Social media enabled human sensing for smart cities-Reference-Cited by-同舟云学术

Social media enabled human sensing for smart cities

Published:2015-08-11 Issue:1 Volume:29 Page:57-75
ISSN:1875-8452
Container-title:AI Communications
language:
Short-container-title:AIC

Author:

Doran Derek¹,Severin Karl²,Gokhale Swapna²,Dagnino Aldo³

Affiliation:

1. Department of Computer Science and Engineering, Kno.e.sis Research Center, Wright State University, Dayton, OH, USA. E-mail: derek.doran@wright.edu

2. Department of Computer Science and Engineering, University of Connecticut, Storrs, CT, USA. E-mails: karl.severin@engr.uconn.edu, ssg@engr.uconn.edu

3. Industrial Software Systems, Data Analytics Group, ABB Corporate Research, Raleigh, NC, USA. E-mail: aldo.dagnino@us.abb.com

Publisher

IOS Press

Subject

Artificial Intelligence

Reference64 articles.

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3. Smart cities of the future;Batty;The European Physical Journal,2012

4. [5]E. Baucom, A. Sanjari, X. Liu and M. Chen, Mirroring the real world in social media: Twitter, geolocation, and sentiment analysis, in: Proceedings of the International Workshop on Mining Unstructured Big Data Using Natural Language Processing, 2013, pp. 61–68.

5. [6]J. Bollen, H. Mao and A. Pepe, Modeling public mood and emotion: Twitter sentiment and socio-economic phenomena, in: Proceedings of International Conference on Weblogs and Social Media, 2011, pp. 450–453.

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