CPSWEEK

Accurate crime forecasting can allow law enforcement to more effectively plan their resource allocation such as patrol routes and placements. We study the effectiveness of traditional regression approaches in forecasting crime occurrences in Portland, ...

Social sensing is a typical application of the crowdsourcing system. With the consideration of system timeliness, flexibility, and stability, it could not be more natural to build a self-organized, distributed, and cross-platform crowdsourcing system. ...

With the rapid proliferation of smartphones, human beings act as social sensors by means of carrying GPS-enabled devices that share location data. This has resulted in an abundance of sensor data gathered over long periods of time. Gaining meaningful ...

In this paper, we consider the demographics associated with social media users as a basis for determining how to interact with a population group to inform military operations such as humanitarian aid and disaster relief (HADR). With social media use ...

Social media activity analysis can provide an open window to the inception and evolution of ideas. In this paper, we introduce a general model of spatiotemporal evolution of an arbitrary number of ideas in social media. As the main theoretical ...

Social sensing has received growing interest in a broad range of applications from business to health care. The potential benefits of modeling infectious disease spread through geo-tagged social sensing data has recently been demonstrated, yet it has ...

Participatory sensing enables individuals, each with limited sensing capability, to share measurements and contribute towards developing a complete knowledge of their environment. The success of a participatory sensing application is often measured in ...

We explore the design of an effective crowdsourcing system for an M-ary classification task. Crowd workers complete simple binary microtasks whose results are aggregated to give the final classification decision. We consider the scenario where the ...

Universities often draw from their student body when conducting human subject studies. Unfortunately, as with any longitudinal human studies project, data quality problems arise from student's waning compliance to the study. While incentive mechanisms ...

Social sensing services use humans as sensor carriers, sensor operators and sensors themselves in order to provide situation-awareness to applications. This promises to provide a multitude of benefits to the users, for example in the management of ...

Locating missing or lost objects has always been a challenging task. RFID technology and participatory sensing based approaches have offered solutions but often their adoption was limited due to the high hardware costs or low active participation ...

While humans can act as effective sensors, human input is subject to a high degree of error and highly dependent on the context. Furthermore, extracting the signal from the noise for social sensing is a difficult challenge. One approach to improving the ...

This paper proposes an unsupervised framework for tracking real world events from their traces on Twitter and Instagram. Empirical data suggests that event detection from Instagram streams errs on the false-negative side due to the relative sparsity of ...

Internet traffic is increasingly dominated by user-generated content, predominantly by multimedia content (photos and videos). The content is primarily shared in online social networks (OSNs) such as Pinterest, Twitter, and Facebook. In this paper, we ...

We propose research directions to model a holistic and general diffusion framework by considering heterogeneous social signals as contextual inputs and by incorporating universal components of real-world diffusion dynamics.

A key requirement for success of smart home energy management systems is understanding the user's psychological perception of a smart environments, and the design of control strategies that specifically take into account such dimensions in system ...

Dynamically localizing users in online social networks is challenging because people seldom post location-related microblogs due to privacy concern. To increase inference accuracy, a promising approach is to leverage microblogs from friends. However, it ...

Sensor devices widely used on vehicles enable the massive data collection for social behavior analysis. We mined trajectory data and on-board sensor data for point-of-interest (POI) locations, which further indicate public and personal social ...

Social sensing aims to collect sensory data by using human population as sensor carriers (e.g., location), sensor operators (e.g., taking photos), and sensors themselves (e.g., Twitter). The Internet of Things (IoT) applications facilitate social ...

The design of crowdsourcing applications to supplement public transportation information systems have generally assumed availability of high-speed Internet connection coupled with high data sampling and gathering via data-hungry application interfaces. ...