Difference between revisions of "Reality Mining"

Revision as of 17:33, 15 October 2010

Definition

Reality Mining is the collection and analysis of machine-sensed environmental data pertaining to human social behavior, with the goal of identifying predictable patterns of behavior. It was declared to be one of the "10 technologies most likely to change the way we live" by Technology Review Magazine, and since has become a popular phrase used by high-tech conferences (e.g., O'Reilly), technology-oriented bloggers (e.g., Wired and Wikinomics), and main-stream media (e.g., Businessweek).

Reality Mining studies human interactions based on the usage of wireless devices such as mobile phones and GPS systems providing a more accurate picture of what people do, where they go, and with whom they communicate with rather than from more subjective sources such as a people's own account. Reality mining is one aspect of digital footprint analysis (BusinessWeek, 2008).

We have invented the technology of reality mining, which analyzes sensor data to extract subtle patterns that predict future human behavior. These predictive patterns begin with biological "honest signals," human behaviors that evolved from ancient primate signaling mechanisms, and which are major factors in human decision making in situations ranging from job interviews to first dates.   By using data from mobile phones, electronic ID badges, or digital media to track these honest signals, we can create a `gods eye' view of how the people in organizations interact, and even `see' the rhythms of interaction for everyone in a city.

Relations to Business Intelligence

Informed business intelligence using "reality mining" supports better business decision-making based on employee behaviors. Gathering intelligence to help improve the business efficiency by monitoring, analyzing and fine tuning the employee's footprint based on what is efficient and what will yield more productive employees. It is important to observe people in the workplace and understand how they interact with their equipment, devices and applications. This observation allows us the means to obtain an “electronic footprint” or eFootPrint of these activities. We focus on what the employee does in their job, where they spend their time, how efficient are they performing it and how it can be improved.

Management insights based on Honest Signals were named a `Breakthrough Idea of 2009' by Harvard Business Review, and Reality Mining was declared `a technology poised to change the world' by Technology Review.  This new view of human nature, organizations, and society is the subject of Sandy Pentland's book `Honest Signals,' published by MIT Press".

Source: [1]

Machine Perception and Learning of Complex Social Systems

Reality Mining defines the collection of machine-sensed environmental data pertaining to human social behavior. This new paradigm of data mining makes possible the modeling of conversation context, proximity sensing, and temporospatial location throughout large communities of individuals. Mobile phones (and similarly innocuous devices) are used for data collection, opening social network analysis to new methods of empirical stochastic modeling.

The original Reality Mining experiment is one of the largest mobile phone projects attempted in academia. Our research agenda takes advantage of the increasingly widespread use of mobile phones to provide insight into the dynamics of both individual and group behavior. By leveraging recent advances in machine learning we are building generative models that can be used to predict what a single user will do next, as well as model behavior of large organizations. We have captured communication, proximity, location, and activity information from 100 subjects at MIT over the course of the 2004-2005 academic year. This data represents over 350,000 hours (~40 years) of continuous data on human behavior.

Such rich data on complex social systems have implications for a variety of fields. The research questions we are addressing include:

• How do social networks evolve over time?
• How entropic (predictable) are most people's lives?
• How does information flow?
• Can the topology of a social network be inferred from only proximity data?
• How can we change a group's interactions to promote better functioning?

Participation

If you have a Nokia Symbian Series 60 Phone (such as the Nokia 6600) with a data plan, you can participate. Additionally, we have cleaned the 2004-2005 data of identifiable information and are making it available to other researchers within the academic community. Both the mobile phone application and the resultant dataset can be downloaded here. This project was generously supported by our partners and collaborators at Nokia.

Source: [2]

Biography


Professor Alex (“Sandy”) Pentland is a pioneer in organizational engineering, mobile information systems, and computational social science. Sandy's focus is the development of human-centered technology, and the creation of ventures that take this technology into the real world. 

He directs the Human Dynamics Lab, helping companies to become more productive and creative through organizational engineering, and the Media Lab Entrepreneurship Program, which helps translate cutting-edge technology into real-world impact around the world.  He is among the most-cited computer scientists in the world, and in 1997 Newsweek magazine named him one of the 100 Americans likely to shape this century. 

Source: [3]