Part of what makes the combination of globalization and social networking so amazing is that it has the ability to connect previously unconnected groups of people. What was already socially organic in the real world, ie. a person meets someone and becomes involved with the groups and communities the person belongs to, and vice versa, became global and instantaneous thanks to the web. And just as in the real world, individuals that do the connecting, called “bridges” or “social connectors” will prove to be a vital in studying behavioral change between online communities.
Previously, researchers focused on identifying central individuals, (ie. influencers or leaders), in the group to accelerate behavior change or stem disease spread. We utilize this principal all the time — for instance, we trust the reviews of our favorite movie critic; we reward the coworker who always boosts team morale; we identify the coworker who helps to spread or prevent disease (the guy who NEVER washes his hands/the OCD hand sanitizer freak). But this only works locally, within groups or communities. For non-movie buffs, the critic’s review doesn’t mean much nor does the morale boost or potential sickness to someone outside of the company. Influence is only important to those who are in the know — and central individuals struggle to affect behavior because their influence means that they must share their attention and persuasion with numbers of people, reducing effectiveness.
A new study by Thomas Valente and Kayo Fujimoto, which appears in the April issue of the journal, Social Networks, suggests that when compared to central individuals, identifying bridging individuals who connect two otherwise disconnected groups is a much more efficient way to affect behavior change or stem disease spread. Furthermore, the study presents a new model for identifying bridging individuals.
According to Valente in a recent article from U. of Southern California, researchers systematically deleted each link in a person’s network and calculated the resultant network cohesion, enabling them to identify an individual’s bridging effect. Using their model, researchers were able to correctly identify the bridge individual in two separate studies: the spread of HIV among the first 40 cases diagnosed in the U.S. and drug use behavior among Irish teenagers in certain social networks. Thinking about the introduction of the myriad of diseases introduced to Native Americans by European bridge individuals (and other more recent examples), it’s clear that this model will be important to public health officials who wish to prevent the spread of disease.
But what does the bridge individual mean to online communities?
Online communities work in a similar fashion to their real world counterparts: viruses and information spread through networks utilizing bridging individuals to reach previously unconnected groups. It’s important to many people to be thought of as a thought leader within their network in order to influence behavior (get someone to read their blog, buy their product, etc.) but this study shows that at a macro level, it’s more important to be a connector, linking groups that might not otherwise organically come together to influence the same behavior. In the case of web marketing/public relations, this model makes it possible to identify individuals and businesses who belong to several groups and who influence those groups naturally — as opposed to individuals and businesses who have influence only within a limited group.