Proceedings ArticleDOI
Challenges for social sensing using WiFi signals
Mikkel Baun Kjærgaard,Petteri Nurmi +1 more
- pp 17-21
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TLDR
This paper reviews existing work on using WiFi for social sensing and outlines challenges that have to be addressed to utilize WiFi at large forsocial sensing.Abstract:
Smartphones are an attractive option for social sensing due to their widespread market penetration rate and advanced sensing capabilities. Enabling social sensing on smartphones would require techniques that can accurately detect and characterize physical proximity, an important prerequisite for the capture of more complex social phenomena. One of the most promising modalities for this purpose is WiFi, as it works both indoors and outdoors, and as WiFi signal environment tends to contain significant spatial variation. A challenge in using WiFi, however, is that the signals are affected by many noise sources, such as fast fading, body attenuation, hardware differences and varying access points densities. In this paper we review existing work on using WiFi for social sensing and outline challenges that have to be addressed to utilize WiFi at large for social sensing.read more
Citations
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Journal ArticleDOI
WiFi Sensing with Channel State Information: A Survey
TL;DR: This survey gives a comprehensive review of the signal processing techniques, algorithms, applications, and performance results of WiFi sensing with CSI, and presents three future WiFi sensing trends, i.e., integrating cross-layer network information, multi-device cooperation, and fusion of different sensors for enhancing existing WiFi sensing capabilities and enabling new WiFi sensing opportunities.
Journal ArticleDOI
Measuring large-scale social networks with high resolution.
Arkadiusz Stopczynski,Vedran Sekara,Piotr Sapiezynski,Andrea Cuttone,Mette My Madsen,Jakob Eg Larsen,Sune Lehmann +6 more
TL;DR: This paper describes the deployment of a large-scale study designed to measure human interactions across a variety of communication channels, with high temporal resolution and spanning multiple years—the Copenhagen Networks Study.
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Measuring large-scale social networks with high resolution. WORKING PAPER.
Arkadiusz Stopczynski,Vedran Sekara,Piotr Sapiezynski,Andrea Cuttone,Jakob Eg Larsen,Sune Lehmann +5 more
Abstract: This paper describes the deployment of a large-scale study designed to measure human interactions across a variety of communication channels, with high temporal resolution and spanning multiple years—the Copenhagen Networks Study. Specifically, we collect data on face-to-face interactions, telecommunication, social networks, location, and background information (personality, demographics, health, politics) for a densely connected population of 1 000 individuals, using state-of-the-art smartphones as social sensors. Here we provide an overview of the related work and describe the motivation and research agenda driving the study. Additionally, the paper details the data-types measured, and the technical infrastructure in terms of both backend and phone software, as well as an outline of the deployment procedures. We document the participant privacy procedures and their underlying principles. The paper is concluded with early results from data analysis, illustrating the importance of multi-channel high-resolution approach to data collection.
Journal ArticleDOI
The strength of friendship ties in proximity sensor data.
Vedran Sekara,Sune Lehmann +1 more
TL;DR: Applying the Bluetooth signal strength parameter to distinguish between observations, it is demonstrated that weak links, compared to strong links, have a lower probability of being observed at later times, while such links—on average—also have lower link-weights and probability of sharing an online friendship.
Journal ArticleDOI
Mobile sensing systems.
TL;DR: The main objective is to reduce the learning curve in mobile sensing systems where the complexity is very high.
References
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Journal ArticleDOI
Reality mining: sensing complex social systems
Nathan Eagle,Alex Pentland +1 more
TL;DR: The ability to use standard Bluetooth-enabled mobile telephones to measure information access and use in different contexts, recognize social patterns in daily user activity, infer relationships, identify socially significant locations, and model organizational rhythms is demonstrated.
Journal ArticleDOI
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Journal ArticleDOI
The Problem of Informant Accuracy: The Validity of Retrospective Data
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Proceedings ArticleDOI
Practical robust localization over large-scale 802.11 wireless networks
Andreas Haeberlen,Eliot John Flannery,Andrew M. Ladd,Algis Rudys,Dan S. Wallach,Lydia E. Kavraki +5 more
TL;DR: The system is sufficiently robust to enable a variety of location-aware applications without requiring special-purpose hardware or complicated training and calibration procedures, and can be adapted to work with previously unknown user hardware.
Proceedings ArticleDOI
EmotionSense: a mobile phones based adaptive platform for experimental social psychology research
Kiran K. Rachuri,Mirco Musolesi,Cecilia Mascolo,Peter J. Rentfrow,Chris Longworth,Andrius Aucinas +5 more
TL;DR: It is shown how speakers and participants' emotions can be automatically detected by means of classifiers running locally on off-the-shelf mobile phones, and how speaking and interactions can be correlated with activity and location measures.