Do I Care Enough? Using a Prosocial Tendencies Measure to Understand Twitter Users Sharing Behavior for Minor Public Safety Incidents

Social media has been used to assist victims of crises, especially large-scale disasters. Research describes the importance of the crowd who are the first witnesses to any sort of crime or disaster. Among others, this paper focuses on smaller scale public safety incidents such as suspicious activities, and minor robberies. We investigate whether prosocial tendencies affect Twitter users’ decisions to share minor public safety incidents on Twitter. The scale used has six subscales including: public, anonymous, dire, emotional, compliant, and altruism. The data (N=363) was collected through Mechanical Turk using an online anonymous survey. Initial results showed a positive relationship between being prosocial and sharing public safety incidents on Twitter. However, once additional variables related to Twitter use were introduced (number of public safety official accounts followed, news exposure on social media, and tweet/retweet frequency), these variables fully mediated the relationship. Limitations and design implications are discussed

Not So Digital After All? A Look at the Nature of Digital Nudging through the Prism of the Digital Object Concept

Digital nudging is an effective way to influence individuals’ behavior when they interact with digital computers. However, scholars only partially discussed how digital technology transforms nudging mechanisms in digital choice environments. Considering the recently proposed research agenda on digital objects, studying the ‘digital’ component of digital nudging can help to understand how the ‘digital’ transforms the phenomenon of nudging and creates new, digital-only methods of influencing individuals’ behavior. This paper investigates the current state of the literature on the context of digital nudging and discusses the role of digital objects in nudging with examples of how digital properties can transform the mechanisms of nudging

Exploring, understanding, then designing: twitter users’ sharing behavior for minor safety incidents

Social media has become an integral part of human lives. Social media users resort to these platforms for various reasons. Users of these platforms spend a lot of time creating, reading, and sharing content, therefore, providing a wealth of available information for everyone to use. The research community has taken advantage of this and produced many publications that allow us to better understand human behavior. An important subject that is sometimes discussed and shared on social media is public safety. In the past, Twitter users have used the platform to share incidents, share information about incidents, victims and perpetrators, and used it to provide help in distressed locations after an attack or after a natural disaster. Public safety officials also used Twitter to disseminate information to maintain and improve safety and seek information from the crowds. The previous focus of the research is mainly on significant public safety incidents; but, incidents with less severity matter too. The focus of this dissertation is on minor incidents and the aim is to understand what motivates social media users to share those incidents to maintain and increase public safety through design suggestions.This dissertation is comprised of three completed studies. The first study attempts to understand motivations to share public safety incidents on social media under the collective action theory lens. Collective action theory assumes that rational people will not participate in a public good unless there is a special incentive or an external motivation for them. In this study, public safety is considered as the public good. This study tests people’s willingness to share incidents on social media if: the victim is someone they know, if the location of the incident is close, and if there is some coercion to influence users willingness to share. General support is found for the hypotheses and collective action theory.In the second study, the focus is on internal motivations that stem from being prosocial. An established scale that measures six different traits of prosocial behavior is used. It is hypothesizes that prosocial behavior is positively related to decisions to share incidents on social media. The study also tests other mediating variables, namely: following news outlets on Twitter, following public safety officials on social media, frequency of tweeting/retweeting. Partial support for prosocial tendencies effect on decisions to share is found. The study also discoveres that the three mediating variables (number of public safety official accounts followed, news exposure on social media, and tweet/retweet frequency) fully mediates the relationship and that they have a significant positive effect on decisions to share. The third and final study complements the previous two and helps conclude the previous findings. A 2X2X2 online experiment design is conducted. The three manipulations are the availability of location information, platform authority availability, and availability of sender authority. The study hypothesizes that the three interventions will produce a significant positive relationship with decisions to share on Twitter. It is found that location information has no effect on sharing minor incidents on Twitter, however, participants are more likely to use a fictitious button that increases local exposure to minor public safety tweets. It is also found that the authority of the sender has a significant effect on decisions to share. On the other hand, platform authority does not show an effect on decisions to share public safety incidents on Twitter

A Study of Ethics in Crowd Work-Based Research

Crowd work as a form of a social-technical system has become a popular setting for conducting and distributing academic research. Crowd work platforms such as Amazon Mechanical Turk (MTurk) are widely used by academic researchers. Recent scholarship has highlighted the importance of ethical issues because they could affect the long-term development and application of crowd work in various fields such as the gig economy. However, little study or deliberation has been conducted on the ethical issues associated with academic research in this context. Current sources for ethical research practice, such as the Belmont Report, have not been examined thoroughly on how they should be applied to tackle the ethical issues in crowd work-based research such as those in data collection and usage. Hence, how crowd work-based research should be conducted to make it respectful, beneficent, and just is still an open question. This dissertation research has pursued this open question by interviewing 15 academic researchers and 17 IRB directors and analysts in terms of their perceptions and reflections on ethics in research on MTurk; meanwhile, it has analyzed 15 research guidelines and consent templates for research on MTurk and 14 published papers from the interviewed scholars. Based on analyzing these different sources of data, this dissertation research has identified three dimensions of ethics in crowd work-based research, including ethical issues in payment, data, and human subjects. This dissertation research also uncovered the “original sin” of these ethical issues and discussed its impact in academia, as well as the limitations of the Belmont Report and AoIR Ethical Guidelines 3.0 for Internet Research. The findings and implications of this research can help researchers and IRBs be more conscious about ethics in crowd work-based research and also inspire academic associations such as AoIR to develop ethical guidelines that can address these ethical issues