The talk will focus on few counter-intuitive results from studies on several different topics, (using different methodologies):
- Optimal seeding policies in user-generated content networks (UGC) such as YouTube, Facebook and SoundCloud advocate for using high status (e.g., high degree) individuals. However, perhaps surprisingly, under quite common conditions, low status (low degree) individuals facilitate larger reach and more effective dissemination. Previous models ignore the response probability of the individual (seed) at hand. Because response probability is a function of status differences (as will be shown), a seeding policy that prioritizes high status individuals is suboptimal, and perhaps should be revised.
- We introduce evidence that name stereotypes can be manifested in facial appearance, producing a face-name matching effect, whereby both a social perceiver and a computer (through a machine learning based classifier) are able to accurately match a person’s name to his or her face. In nine studies (not all of which will be presented), we demonstrate this effect, showing that participants examining an unfamiliar face accurately select the person’s true name from a list of several names, significantly above chance level. We replicate the effect in two countries and find that it extends beyond the limits of socioeconomic cues, and even among fraternal twins. We also find the effect using a computer-based paradigm and 94,000 faces. A self-fulfilling prophecy seems to be at work, as initial evidence shows that facial regions controlled by the individual (e.g., hairstyle) are sufficient to produce the effect, and socially using one’s given name is necessary to generate the effect. Together, these studies suggest that facial appearance represents social expectations of how a person with a specific name should look.
- Finally, if time permits, I will present evidence of how the velocity of the platform we use (e.g., train, bus) influences related decisions such as risk taking, type of search for information, and focus.
Jacob Goldenberg is a Professor of Marketing at the Arison School of Business Administration at the Inter-Disciplinary Center at Hertzelia and a visiting professor at the Columbia Business School. His research focuses on creativity, new product development, diffusion of innovation, complexity in market dynamics social networks effects, and social media. He is an Academic Trustee of the Marketing Science Institute.
Jacob was the editor-in-chief of the International Journal of Research in Marketing and now is an area editor for Journal of Marketing Research, and serves on the editorial board of Marketing Science. He has published papers in the Journal of Marketing, Journal of Marketing Research, JPSP, Management Science, Marketing Science, Nature Physics and Science. In addition, he is an author of two books by Cambridge University Press one in Chicago Press, and one book by Simon&Schuster.
Jacob’s scientific work has been covered in the New York Times, Wall Street Journal, Boston Globe, BBC News, Herald Tribune, The Economist and Wired magazine.
He received his Ph.D. from the Hebrew University of Jerusalem in a joint program of the School of Business Administration and Racach Institute of Physics.