NDLI: Data-driven Human Behavior Models: Opportunities and Challenges

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Data-driven Human Behavior Models: Opportunities and Challenges

Content Provider	ACM Digital Library
Author	Oliver, Nuria
Abstract	We live in a world of data, of big data, a big part of which has been generated by humans through their interactions with both the physical and digital world. A key element in the exponential growth of human behavioral data is the mobile phone. There are more mobile phones in the world as humans which has turned the mobile phone into the piece of technology with the highest levels of adoption in human history. We carry them with us all through the day (and night, in many cases), leaving digital traces of our physical interactions. Mobile phones have become sensors of human activity both in the large scale and also as the most personal devices. In my talk, I present some of the work that we are doing at Telefonica Research in the area of modeling humans from human behavioral data collected from mobile phones. The data may be data that is automatically collected by the mobile network infrastructure --in particular Call Detail Records or CDRs---or data that is collected by an experimental mobile application through a user study. All projects entail data analytics and machine learning in order to build accurate models of individual or aggregate behavior. In particular, I describe four projects: (1) a project to automatically infer personality from Call Detail Records [1]; (2) MobiScore, a project to automatically assess a credit score from Call Detail Records [2]; Borapp, a mobile app that is able to detect boredom from patterns of phone usage [3] and a project to automatically predict crime hotspots in a city from human dynamics and demographic data [4]. I conclude by highlighting opportunities and challenges associated with building data-driven models of human behavior.
Starting Page	1
Ending Page	1
Page Count	1
File Format	PDF
ISBN	9781450341417
DOI	10.1145/2934732.2940297
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-06-14
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Machine learning Data-driven human behavior modeling Computational social sciences Artificial intelligence
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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