conducted a study on Facebook to understand the nature of information spread in social networks.
Some claim that social networks act like echo chambers in which people only consume and share information from likeminded close friends, stifling the spread of diverse information. Our study paints a different picture of the world.
Instead, we found that even though people are more likely to consume and share information that comes from close contacts that they interact with frequently (like discussing a photo from last night’s party), the vast majority of information comes from contacts that they interact with infrequently. These distant contacts are also more likely to share novel information, demonstrating that social networks can act as a powerful medium for sharing new ideas, highlighting new products and discussing current events.
The research suggests that Facebook isn’t the echo chamber that some might expect – online social networks may actually increase the spread of novel information and diverse viewpoints.
Social Networks as Information Pathways
Economic sociologist Mark Granovetter was one of the first to popularize the use of social networks in understanding the spread of information. In his seminal 1973 paper, The Strength of Weak Ties [2], Granovetter found that surprisingly, people are more likely to acquire jobs that they learned about through individuals they interact with infrequently rather than their close personal contacts.
To explain this phenomenon Granovetter used social graphs to illustrate how networks relate to information access (Figure 1). When a person interacts with two individuals frequently, those individuals are also likely to interact with one another. It follows that people tend to form dense clusters of strong ties who are all connected.
Figure 1: We are connected to core groups of strong ties that we interact with frequently and weak ties that we interact with infrequently. Granovetter's hypothesis about the "strength of weak ties" states that weak ties facilitate information flow from disparate clusters of people.
What do these structures have to do with information access? Since people in these clusters all know each other, any information that is available to one individual spreads quickly to others within the cluster. These tight-knit social circles tend to be small relative to people's entire social network, and when it comes to information about future job opportunities, it can be hard to find new leads.
Granovetter used the relationship between interaction frequency and social structure to explain why information about jobs is instead found through weak ties that we interact with infrequently. Weak ties help spread novel information by bridging the gap between clusters of strong tie contacts. The strength of weak ties informs much of the popular understanding of information spread in social networks.
Birds of a Feather Surf Together
But what about information that is more widely available, like news on the Internet? To understand the flow of more general types of information in society, it’s important not only to take into account how people are connected, but also the commonalities that promote the spread of information. One of the most robust findings in social networks is that of homophily [3], the tendency of individuals with similar characteristics to associate with one another. Individuals are connected to each other through workplaces, professions, schools, clubs, hobbies, political beliefs and other affiliations. The homophily principle holds true for any kind of social network you can think of: close friends, professional contacts, classmates and even the people you ride the bus with.
Today, these commonalities not only shape how often people interact and what they talk about, but also what kinds of information they as individuals seek on the Web. Homophily suggests that people who interact frequently are similar and may consume more of the same information. Individuals that interact less often tend to be dissimilar and may consume more diverse information. This view of the world is illustrated in Figure 2 below.
Figure 2: Information spread in online social networks. Our study suggests that strong ties are similar and more likely to be tuned into the same web sites. Weak ties, being more dissimilar, tend to visit different websites.
Interest and Novelty
To understand how online social networks affect the spread of information, we used random variation in the News Feed to determine how likely a person is to share Web content if she did or did not see the content shared by her friends. We found that people are more likely to share the information they were exposed to by their strong ties than by their weak ties on Facebook (Figure 3).
Figure 3: People are more likely to share information (links to Web pages) that they were exposed to by strong ties in their News Feed [4]. Tie strength between two individuals is measured by the number of comments a person received from their friend on Facebook. Other measurements of tie strength, like the number of messages, co-appearances in photos, and discussion on posts are discussed in our paper [5].
There are many possible explanations for the increased flow of information across strong ties. One reason is that close contacts are more likely to be similar to one another, and therefore find content shared by their close friends more interesting. An alternative explanation is that strong ties are more "influential", so that people are more likely to be persuaded to share information from their close contacts.
We also investigate how Facebook amplifies information distribution. That is, if a friend shares something on Facebook, how many times more likely are you to share that information as a result of seeing it in the News Feed? The figure below shows how this multiplicative effect depends on the strength of your tie with that friend.
Figure 4: Weak ties spread novel information that people are unlikely to otherwise see. The figure above shows how many times more likely people are to share a page because of exposure via the News Feed from strong and weak ties.
We found that information shared by a person's weak ties is unlikely to be shared at a later point in time independently of those friends. Therefore, seeing content from a weak tie leads to a nearly tenfold increase in the likelihood that a person will share a link. In contrast, seeing information shared by a strong tie in News Feed makes people just six times as likely to share. In short, weak ties have the greatest potential to expose their friends to information that they would not have otherwise discovered.
The Collective Influence of Weak Ties
Ultimately, we are interested in how these network effects shape information spread as a whole. Even though a person is more likely to share a single piece of information from one of their close contacts, it turns out that weak ties are collectively responsible for the majority of information spread.
Let's consider a hypothetical example (illustrated in Figure 5). Let's say a person has 100 contacts that are weak tie friends, and 10 that are strong tie friends. Suppose the chance that you'll share something is very high for strong tie friends, say 50%, but the weak tie friends tend to share less interesting stuff, so the likelihood of sharing is only 15%. Therefore the amount of information spread due to weak and strong ties would be 100*0.15 = 15, and 10*0.50 = 5 respectively, so in total, people would end up sharing more from their weak tie friends.
Figure 5: People are more likely to share information from their strong ties, but because of their abundance, weak ties are primarily responsible for the majority of information spread on Facebook. The figure above illustrates how a majority of influence (orange) can be generated by weak ties, even if strong ties are individually more influential.
It turns out that the mathematics of information spread on Facebook is quite similar to our hypothetical example: the majority of people’s contacts are weak tie friends, and if we carry out this same computation using the empirical distribution of tie strengths and their corresponding probabilities, we find that weak ties generate the majority of information spread.
Conclusion
The information we consume and share on Facebook is actually much more diverse in nature than conventional wisdom might suggest. We are exposed to and spread more information from our distant contacts than our close friends. Since these distant contacts tend to be different from us, the bulk of information we consume and share comes from people with different perspectives. This may provide some comfort to those who worry that social networks are simply an echo chamber where people are only exposed to those who share the same opinions. Our work is among the first to rigorously quantify influence at a mass scale, and shows that online social networks can serve as an important medium for sharing new perspectives, products and world events.
Footnotes
[1] Common experience would suggest that we spend most of our time communicating with only a few individuals on Facebook. To a large extent, this is true, and documented in Backstrom, et al. Center of Attention: How Facebook Users allocate Attention. ICWSM, 2011.
[2] M. Granovetter. The Strength of Weak Ties. American Journal of Sociology, 1973.
[3] An extensive and accessible introduction to homophily can be found in McPherson et al. Birds of a Feather Flock Together. Annual Review of Sociology, 2001.
[4] It is important to note that very often, information does not "cascade" very far along the network. This phenomenon has been observed in earlier research on Twitter in Everyone's an Influencer: Quantifying Influence on Twitter and has been studied across other networks more extensively in upcoming work by Sharad Goel and Duncan Watts at Yahoo! Research, NY.
[5] The Role of Social Networks in Information Diffusion. E. Bakshy, I. Rosenn, C.A. Marlow, L.A. Adamic, ACM WWW 2012
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Its a nice article of the thought processes behind these research experiments. It must be fun to have access to all the data on facebook to pose social science questions. Does anyone know the software used to produce the diagrams of the social networks in this article, I would like to produce a similar one. thanks
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