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Analysing Protest-Related Tweets: An Evaluation of Techniques by the Open Source Intelligence Team

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Advances in Information and Communication (FICC 2024)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 920))

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Abstract

The police’s Open Source Intelligence (OSINT) team is constantly looking for better ways to analyze large corpora with high precision. This paper presents the evaluation by the OSINT team of more advanced methods than currently used to extract information from tweets related to an upcoming large-scale demonstration. An initial interview revealed the current way of working. Next, more advanced machine learning techniques such as sentiment analysis and network analysis are used to create visualizations that would better suit OSINT’s needs. Finally, our proposed visualizations are evaluated by two OSINT analysts who state that the results are clear, actionable, and relevant, whereas completeness of information and privacy pose additional challenges.

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Acknowledgments

This work was supported in part by the Dutch Police, who provided insights into their open-source intelligence work. Our gratitude goes especially to the OSINT team, who provided valuable insights into their activities.

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Authors and Affiliations

  1. Netherlands Police, Van Deventerlaan 50, 3528 AE, Utrecht, The Netherlands

    Laurens H. F. Müter

  2. Utrecht University, Nationaal Politielab AI, Leuvenlaan 4, 3584 CE, Utrecht, The Netherlands

    Laurens H. F. Müter & Remco C. Veltkamp

Authors
  1. Laurens H. F. Müter
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  2. Remco C. Veltkamp
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Correspondence to Laurens H. F. Müter .

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Editors and Affiliations

  1. Saga University, Saga, Japan

    Kohei Arai

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Müter, L.H.F., Veltkamp, R.C. (2024). Analysing Protest-Related Tweets: An Evaluation of Techniques by the Open Source Intelligence Team. In: Arai, K. (eds) Advances in Information and Communication. FICC 2024. Lecture Notes in Networks and Systems, vol 920. Springer, Cham. https://doi.org/10.1007/978-3-031-53963-3_5

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