Category: Academia (page 1 of 3)

Joining Spotify 👩‍🎤

I am super excited to share I have accepted a new role at Spotify leading a group of insights researchers (data science and user research) to explore the future of Spotify Premium! I had an amazing ride at Facebook over the last six years and I am looking forward to my new adventure at Spotify!

Harassment in Social VR: Implications for Design

Happy to share this work that was just published as part of IEEEVR 2019. Here is the abstract:

We interviewed VR users (n=25) about their experiences with harassment, abuse, and discomfort in social VR. We find that users’ definitions of ‘online harassment’ are subjective and highly personal, making it difficult to govern social spaces at the platform or application level. We also find that embodiment and presence make harassment feel more intense. Finally, we find that shared norms for appropriate behavior in social VR are still emergent, and that users distinguish between newcomers who unknowingly violate expectations for appropriateness and those users who aim to cause intentional harm.

The Immersive VR Self

Very happy to share this paper written together with Will Steptoe. This paper will appear in “A Networked Self and Human Augmentics, AI, Sentience” but is already available here:


Virtual avatars are a common way to present oneself in online social interactions. From cartoonish emoticons to hyper-realistic humanoids, these online representations help us portray a certain image to our respective audiences. Immersive VR systems like the Oculus Rift and HTC Vive track a user’s physical body movement in real-time and utilize this data to drive the corresponding behavior of an avatar. What is then special about avatars in immersive environments and how does this difference play out in the relationship between a user’s physical and virtual sense of presence? In this paper, we summarize academic research in this field, study the conditions that construct self presentation in immersive VR, coin the term “immersive VR self” and detail its unique characteristics.

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.

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.