DATA POLITICS – University of Copenhagen

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DATA POLITICS

Blå fave i vand - photo: colourbox
The Centre for Social Data Science is pleased to announce its Fall Lecture Series 2018. Focusing on the theme of “Data Politics”, SODAS has invited speakers to reflect on the role of politics in the age of (big) data. Speaking on themes such as political elections, fake news, data privacy and the globalization of data, the lectures will present cutting edge research on the political challenges the digital revolution presents us with, and the methodological innovations needed to study them.


Average is Boring: How Similarity Kills a Meme's Success (and what does it mean for our democracy?)

Our next speaker on Friday the 26th of October is Michele Coscia, who is Assistant Professor at the Department of Computer Science, IT University of Copenhagen.

Abstract

We define a meme as the fundamental building block of culture, just like a gene is the fundamental building block of biology. A meme can be a catchphrase, a tune, an architectural feature. We study Internet memes because it is easy to collect them and to gauge their popularity. Computer scientists have proposed many theories about why memes go viral: timely attention, social prominence of first spreaders, and mankind's collective limited attention. My favorite explanation focuses on content: the memes that go viral are the ones that have something unique about them. I provide a way to measure meme-meme similarity and show that, indeed, the memes with low average similarity are the most successful ones. This has repercussions when it comes to political discourse online: extreme trumps moderate because extreme is more surprising. Moreover, fake news stories have an inherent advantage over real ones, because they are unconstrained by reality and thus can be crafted with virality - rather than veracity - in mind.

Lectures will take place in Building 35, Floor 3, Room 20 (35.3.20) of the CSS Campus, Copenhagen University, from 11.00am - 12.30pm.

If you have questions or want to know more, please write Agnete Vienberg Hansen at avh@econ.ku.dk.