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news-please: A Generic News Crawler and Extractor

Authors: Felix Hamborg; Norman Meuschke; Corinna Breitinger; Bela Gipp;

news-please: A Generic News Crawler and Extractor

Abstract

The amount of news published and read online has increased tremendously in recent years, making news data an interesting resource for many research disciplines, such as the social sciences and linguistics. However, large scale collection of news data is cumbersome due to alack of generic tools for crawling and extracting such data. We present news-please, a generic, multi-language, open-source crawler and extractor for news that works out-of-the-box for a large variety of news websites. Our system allows crawling arbitrary news websites and extracting the major elements of news articles on those websites, i.e., title, lead paragraph, main content, publication date, author, and main image. Compared to existing tools, news-please features full website extraction requiring only the root URL.

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Keywords

scraper, news crawler, information extraction, news extractor

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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!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
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3
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47
35
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