New/s/leak - Information extraction and visualization for investigative data journalists

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Abstract

We present new/s/leak, a novel tool developed for and with the help of journalists, which enables the automatic analysis and discovery of newsworthy stories from large textual datasets. We rely on different NLP preprocessing steps such named entity tagging, extraction of time expressions, entity networks, relations and metadata. The system features an intuitive web-based user interface based on network visualization combined with data exploring methods and various search and faceting mechanisms. We report the current state of the software and exemplify it with the WikiLeaks PlusD (Cablegate) data.

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APA

Yimam, S. M., Ulrich, H., Von Landesberger, T., Rosenbach, M., Regneri, M., Panchenko, A., … Ballweg, K. (2016). New/s/leak - Information extraction and visualization for investigative data journalists. In 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - System Demonstrations (pp. 163–168). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/p16-4028

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