tutorial

Citizen sensor data mining, social media analytics and development centric web applications

Authors:

Meena Nagarajan,

Amit Sheth,

Selvam VelmuruganAuthors Info & Claims

WWW '11: Proceedings of the 20th international conference companion on World wide web

Pages 289 - 290

https://doi.org/10.1145/1963192.1963315

Published: 28 March 2011 Publication History

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Abstract

With the rapid rise in the popularity of social media (500M+ Facebook users, 100M+ twitter users), and near ubiquitous mobile access (4+ billion actively-used mobile phones), the sharing of observations and opinions has become common-place (nearly 100M tweets a day, 1.8 trillion SMSs in US last year). This has given us an unprecedented access to the pulse of a populace and the ability to perform analytics on social data to support a variety of socially intelligent applications -- be it towards targeted online content delivery, crisis management, organizing revolutions or promoting social development in underdeveloped and developing countries.

This tutorial will address challenges and techniques for building applications that support a broad variety of users and types of social media. This tutorial will focus on social intelligence applications for social development, and cover the following research efforts in sufficient depth: 1) understanding and analysis of informal text, esp. microblogs (e.g., issues of cultural entity extraction and role of semantic/background knowledge enhanced techniques), and 2) building social media analytics platforms. Technical insights will be coupled with identification of computational techniques and real-world examples.

References

[1]

D. Gruhl, M. Nagarajan, J. Pieper, C. Robson, A. Sheth, Multimodal Social Intelligence in a Real-Time Dashboard System, special issue on 'Data Management and Mining for Social Networks and Social Media', the VLDB Journal, 19 (6), 2010. http://portal.acm.org/citation.cfm?id=1921807

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[2]

A. Sheth, Citizen Sensing, Social Signals, and Enriching Human Experience, IEEE Internet Computing, July/August 2009, pp. 80--85. http://www.computer.org/portal/web/csdl/doi/10.1109/MIC.2009.77

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[3]

M. Nagarajan, K. Gomadam, A. Sheth, A. Ranabahu, R. Mutharaju and A. Jadhav, Spatio-Temporal-Thematic Analysis of Citizen-Sensor Data - Challenges and Experiences, 10th Intl Conf on Web Information Systems Engineering, Oct 5-7, 2009, pp. 539 - 553. http://www.springerlink.com/content/q682443076047208/

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[4]

OSI, Harvard and Columbia Case Studies covering project carried out by Selvam's NGOs: see http://emoksha.org

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[5]

P. Mendes, A. Passant, P. Kapanipathi, A. Sheth, "Linked Open Social Signals," WI2010 IEEE/WIC/ACM International Conference on Web Intelligence (WI-10), Toronto, Canada, Aug. 31 to Sep. 3, 2010.

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Cited By

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Ciftci D(2021)Political Marketing and New Media Election CampaigningHandbook of Research on New Media Applications in Public Relations and Advertising10.4018/978-1-7998-3201-0.ch021(355-379)Online publication date: 2021
https://doi.org/10.4018/978-1-7998-3201-0.ch021
Tran H(2021)Studying the Community of Trump Supporters on Twitter during the 2020 US Presidential Election via Hashtags #maga and #trump2020Journalism and Media10.3390/journalmedia20400422:4(709-731)Online publication date: 18-Nov-2021
https://doi.org/10.3390/journalmedia2040042
Wahyu Wibowo THeru Murti Budi Santosa SSusilo BHery Purwanto T(2021)Geotemporal analysis and topic modelling of Twitter data: study in nine big city areas of IndonesiaSeventh Geoinformation Science Symposium 202110.1117/12.2619356(37)Online publication date: 22-Dec-2021
https://doi.org/10.1117/12.2619356
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Index Terms

Citizen sensor data mining, social media analytics and development centric web applications
1. Human-centered computing
  1. Collaborative and social computing
    1. Collaborative and social computing systems and tools
2. Information systems
  1. World Wide Web

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Published In

WWW '11: Proceedings of the 20th international conference companion on World wide web

March 2011

552 pages

ISBN:9781450306379

DOI:10.1145/1963192

General Chairs:
S. Sadagopan
IIIT-Bangalore, India
,
Krithi Ramamritham
IIT-Bombay, India
,
Arun Kumar
IBM Research, India
,
M. P. Ravindra
Infosys E & R, India
,
Program Chairs:
Elisa Bertino
Purdue University, USA
,
Ravi Kumar
Yahoo! Research, USA

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
The International Institute of Information Technology Bangalore: The International Institute of Information Technology Bangalore

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Association for Computing Machinery

New York, NY, United States

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Published: 28 March 2011

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WWW '11

WWW '11: 20th International World Wide Web Conference

March 28 - April 1, 2011

Hyderabad, India

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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https://doi.org/10.4018/978-1-7998-3201-0.ch021
Tran H(2021)Studying the Community of Trump Supporters on Twitter during the 2020 US Presidential Election via Hashtags #maga and #trump2020Journalism and Media10.3390/journalmedia20400422:4(709-731)Online publication date: 18-Nov-2021
https://doi.org/10.3390/journalmedia2040042
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https://doi.org/10.1117/12.2619356
Yang YHsu JLöfgren KCho W(2021)Cross-platform comparison of framed topics in Twitter and Weibo: machine learning approaches to social media text miningSocial Network Analysis and Mining10.1007/s13278-021-00772-w11:1Online publication date: 14-Aug-2021
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Abas SAddou M(2021)Geospatial Forecasting and Social Media Exploration Based on Sentiment Analysis: Application to Flood ForecastingGeospatial Intelligence10.1007/978-3-030-80458-9_2(19-29)Online publication date: 11-Nov-2021
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Mining social media with social theories: a survey

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