ODSC Speakers 4/72

ODSC Speakers 4/72


AZHAR, HAMDAN

Topic 😕 S,? S, & MAJOR? S: AN INTRODUCTION TO EMOJI DATA SCIENCE

Abstract: Emozy have been called “new type of language.” According to statistics cited by Ad Week, as much as 92% of the online members using emojis. Twitter reports that since 2014 alone, over 110 billion emojis have been tweeted. The proficiency of emojis in the digital life, little research has been done that leverages emojis to understand popular sentiment. We believe that emoji data science, a largely unexplored field, might be a powerful new methodology for both the computational social sciences as well as fast data journalism. We ‘ ll share preliminary research based on an analysis of millions of tweets that explores the relevance of emoji analytics to fields ranging from pop culture (ie the Kanye West vs. Taylor Swift dispute), to politics (the US pres presidential election as well as Brexit) , to gender norms, to the Olympics,and moreWe will also introduce concepts including emoji valence, hashtag-emoji co-occurrence, and sentiment analysis that combine the fields of computational linguistics and natural language processing to provide building blocks for understanding what emojis mean and what your reveal about our culture.

Bio: Hamdan Azhar is a data scientist, journalist, and the founder of PRISMOJI. Hamdan previously worked in ads research at Facebook where he designed experiments to measure the effectiveness of Facebook ads. Prior to that, he served as the national statistician on Ron Paul’s 2012 presidential campaign. Hamdan’s writings on emojis, drone culture, and religion in America have been published in Forbes, VICE, the Christian Science Monitor, and the Washington Post. Hamdan earned his BS in economics from Penn State, his MS in biostatistics from the University of Michigan, and spent one year in the PhD program in neuroscience at the University of Chicago. Earlier this year, Hamdan was named a winner of the 2017 Knight Foundation Prototype Fund Grant which recognizes the most promising early-stage innovations in media and technology.