We study low sample complexity mechanisms in participatory budgeting (PB), where each voter votes for a preferred allocation of funds to various projects, subject to project costs and total spending constraints. We analyse the distortion that PB mechanisms introduce relative to the minimum-social-cost outcome in expectation. The Random Dictator mechanism for this problem obtains a distortion of 2. In a special case where every voter votes for exactly one project, [Fain et al., 2017] obtain a distortion of 4/3. We show that when PB outcomes are determined as any convex combination of the votes of two voters, the distortion is 2. When three uniformly randomly sampled votes are used, we give a PB mechanism that obtains a distortion of at most 1.66, thus breaking the barrier of 2 with the smallest possible sample complexity. We give a randomized Nash bargaining scheme where two uniformly randomly chosen voters bargain with the disagreement point as the vote of a voter chosen uniformly at random. This mechanism has a distortion of at most 1.66. We provide a lower bound of 1.38 for the distortion of this scheme. Further, we show that PB mechanisms that output a median of the votes of three voters chosen uniformly at random, have a distortion of at most 1.80.

Cinematic Virtual Reality (CVR), or 360° video, engages users in immersive viewing experiences. However, as users watch one part of the 360° view, they will necessarily miss out on events happening in other parts of the sphere. Consequently, fear of missing out (FOMO) is unavoidable. However, users can also experience the joy of missing out (JOMO). In a repeated measures, mixed methods design, we examined the fear and joy of missing out (FOMO and JOMO) and sense of presence in two repeat viewings of a 360° film using a head-mounted display. We found that users experienced both FOMO and JOMO. FOMO was caused by the users’ awareness of parallel events in the spherical view, but users also experienced JOMO. FOMO did not compromise viewers’ sense of presence, and FOMO also decreased in the second viewing session, while JOMO remained constant. The findings suggest that FOMO and JOMO can be two integral qualities in an immersive video viewing experience and that FOMO may not be as negative a factor as previously thought.

Elections and opinion polls often have many candidates, with the aim to either rank the candidates or identify a small set of winners according to voters’ preferences. In practice, voters do not provide a full ranking; instead, each voter provides their favorite K candidates, potentially in ranked order. The election organizer must choose K and an aggregation rule. We provide a theoretical framework to make these choices. Each K-Approval or K-partial ranking mechanism (with a corresponding positional scoring rule) induces a learning rate for the speed at which the election recovers the asymptotic outcome. Given the voter choice distribution, the election planner can thus identify the rate optimal mechanism. Earlier work in this area provides coarse order-of-magnitude guaranties which are not sufficient to make such choices. Our framework further resolves questions of when randomizing between multiple mechanisms may improve learning for arbitrary voter noise models. Finally, we use data from 5 large participatory budgeting elections that we organized across several US cities, along with other ranking data, to demonstrate the utility of our methods. In particular, we find that historically such elections have set K too low and that picking the right mechanism can be the difference between identifying the ultimate winner with only a 80% probability or a 99.9% probability after 400 voters.

This paper examines the effects of participants' preferred point of view of two protagonists, and their motivation for this preference, on two viewings of a cinematic 360-degree video filmed from the first person perspective. Before watching the film, which dramatized gender bias in a STEM workplace, participants were asked to state whether they preferred to view the film from the point of view (POV) of a male protagonist, a female protagonist, or make no selection. They were then asked why they held this preference. Their answers were predictive. Participants' tracked head movements, and the events participants recalled from the film, differed according to their pre-stated preference and motivation.

This paper examines the sense of presence, attitude change, perspective-taking, and usability of a split-sphere, first-person perspective 360 degree video about gender inequality, in which people can choose to watch the narrative from the male or female character's perspective. Sixty-seven participants were randomly assigned to watch (1) the video in 360 degree split-view in a head-mounted display, (2) the same film as 180 degree in a HMD, or (3) a flat control version of the video on a laptop. The 360 degree split-sphere increased the viewers' feeling of personal responsibility for resolving gender inequality, desire to rewatch the video, fear of missing out, and feeling of missing the full story. The 180 degree video created the strongest sense of presence, embodiment, and understanding of the character. However, people with greater egocentric projection onto the male character felt less responsible for resolving gender inequality, particularly in the 360 degree split-view.