ONLINE DATA COLLECTION AS ADAPTATION IN CONDUCTING QUANTITATIVE AND QUALITATIVE RESEARCH DURING THE COVID-19 PANDEMIC

This study was conducted to identify online data collection methodologies as an adaptation in the conduct of quantitative and qualitative research amidst the COVID-19 pandemic. While data collection has been hampered by the restrictions posed by the quarantine measures of the local governments around the globe, researchers need to strategize and adapt remote tools in data collection. Analyzing from the responses of 25 highly engaged researchers who served as participants of this study through videoconferencing, it was found out that data collection for quantitative research may be conducted by using online development tools via personal or institutional subscriptions, using google forms as a free and conventional platform, and by using QR Code to generate the electronic survey questionnaire. On the other hand, the data collection for qualitative research may be conducted by using diaries and reflections of participants to replace the typical direct observation, using telephone or mobile phone to conduct an interview, and by using video-conferencing for key informant interview and focus group discussion. Considering the practicality and feasibility of these data collection methods, researchers cannot be constrained by the quarantine and health protocols in pursuing reliable, honest, and high-quality research outputs. Article visualizations

Measuring Psychological Effects of Peer-to-Peer Reputation Systems Involving In-Person Exchanges

University of Minnesota M.S. thesis. July 2019. Major: Computer Science. Advisor: Haiyi Zhu. 1 computer file (PDF); iv, 18 pages.Reputation systems such as those used by peer-to-peer services have proven significant in helping companies better understand and manage their users. Seemingly the new credit scores for the digital economy, these personal rating systems have unexplored consequences on human psyche. Using a case study of Uber passengers and drivers, this study examines stress and control levels associated with personal rating scores. We found that while drivers indicated more difficult experiences in response to the control of their scores, passengers had issues with distress in relation to factors commonly associated with bias, such as age and ethnicity. Both groups exhibited lower perceptions of distress the more times they had used Uber. Overall, the use of peer-to-peer reputation systems can be improved to provide users a higher level of control and lower distress in response to ratings

A Replication of Beyond the Turk: Alternative Platforms for Crowdsourcing Behavioral Research – Sometimes Preferable to Student Groups

This study is a replication of one of two studies found in “Beyond the Turk: Alternative platforms for crowdsourcing behavioral research” (Peer, Brandimarte, Samat, & Acquisti, 2017). We conduct an empirical analysis and comparison between two online crowdsourcing platforms, Amazon Mechanical Turk (MTurk) and Prolific Academic (ProA), as well as to a traditional student group. The online crowdsourcing platform (e.g., MTurk and others) used for years as a launching point for many types of microwork, including academic research. Today, MTurk has several competitors, including one that was built to focus on research tasks, ProA. Across the four segments, we reinforce the original study by finding both MTurk and ProA to provide inexpensive, reliable, and significantly faster methods of conducting surveys over traditional methods. Our results indicate that ProA provides superior service. By centering on research, ProA results are similar to MTurk’s. However, ProA’s response and completion rates, diversity, attention, naivety, reproducibility, and dishonest behavior are better

Estrategias de pago de deudas en jóvenes profesionales y deudores de Santiago de Chile : Tipologías a partir de un análisis de clases latentes

En un contexto como el chileno caracterizado por la expansión del mercado crediticio por la masificación de los créditos estudiantiles como fórmula de acceso a la educación superior y de desprotección institucional frente al mercado del crédito, esta ponencia se propone explorar las estrategias de pago de deudas de jóvenes deudores de Santiago de Chile por medio de un análisis de clases latentes. Los resultados dan cuenta de tres perfiles de deudores en función de las estrategias de pago que movilizan para responder a sus compromisos financieros, a saber: estrategias múltiples, estrategias individualizadas y estrategias no financiarizadas. Las principales diferencias entre cada tipología refieren a los accesos y usos de los instrumentos financieros que los jóvenes activan para responder a sus deudas. Independientemente de las diferencias entre estos grupos, los resultados dan cuenta del uso generalizado de estrategias de planificación de gastos, de activación de las redes sociales y de generación de nuevas entradas económicas. Una caracterización clara de los perfiles de deudores según las estrategias de pago puede favorecer una aproximación más comprensiva para intervenir los problemas financieros de la población.Instituto de Investigaciones en Humanidades y Ciencias Sociale

Effects of Persuasive Dialogues: Testing Bot Identities and Inquiry Strategies

Intelligent conversational agents, or chatbots, can take on various identities and are increasingly engaging in more human-centered conversations with persuasive goals. However, little is known about how identities and inquiry strategies influence the conversation's effectiveness. We conducted an online study involving 790 participants to be persuaded by a chatbot for charity donation. We designed a two by four factorial experiment (two chatbot identities and four inquiry strategies) where participants were randomly assigned to different conditions. Findings showed that the perceived identity of the chatbot had significant effects on the persuasion outcome (i.e., donation) and interpersonal perceptions (i.e., competence, confidence, warmth, and sincerity). Further, we identified interaction effects among perceived identities and inquiry strategies. We discuss the findings for theoretical and practical implications for developing ethical and effective persuasive chatbots. Our published data, codes, and analyses serve as the first step towards building competent ethical persuasive chatbots.Comment: 15 pages, 10 figures. Full paper to appear at ACM CHI 202

Cultural Perspectives on Climate Change: Examining Differences among College Students in Climate Change Threat Perception, Knowledge, and Behaviors

Guided by the Cultural Theory of Risk (CTR), the present study examined the relationship between college students’ cultural worldviews and their climate change threat perception, knowledge levels, and likelihood of engaging in mitigation behaviors. Additionally, the study attempted to investigate the association between the greenhouse gas (GHG) emissions levels of college students’ home countries and their perceived threat of climate change. One-hundred fifty-one college students, representing eighteen countries, completed a survey assessing these variables. Pearson’s correlation analyses revealed a positive relationship between both individualism and hierarchy and college students’ climate change threat perception, knowledge levels, and mitigation behaviors. While a small and demographically skewed sample precluded a global analysis of the association between home country and threat perception, American and Indian respondents had no difference in their perceived threat of climate change. This study’s findings provide a more complete picture of the factors that influence college students’ climate change attitudes and behaviors as well as several implications for achieving more effective climate change communication among culturally diverse college students

THE EFFECTS OF DATA VISUALIZATION AND INFORMATION GRAPHICS ON PUBLIC OPINION IN RESPONSE TO ENDANGERED SPECIES ACT (ESA) LISTING ANNOUNCEMENTS

Scholars have documented the positive effects of data visualizations and infographics on public opinion and understanding that have transcended academic fields and topics. The purpose of this research was to determine if utilizing data visualizations and information graphics can help improve public support for the ESA, ESA listing decisions and the species in the listings. An online experiment tested the effect of infographics on participants’ impressions, feelings and support for the ESA, ESA listing decisions and the species in the listings. The data revealed that ideology has a powerful impact on feelings and support for species and the ESA, regardless of information graphics, species, or learning preferences. Although ideology seemed to outweigh nearly all other factors and variables in the experiment, in the case of impressions of the listing decisions, visual literacy showed a significant effect where other factors, including ideology, did not. While more research should be focused on understanding the role of ideology in information graphics designed for government agencies and/or politicized issues, considering alternative ways to inform their audiences without activating ideology could help increase public support for their duties and mission.Master of Art

Personalizing Persuasive Strategies in Gameful Systems to Gamification User Types

© Owners/Authors, 2018. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in CHI '18 Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. DOI: https://doi.org/10.1145/3173574.3174009Persuasive gameful systems are effective tools for motivating behaviour change. Research has shown that tailoring these systems to individuals can increase their efficacy; however, there is little knowledge on how to personalize them. We conducted a large-scale study of 543 participants to investigate how different gamification user types responded to ten persuasive strategies depicted in storyboards representing persuasive gameful health systems. Our results reveal that people’s gamification user types play significant roles in the perceived persuasiveness of different strategies. People scoring high in the ‘player’ user type tend to be motivated by competition, comparison, cooperation, and reward while ‘disruptors’ are likely to be demotivated by punishment, goal-setting, simulation, and self-monitoring. ‘Socialisers’ could be motivated using any of the strategies; they are the most responsive to persuasion overall. Finally, we contribute to CHI research and practice by offering design guidelines for tailoring persuasive gameful systems to each gamification user type.NSERC Banting CNPq, Brazil SSHRC || 895-2011-1014, IMMERSe NSERC || RGPIN-418622-2012 CFI || 35819 Mitacs || IT0725

Users\u27 Knowkedge and Social Media Sharing Behaviors

The success of social media marketing tactics is highly dependent on the understanding of social media users\u27 information sharing behaviors. Social media user’s likelihood to share is related to various factors, such as knowledge, belief and personality traits. Survey data from 504 American social media users reveals that users\u27 perceived knowledge about social media marketing tactics positively related to their perceived benefits, which further associated with their likelihood of sharing information on social media. Findings also indicate that users\u27 desire for control partially mediates relationship between users’ knowledge of social media tactics and their likelihood to share information. However, the data does not provide evidence for the expected relationship between knowledge, perceived privacy risk and social media sharing behaviors. The findings reinforce the expectancy-value model, indicating the relationship between social media users’ perception of positive self-performance in evaluating social media marketing tactics and the activeness of social media use. The author also discusses the privacy paradox in social media use

Training non-surgical experts to annotate open-source surgical videos for machine learning

The use of video annotation for utilization in machine learning computer programs is an area of medicine that has shown increased demand for research in recent years. The limiting factor for the use of video annotation in surgery is the scale and efficiency in which videos can be labelled. The challenge in surgical contexts is the current notion that only surgical experts can provide accurate video annotations. To challenge this notion, we have conceived a survey to test non-surgical experts’ abilities to accurately annotate open-source surgical videos. This test has been published on the crowdsourcing platform Amazon mTurk. A learning module was created to provide relevant and concise information necessary to accurately annotate the surgical video and complete the survey. This learning module illustrates important instructions on differentiating between three surgical activities of focus: cutting, suturing, and tying. The survey includes free-response and multiple-choice questions that test the accuracy of respondent’s video annotation. Analyzing the results from 50 participants, more data from larger scale studies must be acquired, greater data validation systems must be implemented, and instructions in the survey and learning module must be adapted. These changes are due to high rates of inaccurate annotation for all three surgical activities. The data showed no clear indication that cutting, suturing, or tying could be accurately identified but further investigation would be prudent in the future