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Signal Briefings: Monitoring News Beyond the Brand

  • 2021
  • OriginalPaper
  • Chapter
Published in:
Authors
James Brill
Dyaa Albakour
José Esquivel
Udo Kruschwitz
Miguel Martinez
Jon Chamberlain
Published in
Advances in Information Retrieval
Publisher
Springer International Publishing

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Abstract

The chapter explores the challenges PR professionals face in monitoring news articles relevant to their organizations using traditional Boolean search methods. It introduces Signal Briefings, a system that leverages Natural Language Processing (NLP) to identify key entities and topics, reducing noise and enhancing the relevance of news articles. The system is designed to deliver up-to-date, impactful articles from a broad news space, addressing the need for efficient and effective media monitoring. The chapter describes the architecture and deployment of Signal Briefings, highlighting its clustering and ranking mechanisms to prioritize important articles. It also discusses the system's evaluation, demonstrating significant improvements in user engagement and technical performance compared to existing solutions. The conclusion emphasizes the value of Signal Briefings in enhancing PR professionals' ability to monitor large news spaces with limited resources.
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previous chapter repro_eval: A Python Interface to Reproducibility Measures of System-Oriented IR Experiments
next chapter Time-Matters: Temporal Unfolding of Texts
Title
Signal Briefings: Monitoring News Beyond the Brand
Authors
James Brill
Dyaa Albakour
José Esquivel
Udo Kruschwitz
Miguel Martinez
Jon Chamberlain
Copyright Year
2021
Book
Advances in Information Retrieval

Print ISBN: 978-3-030-72239-5

Electronic ISBN: 978-3-030-72240-1

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-72240-1_52
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