Dina is a data scientist at OmiLab (Open Media and Information Lab) and a Ph.D. candidate at the University of Haifa. Her Master thesis deals with classifying and characterizing persuasion. She is a former teaching assistant for ML and an experienced international public speaker. She is a data science content writer for workshops, meetups, and online courses, as well as an official author of the Towards Data Science publication. Dina is passionate about data, sharing knowledge, and contributing to society and open source. Whenever she can't find a sufficient tutorial, she creates one.
Data Scientist | Researcher
Can also give an online talk/webinar
Paid only. Contact speaker for pricing!
The Art of Quantifying Intentions
Data / AI / ML, Community / Networking, Marketing
In the era of online communication, where most human interactions are online, we must have a proper understanding of social science theories in order to understand those interactions using data science methods. In other words, labeling human values is hard. In this talk, Dina will present What is the science of converting social theories into data science? How can we quantify human behavior? And how to validate your theoretical hypotheses in real data? What does social media influence look like? Why fake-news persuades people? In this lecture, Dina will address those difficulties and how to handle them, which will provide us with a better understanding of the social science behind online social influence analysis.