Our lab is awarded Twitter Data Grant



(Twitter Data Grant team members in front of a visualization from their previous project selfiecity.net.)



We are among 6 international teams awarded Twitter Data Grants:

Twitter #DataGrants selections



Project proposal title:

Do happy people take happy images? Measuring happiness of cities from tweeted Images


Abstract:

Can visual characteristics of images shared on social media tell us about the “moods” of cities? We propose to study the relationship between features of tweeted images in a number of U.S. cities and existing measures of "happiness" estimated using traditional surveys and other data sources (such as health and well-being statistics).


For further about this project, see the following:

Calit2 news release, The Happiness of Cities: Do Happy People Take Happy Images?

San Diego Union-Tribune, Do happy people take happy photos?



A Window, a Message, or a Medium? Learning from Instagram





My upcoming talk at International Conference on Mobile and Social Media Practices (organized by Dr. Tristan Thielmann).

June 19-21, 2014
The University of Siegen
Germany


Title:

A Window, a Message, or a Medium? Learning from Instagram


Abstract:

Over last few years, tens of thousands of researchers in social computing and computational social sciences started to use available data from social networks and media sharing services (such as Twitter, Foursquare and Instagram) created by users of mobile platforms. The research uses techniques from statistics, machine learning, and visualization, among others, to analyze all kinds of patterns contained in this data and also (less frequently) propose new models for understanding the social. The examples include analysis of information propagation in Twitter, predicting popularity of photos on Flickr, proposing new sets of city neighborhoods using Foursquare users check-ins, and understanding connections between musical genres using listening data from Echonest.

In my talk I will address a fundamental question we face in doing this research: what exactly are we learning when analyzing massive social media data? Is it a window into real-world social and cultural behaviors, a reflection of lifestyles of particular demographics who use mobile platforms and particular network services, or only an artifact of mobile apps? In other words - is social media a "message" or a "medium"?

I will discuss this question using three recent projects from my lab (softwarestudies.com). The projects use large sets of Instagram images and accompanying data together with data science and visualization tools. Phototrails.net (2013) analyzes 2.3 million photos from 13 global cities to investigate how different kinds of events are represented in these photos. The project also investigates if the universal affordances of Instagram app (same interface and same set of filters available to all users) result in universal digital visual language. Selfiecity.net (2014) analyzes the distinct artifact of mobile platforms – selfies. We compare thousands of selfies to see if cultural specificity of different places and cultural is preserved in this genre. Finally, our third project compares Instagram photos taken by visitors in a few major modern art museums, asking if photographs of famous works of the art differ depending on what these artworks are and where they are situated.

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