Our Resource of the Month for August is International Newsstream Collection

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Each month, one of our Subject Librarians chooses an electronic resource which they feel will be of interest to you.

John Southall (Bodleian Data Librarian and Subject Consultant for Economics and Sociology) sat beside a computer in the Social Science Library. Book shelves are in the background.

August’s Resource of the Month has been selected by John Southall, Bodleian Data Librarian and Subject Consultant for Economics and Sociology.

John’s choice, the International Newsstream Collection from ProQuest is a powerful database providing access to thousands of news sources from around the world.

Overview

The International Newsstream Collection brings together news content from across Europe, Asia, Africa, Latin America, the Middle East, Australia, and New Zealand (North America is not included). The collection includes more than 1,700 print, digital, and broadcast news sources, with archives stretching back to the 1980s, making it an invaluable resource for both current affairs and historical research.

The collection offers access to:

  • Authoritative, full-text journalism from trusted publishers
  • Global perspectives on the same event, helping compare how issues are framed in different countries
  • Historical coverage, showing how stories and debates have evolved over time
  • Advanced search tools, including searching by publication, country, date, subject, or keyword
  • Integrated citation and export features, making it easy to save articles and reference them in your work

International Newsstream provides full-text access to major international newspapers and news providers, including; The Guardian, The Times, Le Monde, China Daily, The Australian, Straits Times, Times of India and Al-Ahram.

Text Mining Capability

A particular strength is its integration with ProQuest TDM Studio which supports text and data mining (TDM), allowing researchers to undertake systematic downloading of large news corpora and application of computational techniques such as sentiment analysis, topic modelling, and other forms of large-scale textual analysis.

A Subject & Research Guide has been published to support this and other resources, as well as outline the principles of Text and Data Mining.

Where can you access the resource

This resource can be accessed via SOLO.

A Single-Sign-On (SSO) is required to access this database remotely, as it is restricted to Oxford University students and staff members.

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