Visualizing Trends on Twitter

With its popularity, Twitter has become an increasingly valuable source of real-time, user-generated information about interesting events in our world. This thesis presents TwitGeo, a system to explore and visualize trending topics on Twitter. It features an interactive map that summarizes trends across dierent geographical regions. Powered by a novel GPU-based datastore, this system performs ad hoc trend detection without predefined temporal or geospatial indexes, and is capable of discovering trends with arbitrary granularity in both dimensions. An evaluation of the system shows promising results for visualizing trends on Twitter in real time.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2013

Author dc:creator

• Tong, Cheng Hau

Advisor dc:contributor.advisor

• Samuel Madden.

• Electrical Engineering and Computer Science.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/85229

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/85229