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  1. University of Information Technology
  2. Faculty of Information Science

Information Extraction from Social Media

http://hdl.handle.net/20.500.12678/0000005353
http://hdl.handle.net/20.500.12678/0000005353
5e5d2027-f592-4095-ab52-6a0bb39fe820
9d96ed06-1483-4faf-ac5c-0a4297d8a68a
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Information Information Extraction from Social Media.pdf (194 Kb)
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Publication type
Conference paper
Upload type
Publication
Title
Title Information Extraction from Social Media
Language en
Publication date 2017-02-17
Authors
San San Nwe
Khin Nwe Ni Tun
Description
With the proliferation of social media
sites, such as Twitter, Facebook, and LinkedIn,
social streams have proven to contain the most
up-to-date information on current events.
Therefore, it is crucial to extract activities or
events from the social streams, such as tweets
and it become an ongoing research trend. Most
approaches that aim at extracting event
information from twitter typically use the context
of messages. However, exploiting the location
information of geo-referenced messages and the
profile data are also important because tweet
messages are short, fragmented and noisy, and
therefore not include complete information about
the events. For this, in this paper, a framework
for event-extraction and categorization from
Twitter is proposed. To extract the localized
related activities, several mining mechanisms
and cleaning techniques is used for real-time
twitter corpus and various language processing
approaches is applied for categorization the
events and then the system will display the
valuable information for the targeted domain.
Keywords
Information Extraction, Social Media, Activity, Event, Twitter
Conference papers
ICCA
16-17 February, 2017
International Conference on Computer Applications
Sedona Hotel, Yangon, Myanmar
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