TAILIEUCHUNG - Báo cáo khoa học: "A Support Platform for Event Detection using Social Intelligence"

This paper describes a system designed to support event detection over Twitter. The system operates by querying the data stream with a user-specified set of keywords, filtering out non-English messages, and probabilistically geolocating each message. The user can dynamically set a probability threshold over the geolocation predictions, and also the time interval to present data for. | A Support Platform for Event Detection using Social Intelligence Timothy Baldwin Paul Cook Bo Han Aaron Harwood Shanika Karunasekera and Masud Moshtaghi Department of Computing and Information Systems The University of Melbourne Victoria 3010 Australia Abstract This paper describes a system designed to support event detection over Twitter. The system operates by querying the data stream with a user-specified set of keywords filtering out non-English messages and probabilistically geolocating each message. The user can dynamically set a probability threshold over the geolocation predictions and also the time interval to present data for. 1 Introduction Social media and micro-blogs have entered the mainstream of society as a means for individuals to stay in touch with friends for companies to market products and services and for agencies to make official announcements. The attractions of social media include their reach either targeted within a social network or broadly across a large user base ability to selectively pub-lish filter information selecting to publish certain information publicly or privately to certain groups and selecting which users to follow and real-time nature information push happens immediately at a scale unachievable with . email . The serendipitous takeoff in mobile devices and widespread support for social media across a range of devices have been significant contributors to the popularity and utility of social media. While much of the content on micro-blogs describes personal trivialities there is also a vein of high-value content ripe for mining. As such organisations are increasingly targeting micro-blogs for monitoring purposes whether it is to gauge product acceptance detect events such as traffic jams or track complex unfolding events such as natural disasters. In this work we present a system intended to support real-time analysis and geolocation of events based on Twitter. Our system consists of the following steps 1 user selection

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