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:

Results, Examples: http://mlg.ucd.ie/timelines

More via @MagicTimelines

Work with Insight: http://www.insight-centre.org/working-with-us