- Computational Social Science
- Critical Data Studies
- Data Science
- Economics and Information
- Education Technology
- Ethics, Law and Policy
- Human-Computer Interaction
- Human-Robot Interaction
- Incentives and Computation
- Infrastructure Studies
- Interface Design and Ubiquitous Computing
- Natural Language Processing
- Network Science
- Social Computing and Computer-supported Cooperative Work
- Technology and Equity
Title: Language and Social Dynamics
Abstract: More and more of life is now manifested online, and many of the digital traces that are left by human activity are in natural-language format. In this talk I will show how exploiting these resources under a computational framework can bring a new understanding of online social dynamics; I will be discussing three of my efforts in this direction.
The first project explores the relation between users and their community, as revealed by patterns of linguistic change. I will show that users follow a determined life-cycle with respect to their susceptibility to adopt new community norms, and how this insight can be harnessed to predict how long a user will stay active in the community.
The second project aims at providing a better understanding of the mechanism behind the evolution of language. In particular, I will consider two opposing forces regulating language change --- the need for innovation on one side, and the need for consistency between generations on the other --- and show how these two needs are balanced by the adoption cycle of individuals.
I will conclude by discussing computational approaches to complex linguistic norms --- such as politeness and ideological bias --- and considering the impact of this research direction on our understanding of social dynamics and on the design of social-media systems.
Bio: Cristian Danescu-Niculescu-Mizil is a faculty member of the Max Planck Institute SWS. His research aims at developing computational frameworks that can lead to a better understanding of human social behavior, by unlocking the unprecedented potential of the large amounts of natural language data generated online. His work tackles problems related to conversational behavior, opinion mining, computational pragmatics and computational advertising. He is the recipient of several awards, including the WWW 2013 Best Paper Award and a Yahoo! Key Scientific Challenges award, and his work has been featured in popular-media outlets such as the New Scientist, NBC's The Today Show, NPR and the New York Times.