https://doi.org/10.1145/1963192.1963315">
 

Title

Citizen Sensor Data Mining, Social Media Analytics and Development Centric Web Applications

Document Type

Article

Abstract

With the rapid rise in the popularity of social media (500M+ Facebook users, 100M+ twitter users), and near ubiquitous mobile access (4.1 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.

Digital Object Identifier (DOI)

https://doi.org/10.1145/1963192.1963315

APA Citation

Nagarajan, M., Sheth, A. P., & Velmuru, S. (2011). Citizen Sensor Data Mining, Social Media Analytics and Development Centric Web Applications. WWW '11 Proceedings of the 20th International Conference Companion on World Wide Web, 289-290.
https://corescholar.libraries.wright.edu/knoesis/140

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