Yimam, Seid Muhie and Ulrich, Heiner and Landesberger, Tatiana von and Rosenbach, Marcel and Regneri, Michaela and Panchenko, Alexander and Fahrer, Uli and Biemann, Chris and Ballweg, Kathrin (2016):
new/s/leak - Information Extraction and Visualization for Investigative Data Journalists.
The Association for Computational Linguistics, The 54th Annual Meeting of the Association for Computational Linguistics, Berlin, Germany, August 7–12, [Conference or Workshop Item]
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.
| Item Type: | Conference or Workshop Item |
|---|---|
| Erschienen: | 2016 |
| Creators: | Yimam, Seid Muhie and Ulrich, Heiner and Landesberger, Tatiana von and Rosenbach, Marcel and Regneri, Michaela and Panchenko, Alexander and Fahrer, Uli and Biemann, Chris and Ballweg, Kathrin |
| Title: | new/s/leak - Information Extraction and Visualization for Investigative Data Journalists |
| Language: | English |
| 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. |
| Publisher: | The Association for Computational Linguistics |
| Uncontrolled Keywords: | Forschungsgruppe Visual Search and Analysis (VISA), Information extraction, Information visualization |
| Divisions: | 20 Department of Computer Science 20 Department of Computer Science > Mathematical and Applied Visual Computing |
| Event Title: | The 54th Annual Meeting of the Association for Computational Linguistics |
| Event Location: | Berlin, Germany |
| Event Dates: | August 7–12 |
| Date Deposited: | 07 May 2019 08:42 |
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