The Power of Wordplay: Science Meets Language

#sxsw #wordtech

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There is no doubt that words are powerful, but how can the application of big data impact the effectiveness of the way our human language is perceived? There are infinite variations to express one message, and the exact way a particular message is conveyed affects consumer engagement on multiple levels. An exploration of any given message can result in upwards of 16 million variations. In this conversation you will hear Guy Krief, SVP of Product and Innovation at Persado and Michael Collins, Computational Linguistics Expert and Professor at Columbia University discuss insights about how semantic elements of the human language work to facilitate or hinder connecting with people, and how unexpected tweaks backed by math and big data can result in substantial changes in perception and effectiveness.

Presenters

Guy Krief

SVP of Prod & Innovation

Persado

Guy is SVP of Product & Innovation and co-founder of Persado, where he oversees product management, algorithmic research, and software development for Persado.
Guy previously was VP of Innovation for Upstream, where he led the incubation and implementation of the innovative mobile marketing campaigns for global mobile operator and brand clients. Guy has followed a diverse career path, which has seen him write and star in his own TV comedy series and host his own radio show. He was also previously a marketing manager for Wanadoo (France Telecom) in Paris, which became Orange. Guy holds a Masters in Social Psychology from the Sorbonne in Paris.

Michael Collins

Computational Linguistics Expert & Professor of Computer Science, Columbia University

Columbia University

Michael Collins' research interests are in natural language processing as well as machine learning and he has made important contributions in statistical parsing and in statistical machine learning. One notable contribution is a state-of-the-art parser for the Penn Wall Street Journal corpus. His research covers a wide range of topics such as parse re-ranking, tree kernels, semi-supervised learning, machine translation and exponentiated gradient algorithms with a general focus on discriminative models and structured prediction. Collins worked as a researcher at AT&T Labs between January 1999 and November 2002, and later held the positions of assistant and associate professor at M.I.T. Since January 2011, he has been a professor at Columbia University.