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Signal Patterns Forms Scientific Advisory Board with Leading Scientists and Researchers from Top Universities
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Signal Patterns Forms Scientific Advisory Board with Leading Scientists and Researchers from Top Universities

Newly formed group represents the world's largest team of psychologists to work on social web applications

PLEASANTVILLE, N.Y., July 31 /PRNewswire/ -- Signal Patterns, developers of scientific-based social web applications that characterize and connect people in meaningful ways, today announced its Scientific Advisory Board. Composed of leading academic experts in personality psychology and psychometrics, the team will help support the company's research initiatives and personality assessment technology.

Signal Patterns' Scientific Advisory Board is the world's largest team of psychologists assembled to collaborate and work on social web applications. The Scientific Advisory Board is headed by Lewis R. Goldberg, Ph.D., a prominent psychologist who is Professor Emeritus with the University of Oregon and a senior scientist with the Oregon Research Institute.

Goldberg is also part of Signal Patterns' Science Team, which includes Daniel J. Levitin, Ph.D, who directs the McGill Laboratory for the Study of Music Cognition, Perception and Expertise; Jason Rentfrow, Ph.D, Psychology, an expert in personality and social psychology and lecturer at the Faculty of Social and Political Sciences at Cambridge University in England; and David H. Rosen, Ph.D, Psychology, a behavioral and personality psychology expert and consultant.

The Science Team works closely with the Signal Patterns product development team in developing new surveys and models, and conducting experiments. In addition, the Science Team works with the Scientific Advisory Board on research projects in specific subject areas.

The Scientific Advisory Board includes 19 behavioral experts specializing in different domains such as leadership, work psychology, media and genre preferences, and social attitudes from leading academic institutions such as Northwestern University, University of Texas at Austin, University of Oregon, Universitat Hamburg, and University of Southern California.

"This esteemed group of research psychologists represents the leaders in personality and psychology," said Ran Zilca, CEO and co-founder of Signal Patterns. "Working alongside our Science Team, the Scientific Advisory Board will help us break new ground in personality and psychological assessment, and provide valuable insight into the connections between personality, behavior and preferences."

Signal Patterns develops research surveys aimed to help people identify and recognize their own unique patterns of personality and preferences in a wide range of subject areas, from career choices to leisure activities, music preferences, friends, and more. Through Signal Patterns' surveys, people are able to learn more about their selves - and ultimately use that knowledge to seek out people with whom they can better relate, as well as identify a career change and new pastimes they would enjoy.

The company recently launched a Personality Patterns Facebook application that offers an in-depth 45-score personality assessment algorithm based on the trait-based "Big Five" theory. This innovative survey assesses and connects people based on unique personality traits rather than the rough "buckets" of personality types found in more traditional type-based personality assessment methods like the Myers-Briggs Type Indicator(R) (MBTI). An extended and more detailed personality assessment, as well as a music preferences survey and other features, are available at SignalPatterns.com.

    Scientific Advisory Board members:
    -- Paul Barrett, Chief Research Scientist, Hogan Assessment Systems
    -- Tom Buchanan, Reader in Psychology, University of Westminster, UK
    -- Matthias Burisch, Fachbereich Psychologie, Universitat Hamburg
    -- David Buss, Professor of Psychology, University of Texas at Austin
    -- William Chaplin, Professor of Psychology, St John's University
    -- Colin DeYoung, Assistant Professor of Psychology, University of
       Minnesota, Twin Cities
    -- Sam Gosling, Associate Professor of Psychology, University of Texas at
       Austin
    -- Willem Hofstee, Emeritus Professor of Psychology, University of
       Groningen, Netherlands
    -- John McArdle, Senior Professor of Psychology, University of Southern
       California
    -- Robert McGrath, Professor of Psychology, Fairleigh Dickinson University
    -- Daniel Nettle, Reader in Psychology, Newcastle University
    -- James Pennebaker, Professor and Chair of the Department of Psychology,
       The University of Texas at Austin
    -- William Revelle, Professor of Psychology, Northwestern University
    -- Brent Roberts, Professor of Psychology, University of Illinois,
       Urbana-Champaign
    -- Jim Russell, Professor and Chair of the Department of Psychology,
       Boston College
    -- Gerard Saucier, Associate Professor of Psychology, University of Oregon
    -- Leonard Simms, Assistant Professor of Psychology, University at
       Buffalo, State University of New York
    -- Sanjay Srivastava, Assistant Professor of Psychology, University of
       Oregon
    -- Michelle Yik, Associate Professor, Division of Social Science, The Hong
       Kong University of Science and Technology


    Additional resources: http://www.signalpatterns.com/corporate_press.html

About Signal Patterns

Signal Patterns develops social web applications that characterize and connect users to each other based on their interests, personality and preferences. With these scientific-based applications, consumers can discover more about themselves and make valuable connections to like-minded individuals, while publishers, advertisers and social networks can increase their own user engagement. Signal Patterns' patent-pending technology results from a unique combination of in-house behavioral science research and data mining expertise. Pleasantville, NY-based Signal Patterns was founded in 2006. http://www.signalpatterns.com

SOURCE Signal Patterns

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