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Crowdsourcing on the spot: altruistic use of public displays, feasibility, performance, and behaviours
- In Ubicomp. ACM
"... This study is the first attempt to investigate altruistic use of interactive public displays in natural usage settings as a crowdsourcing mechanism. We test a non-paid crowdsourcing service on public displays with eight different motivation settings and analyse users ’ behavioural patterns and crowd ..."
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This study is the first attempt to investigate altruistic use of interactive public displays in natural usage settings as a crowdsourcing mechanism. We test a non-paid crowdsourcing service on public displays with eight different motivation settings and analyse users ’ behavioural patterns and crowdsourcing performance (e.g., accuracy, time spent, tasks completed). The results show that altruistic use, such as for crowdsourcing, is feasible on public displays, and through the controlled use of motivational design and validation check mechanisms, performance can be improved. The results shed insights on three research challenges in the field: i) how does crowdsourcing performance on public displays compare to that of online crowdsourcing, ii) how to improve the quality of feedback collected from public displays which tends to be noisy, and iii) identify users ’ behavioural patterns towards crowdsourcing on public displays in natural usage settings.
Challenges and opportunities on the large scale study of city dynamics using participatory sensing
- In ISCC’13
, 2013
"... Abstract—Cities are not identical and evolve over time, and sensing in large scale can be used to capture these differences. Research in Wireless Sensor Networks has provided several tools, techniques and algorithms to solve the problem of sensing in restricted scenarios (e.g., factory). However, se ..."
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Abstract—Cities are not identical and evolve over time, and sensing in large scale can be used to capture these differences. Research in Wireless Sensor Networks has provided several tools, techniques and algorithms to solve the problem of sensing in restricted scenarios (e.g., factory). However, sensing large scale areas, such as big cities, brings many challenges and incurs high costs related to system building and management. Thus, sensing those areas becomes more feasible when people collaborate among themselves using their portable devices, and building what has been named participatory sensing systems. This work analyzes an emerging type of network derived from this type of system, the Participatory Sensor Network (PSN), where nodes are autonomous mobile entities and the sensing depends on whether they want to participate in the sensing process. Based on four datasets of participatory sensing systems (27 million of records), we show that this type of network brings many challenges related to structural problems, e.g. instant coverage very limited, and also because of big data issues, which may restrict the use of this emerging type of network. However, it presents also, as shown here, many advantages and open opportunities, mainly related to large scale study of cities dynamics. Keywords-Participatory sensing; big data; location sharing services; social networks; smart cities I.
A comparison of Foursquare and Instagram to the study of city dynamics and urban social behavior
- In Proceedings of the 2nd ACM SIGKDD International Workshop on Urban Computing (UrbComp 13). ACM
, 2013
"... Social media systems allow a user connected to the Internet to pro-vide useful data about the context in which they are at any given moment, such as Instagram and Foursquare, which are called par-ticipatory sensing systems. Location sharing services are examples of participatory sensing systems. The ..."
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Social media systems allow a user connected to the Internet to pro-vide useful data about the context in which they are at any given moment, such as Instagram and Foursquare, which are called par-ticipatory sensing systems. Location sharing services are examples of participatory sensing systems. The sensed data is a check-in of a particular place that indicates, for instance, a restaurant in a specific location, and also a signal from a user expressing his/her preference. From a participatory sensing system we can derive a participatory sensor network. In this work we compare two differ-ent participatory sensor networks, one derived from Instagram, and another one derived from Foursquare. In Instagram, the sensed data is a picture of a specific place. On the other hand, in Foursquare the sensed data is the actual location associated with a specific cate-gory of place (e.g., restaurant). Using those social networks we can
Universidade Federal de
- Food Control
, 2006
"... (Brazil) birth cohort study: methods ..."
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Worker Ranking Determination in Crowdsourcing Platforms using Aggregation Functions
"... Abstract — The increasing adoption of crowdsourcing for commercial and industrial purposes rises the need for creating sophisticated mechanisms in crowd-based digital platforms for efficient worker management. One of the main challenges in this area is worker motivation and skill set control and its ..."
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Abstract — The increasing adoption of crowdsourcing for commercial and industrial purposes rises the need for creating sophisticated mechanisms in crowd-based digital platforms for efficient worker management. One of the main challenges in this area is worker motivation and skill set control and its impact on the output quality. The quality delivered by the workers in the crowd depends on different aspects such as their skills, experience, commitment, etc. The lack of generic and detailed proposals to incentive workers and the need for creating ad-hoc solutions depending on the domain make it difficult to evaluate the best rewarding functions in each scenario. In this paper, we make a step further in this direction and propose the use of aggregation functions to evaluate the professional skills of crowd-workers based on the quality of their past tasks. Addi-tionally, we present a real industrial crowdsourcing solution for software localisation in which the proposed solutions are put into practice with real text translations quality measures. I.
Worker Performance in a Situated Crowdsourcing Market
"... We present an empirical study that investigates crowdsourcing performance in a situated market. Unlike online markets, situated crowdsourcing markets consist of workers who become serendipitously available for work in a particular location and context. So far, the literature has lacked a systematic ..."
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We present an empirical study that investigates crowdsourcing performance in a situated market. Unlike online markets, situated crowdsourcing markets consist of workers who become serendipitously available for work in a particular location and context. So far, the literature has lacked a systematic study of task performance and uptake in such markets under varying incentives. In a 3-week field study, we demonstrate that in a situated crowdsourcing market, task uptake and accuracy are generally comparable with online markets. We also show that increasing task rewards in situated crowdsourcing leads to increased task uptake but not accuracy, while decreasing task rewards leads to decreases in both task uptake and accuracy. RESEARCH HIGHLIGHTS • We present a 3-week empirical study on worker performance in a situated crowdsourcing market. • We manipulate task rewards to investigate its effects on performance. • Increasing task rewards led to increased task uptake but not accuracy. • Decreasing task rewards led to decreased task uptake and accuracy. • We compare the performance of our reported tasks and literature using several types of crowdsourcing.
Social Media as a Source of Sensing to Study City Dynamics and Urban Social Behavior: Approaches, Models, and Opportunities
"... Abstract. In order to achieve the concept of ubiquitous computing, popularized by Mark Weiser, is necessary to sense the environment. One alternative is use traditional wireless sensor networks (WSNs). However, WSNs have their limita-tions, for instance in the sensing of large areas, such as metropo ..."
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Abstract. In order to achieve the concept of ubiquitous computing, popularized by Mark Weiser, is necessary to sense the environment. One alternative is use traditional wireless sensor networks (WSNs). However, WSNs have their limita-tions, for instance in the sensing of large areas, such as metropolises, because it incurs in high costs to build and maintain such networks. The ubiquity of smart phones associated with the adoption of social media websites, forming what is called participatory sensing systems (PSSs), enables unprecedented opportunities to sense the environment. Particularly, the data sensed by PSSs is very interesting to study city dynamics and urban social behavior. The goal of this work is to sur-vey approaches and models applied to PSSs data aiming the study city dynamics and urban social behavior. Besides that it is also an objective of this work discuss some of the challenges and opportunities when using social media as a source of sensing. 1
A picture of Instagram is worth more than a thousand words: Workload characterization and application
"... Abstract—Participatory sensing systems (PSSs) have the po-tential to become fundamental tools to support the study, in large scale, of urban social behavior and city dynamics. To that end, this work characterizes the photo sharing system Instagram, considered one of the currently most popular PSS on ..."
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Abstract—Participatory sensing systems (PSSs) have the po-tential to become fundamental tools to support the study, in large scale, of urban social behavior and city dynamics. To that end, this work characterizes the photo sharing system Instagram, considered one of the currently most popular PSS on the Internet. Based on a dataset of approximately 2.3 million shared photos, we characterize user’s behavior in the system showing that there are several advantages and opportunities for large scale sensing, such as a global coverage at low cost, but also challenges, such as a very unequal photo sharing frequency, both spatially and temporally. We also observe that the temporal photo sharing pattern is a good indicator about cultural behaviors, and also says a lot about certain classes of places. Moreover, we present an application to identify regions of interest in a city based on data obtained from Instagram, which illustrates the promising potential of PSSs for the study of city dynamics. I.
Visualizing the invisible image of cities
"... Abstract—With the recent advances in technology, we have the opportunity to study the city dynamics at a large scale. A fundamental step is to be able to sense extensive areas. Participatory sensor networks have the potential to become a very fundamental tool to study social behavior at a large scal ..."
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Abstract—With the recent advances in technology, we have the opportunity to study the city dynamics at a large scale. A fundamental step is to be able to sense extensive areas. Participatory sensor networks have the potential to become a very fundamental tool to study social behavior at a large scale. Currently, there are some location sharing services, such as Foursquare, that record the user’s location along the time, which is clearly one of dimensions in the city dynamics. In this work, we propose a technique called City image and show its applicability taking as examples eight different cities. The resulting image is a way of summarizing the city dynamics based on transition graphs, which map the movements of individuals in a PSN. This technique is a promising way to better understand the city dynamics, helping us to visualize the invisible images of cities. I.
ENGINEERING CROWDSOURCED STREAM PROCESSING SYSTEMS
, 2014
"... A crowdsourced stream processing system (CSP) is a system that incorporates crowd-sourced tasks in the processing of a data stream. This can be seen as enabling crowd-sourcing work to be applied on a sample of large-scale data at high speed, or equivalently, enabling stream processing to employ huma ..."
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A crowdsourced stream processing system (CSP) is a system that incorporates crowd-sourced tasks in the processing of a data stream. This can be seen as enabling crowd-sourcing work to be applied on a sample of large-scale data at high speed, or equivalently, enabling stream processing to employ human intelligence. It also leads to a substantial expansion of the capabilities of data processing systems. Engineering a CSP system requires the combination of human and machine computation elements. From a general systems theory perspective, this means taking into account inherited as well as emerging properties from both these elements. In this paper, we position CSP systems within a broader taxonomy, outline a series of design principles and evaluation metrics, present an extensible framework for their design, and describe several design patterns. We showcase the capabilities of CSP systems by performing a case study that applies our proposed framework to the design and analysis of a real system (AIDR) that classifies social media messages during time-critical crisis events. Results show that compared to a pure stream processing system, AIDR can achieve a higher data classification accuracy, while com-pared to a pure crowdsourcing solution, the system makes better use of human workers by requiring much less manual work effort.
