Our Research at IEEE VR

Very happy to announce my joint work with Ketaki Shriram was accepted to be presented at IEEE VR 2017.  Here is the title and abstract:

All Are Welcome: Using VR Ethnography to Explore Harassment Prevention in Immersive Social Virtual Reality

The growing ubiquity of VR headsets has given rise to questions around harassment in social virtual reality. This paper presents two studies. In the first, a pilot ethnographic study, users were interviewed in immersive social virtual reality about their experiences and behaviors in these spaces. Harassment was occasional, and those in female avatars reported more harassment than those in male avatars. In Study Two, a quantitative survey was conducted to validate ethnographic results. A large percentage of users witness harassment in virtual reality. These studies provide mixed methods insight of user demographics and behaviors in the relatively new social VR space.

Shriram K., Schwartz, R. (2017) All Are Welcome: Using VR Ethnography to Explore Harassment Prevention in Immersive Social Virtual Reality. IEEE VR. Los Angeles, USA, March 2017.

Joining Oculus!


I am excited to announce I joined the Oculus Experience Research in London as a Research Lead. My research will support the development of the next computing platform and more specifically social interactions in immersive VR. If you have followed the latest developers conference you might have seen two of the projects I have had a chance to support: Oculus Rooms and Oculus Avatars. Both of these projects will be available soon and I can’t wait to see how people are going to use them!


CityBeat at ICWSM 2015

Our paper “Editorial Algorithms: Using Social Media to Discover and Report Local News” was accepted as a full paper presentation at ICWSM 2015 in Oxford, UK.  Here is the abstract:

The role of algorithms in the detection, curation and broadcast of news is becoming increasingly prevalent. To better understand this role we developed CityBeat, a system that implements what we call “editorial algorithms” to find possible news events. This fully functional system collects real-time geo-tagged information from social media, finds key stories, makes an editorial decision whether these events are of interest and eventually visualizes these stories on a big screen display. The system was designed in collaboration with jour- nalists and tested at four New York City newsrooms. Our results show that while journalists were receptive to the idea of machine-generated news stories, the actual results of the system confirmed current concerns among journalists and researchers about the dangers of outsourcing news-finding tasks to machines. This paper, therefore, exemplifies how news sourcing systems based on social media may favor specific types of news events, do not report results quickly enough, and cater to a biased population and range of interests.

I am joining Facebook Research!

Starting October 2014 I will be joining the research team at Facebook.

The Spatial Self: New Article on New Media and Society

A new article by the awesome Germaine Halegoua and me was just published on New Media & Society. Here is the abstract:

As a growing number of social media platforms now include location information from their users, researchers are confronted with new online representations of individuals, social networks, and the places they inhabit. To better understand these representations and their implications, we introduce the concept of the “spatial self”: a theoretical framework encapsulating the process of online self-presentation based on the display of offline physical activities. Building on previous studies in social science, humanities, and computer and information science, we analyze the ways offline experiences are harnessed and performed online. We first provide an encompassing interdisciplinary survey of research that investigates the relationships between location, information technology, and identity performance. Then, we identify and characterize the spatial self as well as examine its occurrences through three case studies of popular social media sites: Instagram, Facebook, and Foursquare. Finally, we offer possible research directions and methodological considerations for the analysis of geocoded social media data.