Human dynamics: computation for organizations

by: Alex Pentland, Tanzeem Choudhury, Nathan Eagle, Push Singh

Pattern Recognition Letters, Vol. 26, No. 4. (March 2005), pp. 503-511.

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Abstract

The human dynamics group at the MIT Media Laboratory proposes that active pattern analysis of face-to-face interactions within the workplace can radically improve the functioning of the organization. There are several different types of information inherent in such conversations: interaction features, participants, context, and content. By aggregating this information, high-potential collaborations and expertise within the organization can be identified, and information efficiently distributed. Examples of using wearable machine perception to characterize face-to-face interactions and using the results to initiate productive connections are described, and privacy concerns are addressed.

@article{pentland:dynamics, abstract = {The human dynamics group at the MIT Media Laboratory proposes that active pattern analysis of face-to-face interactions within the workplace can radically improve the functioning of the organization. There are several different types of information inherent in such conversations: interaction features, participants, context, and content. By aggregating this information, high-potential collaborations and expertise within the organization can be identified, and information efficiently distributed. Examples of using wearable machine perception to characterize face-to-face interactions and using the results to initiate productive connections are described, and privacy concerns are addressed.}, author = {Pentland, Alex and Choudhury, Tanzeem and Eagle, Nathan and Singh, Push }, booktitle = {ICAPR 2003}, citeulike-article-id = {3032986}, doi = {http://dx.doi.org/10.1016/j.patrec.2004.08.012}, journal = {Pattern Recognition Letters}, keywords = {measurement, pvnets, sensor-networks, social-networks, user-study}, month = {March}, number = {4}, pages = {503--511}, posted-at = {2008-07-22 16:23:42}, priority = {2}, title = {Human dynamics: computation for organizations}, url = {http://dx.doi.org/10.1016/j.patrec.2004.08.012}, volume = {26}, year = {2005} }

RIS record

TY - JOUR ID - pentland:dynamics L3 - citeulike-article-id:3032986 TI - Human dynamics: computation for organizations T2 - ICAPR 2003 JF - Pattern Recognition Letters VL - 26 IS - 4 SP - 503 EP - 511 N2 - The human dynamics group at the MIT Media Laboratory proposes that active pattern analysis of face-to-face interactions within the workplace can radically improve the functioning of the organization. There are several different types of information inherent in such conversations: interaction features, participants, context, and content. By aggregating this information, high-potential collaborations and expertise within the organization can be identified, and information efficiently distributed. Examples of using wearable machine perception to characterize face-to-face interactions and using the results to initiate productive connections are described, and privacy concerns are addressed. KW - measurement KW - pvnets KW - sensor-networks KW - social-networks KW - user-study AU - Pentland, Alex AU - Choudhury, Tanzeem AU - Eagle, Nathan AU - Singh, Push PY - 2005/03// UR - http://dx.doi.org/10.1016/j.patrec.2004.08.012 ER -

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