128,749 research outputs found
Citizen Science 2.0 : Data Management Principles to Harness the Power of the Crowd
Citizen science refers to voluntary participation by the general public in scientific endeavors. Although citizen science has a long tradition, the rise of online communities and user-generated web content has the potential to greatly expand its scope and contributions. Citizens spread across a large area will collect more information than an individual researcher can. Because citizen scientists tend to make observations about areas they know well, data are likely to be very detailed. Although the potential for engaging citizen scientists is extensive, there are challenges as well. In this paper we consider one such challenge – creating an environment in which non-experts in a scientific domain can provide appropriate and accurate data regarding their observations. We describe the problem in the context of a research project that includes the development of a website to collect citizen-generated data on the distribution of plants and animals in a geographic region. We propose an approach that can improve the quantity and quality of data collected in such projects by organizing data using instance-based data structures. Potential implications of this approach are discussed and plans for future research to validate the design are described
Reconsidering online reputation systems
Social and socioeconomic interactions and transactions often require trust. In digital spaces, the main approach to facilitating trust has effectively been to try to reduce or even remove the need for it through the implementation of reputation systems. These generate metrics based on digital data such as ratings and reviews submitted by users, interaction histories, and so on, that are intended to label individuals as more or less reliable or trustworthy in a particular interaction context. We suggest that conventional approaches to the design of such systems are rooted in a capitalist, competitive paradigm, relying on methodological individualism, and that the reputation technologies themselves thus embody and enact this paradigm in whatever space they operate in. We question whether the politics, ethics and philosophy that contribute to this paradigm align with those of some of the contexts in which reputation systems are now being used, and suggest that alternative approaches to the establishment of trust and reputation in digital spaces need to be considered for alternative contexts
Incentive Mechanisms for Participatory Sensing: Survey and Research Challenges
Participatory sensing is a powerful paradigm which takes advantage of
smartphones to collect and analyze data beyond the scale of what was previously
possible. Given that participatory sensing systems rely completely on the
users' willingness to submit up-to-date and accurate information, it is
paramount to effectively incentivize users' active and reliable participation.
In this paper, we survey existing literature on incentive mechanisms for
participatory sensing systems. In particular, we present a taxonomy of existing
incentive mechanisms for participatory sensing systems, which are subsequently
discussed in depth by comparing and contrasting different approaches. Finally,
we discuss an agenda of open research challenges in incentivizing users in
participatory sensing.Comment: Updated version, 4/25/201
Is there Still a PR Problem Online? Exploring the Effects of Different Sources and Crisis Response Strategies in Online Crisis Communication Via Social Media
This study examined the effects of source and crisis response strategy on crisis communication outcomes in the context of social media. A 3 (source: organization, CEO, or customer) × 2 (strategy: accommodative or defensive) × 2 (crisis type: airline crash or bank hacking) mixed experimental study was conducted with 391 participants. The organizational sources were more likely to be perceived as more credible than the non-organizational sources. In particular, the CEO appeared to be the most trustworthy and credible source in delivering crisis messages. The path analysis indicated that perceived source credibility mediated the effect of source on reputation and behavioral intentions. This mediation appeared to be contingent on the type of crisis response strategy
From Social Data Mining to Forecasting Socio-Economic Crisis
Socio-economic data mining has a great potential in terms of gaining a better
understanding of problems that our economy and society are facing, such as
financial instability, shortages of resources, or conflicts. Without
large-scale data mining, progress in these areas seems hard or impossible.
Therefore, a suitable, distributed data mining infrastructure and research
centers should be built in Europe. It also appears appropriate to build a
network of Crisis Observatories. They can be imagined as laboratories devoted
to the gathering and processing of enormous volumes of data on both natural
systems such as the Earth and its ecosystem, as well as on human
techno-socio-economic systems, so as to gain early warnings of impending
events. Reality mining provides the chance to adapt more quickly and more
accurately to changing situations. Further opportunities arise by individually
customized services, which however should be provided in a privacy-respecting
way. This requires the development of novel ICT (such as a self- organizing
Web), but most likely new legal regulations and suitable institutions as well.
As long as such regulations are lacking on a world-wide scale, it is in the
public interest that scientists explore what can be done with the huge data
available. Big data do have the potential to change or even threaten democratic
societies. The same applies to sudden and large-scale failures of ICT systems.
Therefore, dealing with data must be done with a large degree of responsibility
and care. Self-interests of individuals, companies or institutions have limits,
where the public interest is affected, and public interest is not a sufficient
justification to violate human rights of individuals. Privacy is a high good,
as confidentiality is, and damaging it would have serious side effects for
society.Comment: 65 pages, 1 figure, Visioneer White Paper, see
http://www.visioneer.ethz.c
The Online Laboratory: Conducting Experiments in a Real Labor Market
Online labor markets have great potential as platforms for conducting
experiments, as they provide immediate access to a large and diverse subject
pool and allow researchers to conduct randomized controlled trials. We argue
that online experiments can be just as valid---both internally and
externally---as laboratory and field experiments, while requiring far less
money and time to design and to conduct. In this paper, we first describe the
benefits of conducting experiments in online labor markets; we then use one
such market to replicate three classic experiments and confirm their results.
We confirm that subjects (1) reverse decisions in response to how a
decision-problem is framed, (2) have pro-social preferences (value payoffs to
others positively), and (3) respond to priming by altering their choices. We
also conduct a labor supply field experiment in which we confirm that workers
have upward sloping labor supply curves. In addition to reporting these
results, we discuss the unique threats to validity in an online setting and
propose methods for coping with these threats. We also discuss the external
validity of results from online domains and explain why online results can have
external validity equal to or even better than that of traditional methods,
depending on the research question. We conclude with our views on the potential
role that online experiments can play within the social sciences, and then
recommend software development priorities and best practices
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