Online field experiments: a selective survey of methods

Cao, Yan; Konstan, Joseph A.

doi:10.1007/s40881-015-0005-3

Cited by 35 publications

(22 citation statements)

References 37 publications

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“…For example, lenders who join teams might simply be those who are more active in general (4). To establish the causal relationship between group membership and prosocial lending, we use a randomized field experiment that enables us to combine the control of a laboratory experiment with the external validity of a field study (6,7).…”

mentioning

confidence: 99%

Recommending teams promotes prosocial lending in online microfinance

Chen

Yan

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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This paper reports the results of a large-scale field experiment designed to test the hypothesis that group membership can increase participation and prosocial lending for an online crowdlending community, Kiva. The experiment uses variations on a simple email manipulation to encourage Kiva members to join a lending team, testing which types of team recommendation emails are most likely to get members to join teams as well as the subsequent impact on lending. We find that emails do increase the likelihood that a lender joins a team, and that joining a team increases lending in a short window (1 wk) following our intervention. The impact on lending is large relative to median lender lifetime loans. We also find that lenders are more likely to join teams recommended based on location similarity rather than team status. Our results suggest team recommendation can be an effective behavioral mechanism to increase prosocial lending.social identity | charitable giving | microfinance | field experiment | recommender systems

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confidence: 99%

Recommending teams promotes prosocial lending in online microfinance

Chen

Yan

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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“…Internet technologies have opened new frontiers in social collective action and knowledge and the gathering of scientific data in the forms of online crowdsourcing and digital field experiments (see [153][154][155][156][157] for reviews). Crowdsourcing can be understood as the leveraging of information technologies for individual participation in collective processes [158], such as crowdfunding, mapping applications such as Waze, and citizen science data collection efforts (e.g., Christmas Bird Count [159] and Geo-Wiki [160]).…”

Section: Online Crowdsourcing and Field Experimentsmentioning

confidence: 99%

Computational Social Science of Disasters: Opportunities and Challenges

Burger

Kennedy

et al. 2019

Future Internet

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Disaster events and their economic impacts are trending, and climate projection studies suggest that the risks of disaster will continue to increase in the near future. Despite the broad and increasing social effects of these events, the empirical basis of disaster research is often weak, partially due to the natural paucity of observed data. At the same time, some of the early research regarding social responses to disasters have become outdated as social, cultural, and political norms have changed. The digital revolution, the open data trend, and the advancements in data science provide new opportunities for social science disaster research. We introduce the term computational social science of disasters (CSSD), which can be formally defined as the systematic study of the social behavioral dynamics of disasters utilizing computational methods. In this paper, we discuss and showcase the opportunities and the challenges in this new approach to disaster research. Following a brief review of the fields that relate to CSSD, namely traditional social sciences of disasters, computational social science, and crisis informatics, we examine how advances in Internet technologies offer a new lens through which to study disasters. By identifying gaps in the literature, we show how this new field could address ways to advance our understanding of the social and behavioral aspects of disasters in a digitally connected world. In doing so, our goal is to bridge the gap between data science and the social sciences of disasters in rapidly changing environments.

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“…Recent work investigating the ethical practices of CSCW researchers found that 22% of researchers surveyed held the view that obtaining informed consent is always necessary [37]. At the same time, waivers of informed consent are sought and obtained in field experiments across the social sciences [23,9]. However, the omission of informed consent was one of the key controversial issues discussed in the turmoil surrounding Facebook's emotional contagion experiment.…”

Section: Informed Consentmentioning

confidence: 99%

Bots as Virtual Confederates

Krafft

Macy

Pentland

2017

Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing

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The use of bots as virtual confederates in online field experiments holds extreme promise as a new methodological tool in computational social science. However, this potential tool comes with inherent ethical challenges. Informed consent can be difficult to obtain in many cases, and the use of confederates necessarily implies the use of deception. In this work we outline a design space for bots as virtual confederates, and we propose a set of guidelines for meeting the status quo for ethical experimentation. We draw upon examples from prior work in the CSCW community and the broader social science literature for illustration. While a handful of prior researchers have used bots in online experimentation, our work is meant to inspire future work in this area and raise awareness of the associated ethical issues.

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Online field experiments: a selective survey of methods

Cited by 35 publications

References 37 publications

Recommending teams promotes prosocial lending in online microfinance

Recommending teams promotes prosocial lending in online microfinance

Computational Social Science of Disasters: Opportunities and Challenges

Bots as Virtual Confederates

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