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Normalizing digital news-stories for preservation

Authors: Muzammil Khan 0001; Arif Ur Rahman; M. Daud Awan; Syed Mehtab Alam;

Normalizing digital news-stories for preservation

Abstract

Preserving news stories may be important because of various reasons like they provide detailed information about events and they may be used for research purposes in the long term. However, the news stories published online are in danger because of reasons like constant change in the technologies used to publish information and the formats for publication. Certain institutions or individuals may be interested in preserving news stories related to a particular event or topic. The stories should be collected from various online newspapers and preserved for the long term. The major issue in the preservation process is that newspapers use different formats for online publication of the stories. The paper presents a tool which is developed to addresses the issue. The tool facilitates users in the extraction of news stories from various online newspapers and migration to a normalized format.

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    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Top 10%
Top 10%
Average
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