Adaptive Representations for Tracking Breaking News on Twitter
NewsKDD, August 24, 2014
Igor Brigadir, Derek Greene, Pádraig CunninghamUCD
Motivation: Help Curate Liveblogs & Tweet collections
Motivation: Help Curate Liveblogs & Tweet collections
Motivation: Help Curate Liveblogs & Tweet collections
Tracking:
“Happening Right Now” Timelines: Newswire, Liveblogs.
“Retrospective Timelines” Timelines: Storify, Collections.
Breaking News on Twitter: Little context,
Lots of Duplicate & Near Duplicate information,
This -> RT @previous “Lots of #Duplicate & Near Duplicate #information”
Representations:
Distributional Semantics
“You shall know a word by the company it keeps”(Harris 1954; Firth, 1957)
Example: “swift”
Distributional Semantics:
“Society for Worldwide Interbank Financial Telecommunication”?
Bird? Car? Taylor?
“swift”
Distributional Semantics:
From June 2014, at
“Apple Worldwide Developers Conference”
...new programming language swift ... ... language its called swift ... ... language incoming swift developers kind of stunned #wwdc14...new programming language swift objective c without the translation...new programming language swift definitely a developers conferenceprogramming language called swift the developers are excited the ...programming language called swift #wwdc ... ... swift replaces objective c on apple ...
“swift”
Adaptive:Regularly update representationsSliding window over tweet stream
Timely, Meaningful Similarity
“Nakamoto Chase”
Term Frequency based Similarity: 0%Static, Distributional Semantic Similarity: 67%Adaptive, Distributional Semantic Similarity: 85%
Adaptive:
More via @MagicTimelines
Work with Insight: http://www.insight-centre.org/working-with-us
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