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

机译:市民传感器数据挖掘,社交媒体分析和以开发为中心的Web应用程序

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摘要

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.
机译:随着社交媒体(5亿+ Facebook用户,1亿+ Twitter用户)的普及迅速增长,以及近乎无处不在的移动访问(41亿活跃使用的手机),意见和观点的共享已变得司空见惯(近1亿条推文)去年,每天有1.8万亿条SMS。这使我们能够前所未有地接触到民众,并能够对社会数据进行分析以支持各种社会智能应用程序-从而实现针对性的在线内容交付,危机管理,组织革命或促进社会发展。欠发达国家和发展中国家。本教程将解决构建支持广泛用户和社交媒体类型的应用程序的挑战和技术。本教程将侧重于社会智能在社会发展中的应用,并充分深入地涵盖以下研究工作:1)特别是对非正式文本的理解和分析。微博(例如,文化实体提取问题以及语义/背景知识增强技术的作用),以及2)建立社交媒体分析平台。技术见解将与识别计算技术和实际示例结合在一起。

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