preserving born-digital news panel jcdl 2016

Collecting, Analyzing, and Linking TV News and Social Media Collections

@mart1nkle1n#jcdl2016 Newark, NJ, 06/21/2016

Panel: Preserving Born-Digital News

Collecting, Analyzing, and Linking TV News and

Social Media Collections

Peter Broadwell@peterbroadwell

Martin Klein@mart1nkle1n

University of California Los AngelesResearch Library



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• Iranian Green Movement• Tahrir Square Unrest• Zanzibar Riots• Israel, South Africa, Argentina, Cuba, Armenia, Ukraine

International Digitizing Ephemera Project

http://digital.library.ucla.edu/dep/



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• Tahrir Square Egypt & Libya unrest, 2011• Tōhoku earthquake and tsunami, Japan, 2011• AirAsia 8501 crash, December 2014• Charlie Hebdo shooting, January 2015• GOP and Democratic Party presidential debates 2015/16

Collecting Social Media - Tweets



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• Tahrir Square Egypt & Libya unrest, 2011• Tōhoku earthquake and tsunami, Japan, 2011• AirAsia 8501 crash, December 2014• Charlie Hebdo shooting, January 2015• GOP and Democratic Party presidential debates 2015/16

Social Feed Managerhttp://social-feed-manager.readthedocs.org/

Collecting Social Media - Tweets



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Collecting TV News - NewsScape

• 289,174 hours of TV news archived digitally• Recorded 2005-present, ca. 145 shows/day• 46 networks, 13 countries, 9 languages• Searchable by captions, official transcripts, on-screen text• 3.55 billion words indexed



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Collecting TV News - NewsScape

• 289,174 hours of TV news archived digitally• Recorded 2005-present, ca. 145 shows/day• 46 networks, 13 countries, 9 languages• Searchable by captions, official transcripts, on-screen text• 3.55 billion words indexed



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Linking TV News and Social Media



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CNN09/16/201505:22pm



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CNN09/16/201505:22pm

Twitter09/16/2015

06:22pm



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Linking via Automated Entity Detection

• Discover and highlight commonalities and relationships between disjoint collections on related news events• Link to authorities• Address problem of disambiguation• Improve discoverability and reusability



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Experimental Exploration

• Apply DBpedia Spotlight Named Entity Recognition (NER) software to collections on second GOP presidential primary debate on 09/16/2015• Twitter: 800,000 tweets• TV: CNN coverage of debate• Minute granularity• Persons, Organizations, Places

Results:• Linked entities with URIs to DBpedia resources• Visualization of correlations between entities



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Persons

http://sologlo.library.ucla.edu/visualizations/gop_debate/rickshaw/graphs/gop_persons.html

Twitt

erN

ewsS

cape



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Places

http://sologlo.library.ucla.edu/visualizations/gop_debate/rickshaw/graphs/gop_places.html

Twitt

erN

ewsS

cape



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Persons

http://sologlo.library.ucla.edu/visualizations/gop_debate/rickshaw/graphs/gop_persons.html

Twitt

erN

ewsS

cape



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Organizations

http://sologlo.library.ucla.edu/visualizations/gop_debate/rickshaw/graphs/gop_orgs.html

Twitt

erN

ewsS

cape



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http://dbpedia.org/resource/Ronald_Reagan



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http://dbpedia.org/resource/Ronald_Reagan



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Hashtags

http://sologlo.library.ucla.edu/visualizations/gop_debate/rickshaw/graphs/gop_orgs_hashtags.html



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#DebateWithBernie

http://sologlo.library.ucla.edu/visualizations/gop_debate/rickshaw/graphs/gop_orgs_hashtags.html



Panel: Preserving Born-Digital News

Collecting, Analyzing, and Linking TV News and

Social Media Collections

Peter Broadwell@peterbroadwell

Martin Klein@mart1nkle1n

University of California Los AngelesResearch Library

preserving born-digital news panel jcdl 2016

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