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  1. University of Computer Studies, Yangon
  2. Conferences

Information Extraction from Social Media

http://hdl.handle.net/20.500.12678/0000004815
http://hdl.handle.net/20.500.12678/0000004815
81968e21-114e-427a-aaa1-1bd195593c6c
99f0316a-cd69-4e85-841c-33e89c7c3715
Publication type
Article
Upload type
Publication
Title
Title Information Extraction from Social Media
Language en
Publication date 2017-02-16
Authors
Nwe, San San
Tun, Khin Nwe Ni
Description
With the proliferation of social media sites, suchas Twitter, Facebook, and LinkedIn, social streamshave proven to contain the most up-to-date informationon current events. Therefore, it is crucial to extractactivities or events from the social streams, such astweets and it become an ongoing research trend. Mostapproaches that aim at extracting event informationfrom twitter typically use the context of messages.However, exploiting the location information of georeferencedmessages and the profile data are alsoimportant because tweet messages are short,fragmented and noisy, and therefore not includecomplete information about the events. For this, in thispaper, a framework for event-extraction andcategorization from Twitter is proposed. To extract thelocalized related activities, several mining mechanismsand cleaning techniques is used for real-time twittercorpus and various language processing approaches isapplied for categorization the events and then thesystem will display the valuable information for thetargeted domain.
Keywords
Information Extraction, Social Media, Activity, Event, Twitter
Identifier http://onlineresource.ucsy.edu.mm/handle/123456789/713
Journal articles
Fifteenth International Conference on Computer Applications(ICCA 2017)
Conference papers
Books/reports/chapters
Thesis/dissertations
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