Unifying Social Networking and Communications

Integrating communications functionality into social networking tools provides a real opportunity to significantly increase the value of the social graphs maintained by those tools. Let’s look at LinkedIn, for example. While LinkedIn may expose my connections and my social network, it doesn’t distinguish between casual acquaintances and close business partners. It doesn’t show whether someone has been a close friend for 20 years or if I just met the person at a trade show last week. For others who are trying to leverage my social graph, that type of information might be critical when deciding how to best approach me or who to consult for an introduction.

However, if LinkedIn were aware of my communication patterns (e.g. because communications were initiated from within LinkedIn), it could correlate these communications patterns with my network connections, and identify which ones of these connections are “high-value” connections (because I communicate with those connections extensively), and which connections are superficial and casual.

Taking this one step further, there is huge potential for social networking tools to mine communications patterns more aggressively, even communications that are not initiated from within those tools. Ultimately, this could allow social tools to construct people’s social networks automatically: by tracking the real interactions that go on every day in an organization, it becomes possible to extract common interaction patterns that can point out who the real information gatekeepers are in an organization, who the go-to people are, and who are the movers and shakers. This eliminates the need for social networking users to build up their network manually and might result in information that is more accurate and more valuable.