Maskinläsning [Elektronisk resurs] om massdigitalisering, digitala metoder och svensk dagspress
-
Jarlbrink, Johan (författare)
-
Snickars, Pelle (författare)
-
Colliander, Cristian (författare)
-
Umeå universitet Humanistiska fakulteten (utgivare)
-
Umeå universitet Umeå universitetsbibliotek (UB) (utgivare)
-
Umeå universitet Samhällsvetenskapliga fakulteten (utgivare)
- Göteborg Nordicom 2016
- Svenska.
-
Ingår i: Nordicom Information. - 0349-5949. ; 38:3, 27-40
-
Läs hela texten
-
Läs hela texten
-
Läs hela texten
Sammanfattning
Ämnesord
Stäng
- This article highlights the media historical possibilities to analyse linguistic patterns in massive amounts of texts using digital methods. Our starting point is the fact that The National Library of Sweden has made over 12 million newspaper pages available in digital format. An important question is how to research them. The article presents a media history of the Swedish newspaper digitisation, as well as new ways of conducting historical newspaper research using digital methods. A case study is presented where the conceptualisation of a new media technology (the internet) in newspapers from the 1990s is tracked with a digital tool searching for word co-occurrences. The possibilities of digital methods are often incredible, but we should not underestimate the problematic aspects of using digital tools to explore digitised newspapers. The poor quality of the OCR (Optical Character Recognition) is described as one of the major challenges facing historical newspaper research in a digital environment
Ämnesord
- Social Sciences (hsv)
- Media and Communications (hsv)
- Media Studies (hsv)
- Samhällsvetenskap (hsv)
- Medie- och kommunikationsvetenskap (hsv)
- Medievetenskap (hsv)
- Information Systems, Social aspects (hsv)
- Systemvetenskap, informationssystem och informatik med samhällsvetenskaplig inriktning (hsv)
- medie- och kommunikationsvetenskap (umu)
- medie- och kommunikationsvetenskap (umu)
Indexterm och SAB-rubrik
- media history
- digitized newspapers
- OCR
- digital humanities
- text analysis
Inställningar
Hjälp
Beståndsinformation saknas