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1. Distributed Knowledge in Crowds: Crowd Performance on Hidden Profile Tasks

   Tausczik, Yla; Boons, Mark (June 2018, Proceedings of the International AAAI Conference on Weblogs and Social Media)

   Individuals today discuss information and form judgements as crowds in online communities and platforms. “Wisdom of the crowd” arguments suggest that, in theory, crowds have the capacity to bring together diverse expertise, pooling distributed knowledge and thereby solving challenging and complex problems. This paper concerns one way that crowds might fall short of this ideal. A large body of research in the social psychology of small groups concerns the shared information bias, a tendency for group members to focus on common knowledge at the expense of rarer information which only one or a few individuals might possess. We investigated whether this well-known bias for small groups also impacts larger crowds of 30 participants working on Amazon’s Mechanical Turk. We found that crowds failed to adequately pool distributed facts; that they were partially biased in how they shared facts; and that individual perception of group decisions was unstable. Nonetheless, we found that aggregating individual reports from the crowd resulted in moderate performance in solving the assigned task. 

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2. Residents’ Perceptions of Behavioral Reference Groups for Personalized Normative Messaging Interventions

   Song, K. (November 2020, Construction Research Congress)

   Reporting normative feedback to residential energy consumers has been found effective at reducing residential energy consumption. Upon receiving normative feedback households tend to modify their use to become in line with group norms. The effect of normative messages is partially moderated by how personally relevant normative reference groups are to the individual. Advanced energy metering technologies capture households’ energy use patterns, making it possible to generate highly similar and relevant normative reference groups in a non-invasive manner. Unfortunately, it is not well understood how similar individuals are to other group members. It also remains unknown how much individuals identify with behavioral reference groups. Therefore, this research aims to investigate how households perceive behavioral reference groups used in normative comparisons. Survey questionnaires are collected from 2,008 participants using Amazon Mechanical Turk. It is found that while households’ behaviors are more similar when grouped based on energy use profiles than based on geographic proximity, they identify more closely with proximity-based groups. Also, members’ group identification increases as individuals have higher similarity in energy use behaviors with other group members. This implies that enhancing the identity of profile-based behavioral reference groups will lead to an increase in norm adherence, and in turn reductions in household energy use. 

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3. Socially driven negative feedback regulates activity and energy use in ant colonies

   https://doi.org/10.1371/journal.pcbi.1012623  

   Porfiri, Maurizio; Abaid, Nicole; Garnier, Simon (November 2024, PLOS Computational Biology)

   Marshall, James AR (Ed.)

   Despite almost a century of research on energetics in biological systems, we still cannot explain energy regulation in social groups, like ant colonies. How do individuals regulate their collective activity without a centralized control system? What is the role of social interactions in distributing the workload amongst group members? And how does the group save energy by avoiding being constantly active? We offer new insight into these questions by studying an intuitive compartmental model, calibrated with and compared to data on ant colonies. The model describes a previously unexplored balance between positive and negative social feedback driven by individual activity: when activity levels are low, the presence of active individuals stimulates inactive individuals to start working; when activity levels are high, however, active individuals inhibit each other, effectively capping the proportion of active individuals at any one time. Through the analysis of the system’s stability, we demonstrate that this balance results in energetic spending at the group level growing proportionally slower than the group size. Our finding is reminiscent of Kleiber’s law of metabolic scaling in unitary organisms and highlights the critical role of social interactions in driving the collective energetic efficiency of group-living organisms. 

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4. Feature creep or just plain creepy? How advances in “smart” technologies affect attitudes toward data privacy

   Vitak, J. (January 2020, Annals of the International Communication Association)

   Smart home technologies on our phones and in our homes are collecting more (quantity) and more (types of) data about us. These tools are intended to simplify everyday tasks, but to do so effectively, they collect significant data about users and their environment. One popular example includes intelligent personal assistants (IPAs) like Apple’s Siri, Amazon’s Alexa, and Google’s Assistant. As these services have transitioned from being embedded in consumers’ smartphones to standalone devices in the home, they have evolved to collect and share more data in more potentially invasive ways. In this paper, we consider American adults’ attitudes toward IPAs. Through an analysis of focus groups with IPA users and non-users, we describe attitudes and concerns toward IPAs broadly, as well as how these attitudes vary based on the devices’ features. We suggest new frameworks for evaluating privacy-based decisions and offer policy suggestions for regulating data flows from smart technologies. 

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5. Developing an Observation Protocol for Cooperative Learning

   Fong, M.; Chen, H.; Butler, L.; Herman, G. (July 2022, American Society for Engineering Education Annual Conference & Exposition)

   Use of structured roles to facilitate cooperative learning is an evidence-based practice that has been shown to improve student performance, attitude, and persistence. The combination of structured roles and activities also helps build students’ process skills including communication and metacognition. While these benefits have been shown in a variety of disciplines, most prior work has focused on in-person, synchronous settings, and few studies have looked at online, synchronous settings. With the ongoing COVID-19 pandemic, we need a better understanding of how cooperative learning takes place online and what differences may exist between online and in-person modalities. This work-in-progress serves to document our development of an observation protocol to help us answer research questions such as the following: Do group members participate equally? Do group members’ contributions match their role? How do groups connect and bond with each other? How do groups seek help? 

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