The cost of search and evaluation in online problem-solving social networks with financial and non-financial incentives

  • Daniel Scain Farenzena Federal University of Rio Grande do Sul
  • Luís da Cunha Lamb Federal University of Rio Grande do Sul
  • Ricardo Matsumura Araújo Federal University of Pelotas
Keywords: Online Social Networks, Incentives, User interface, Problem Solving

Abstract

Online networks of individuals have been used to solve a number of problems on a scale that would not be possible if not within a connected, virtual and social environment such as the Internet. In this paper, we show that when solving tasks with small duration (under five minutes), also known as microtasks, individuals decision making will be strongly biased by costs of searching (and evaluating) options rather than financial or non-financial incentives. Indeed, we are able to show that we can influence individuals decisions, when solving problems, by rearranging elements visually to modify an individual search sequence, be it by designing the virtual work environment or manipulating which options are first shown in non-controlled environments, such as the Amazon Mechanical Turk labor market. We performed almost 50 experiments in online networks where individuals were invited to work on tasks with varying degrees of difficulty within three settings: mathematical games with objective truth (Sudoku and SAT instances); surveys with subjective evaluation (public policy polling); and labor markets (Amazon Mechanical Turk).

Author Biographies

Daniel Scain Farenzena, Federal University of Rio Grande do Sul

Daniel Scain Farenzena is a Software Architect at Aurea. He holds a Ph.D. in Computer Science from the Federal University of Rio Grande do Sul. His research interests include Data Science, Artificial Intelligence and and Social Computing.

Luís da Cunha Lamb, Federal University of Rio Grande do Sul
Luís C. Lamb is Professor and Dean of the Institute of Informatics at the Federal University of Rio Grande do Sul, Porto Alegre, Brazil. He holds a Ph.D. in Computing Science from the Imperial College London (2000) and the Diploma of the Imperial College, MSc by research (1995) and BSc in Computer Science (1992) from the Federal University of Rio Grande do Sul. His research interests include Logic in Computer Science and Artificial Intelligence, Neural Computation; Social Computing and Computing in the Physical and Social Sciences. Lamb holds an Advanced Research Fellowship from the Brazilian National Research Council CNPq.
Ricardo Matsumura Araújo, Federal University of Pelotas
Ricardo M Araujo is a Computer Science Professor at the Center for Technological Advancement in the Federal University of Pelotas (UFPel). He holds a PhD and Master Degrees in Computer Science from UFRGS and lectures at the Computer Science, Computer Engineering undergrad courses and the Graduation Program in Computer Science. His research interests include machine learning, computational social science and data science.
Published
2016-07-20
How to Cite
Farenzena, D. S., Lamb, L. da C., & Araújo, R. M. (2016). The cost of search and evaluation in online problem-solving social networks with financial and non-financial incentives. First Monday, 21(8). https://doi.org/10.5210/fm.v21i8.6751