Influential people, from journalists and entrepreneurs to investors and developers are idea-generators shaping the ideas we drool over and discuss et infinitum. But who are these people leading the charge? How did they come to be, and rise above the rest to gather a following? Sites like Twitter and Facebook are now testing grounds for quantifying the world’s leaders. But do we understand what influence means and what variables are really at play? We all know that a follower count means nothing, but what does a RT mean? Or better yet, what does an @reply by Scoble mean vs. one from Arrington? Beneath the surface is where the science gets really interesting. In this panel you’ll hear from the experts who are distilling influence down to it’s basic components. They’ll explain tips for increasing influence, which variables really matter and the types of influence they are discovering across the web.
Dan Zarrella is an award-winning social, search, and viral marketing scientist at HubSpot and author of two O’Reilly Media books: “The Social Media Marketing Book” and The Facebook Marketing Book."
Michael Wu is the Principal Scientist of Analytics at Lithium Technologies Inc. Michael received his Ph.D. from UC Berkeley’s Biophysics graduate program. His graduate research focuses on modeling the human brain, specifically the visual cortex, with techniques from math, physics, statistics, and machine learning. Currently, Michael is applying similar data-driven methodologies to investigate and understand the complex dynamics within online communities as well as the greater social web.
Michael has developed the Community Health Index (CHI) and many predictive social analytic algorithms that bring Lithium closer to its vision of “one portal to manage the entire social web.” To tackle challenging problems like the value of WOM and social media ROI, Michael collaborates with academicians to conduct research on these important topics of social media that are presently unsolved. Michael’s R&D work at Lithium has won him the recognition as a 2010 Influential Leader by CRM Magazine.
Michael has been a DOE fellow during his graduate career and was awarded 4 years of full fellowship plus stipend under the Computational Science Graduate Fellowship. During his fellowship tenure, he has also served at the Los Alamos National Lab, conducting cutting edge research in machine learning and face recognition. Prior to his graduate research, Michael received his undergraduate degree from UC Berkeley triple majoring in Applied Math, Physics, and Molecular & Cell Biology.
Ramya Krishnamurthy is Director of Research Engineering at Klout. At Klout, Ms. Krishnamurthy brings to bear her extensive background of Machine Learning, Natural Language Processing, and Statistical Analysis to detect complex patterns in human interactions and quantify them in a measurable manner. Ramya's team is consistently working to build an intelligent and scalable solution for assessing influence.
Prior to joining Klout, Ms. Krishnamurthy was one of the lead researchers at Fox Audience Network where she helped the company build multiple online targeting products by applying various data mining techniques.
Ms. Krishnamurthy has been a member of the research team at the Mathematics and Computer Science division of Oak Ridge National Laboratory. She is originally from India and currently lives in San Francisco, CA.
When Ramya is not cooking up solutions to complex problems, she enjoys experimenting with different ingredients and cuisines in the kitchen.
