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

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Title Citizen Sensor Data Mining, Social Media Analytics and Development Centric Web Applications
Author , ,
Venue WWW 2011
Dates
Year 2011
Resource Type Tutorial Presentation
Keyword(s) social signals,user generated content,social media analysis,semantic social mashup,semantic social web,social development application,mobile development application,people-content-network view of social media,Citizen sensing
Full Citation Meenakshi Nagarajan,Amit Sheth,Selvam Velmurugan Citizen Sensor Data Mining, Social Media Analytics and Development Centric Web Applications Proc of the WWW 2011, March 28 - April 1, 2011, Hyderabad, India, ACM.
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.
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