Visualization of the Topic Space of Argument Search Results in args.me
| Autor: | Henning Wachsmuth, Yamen Ajjour, Fan Fan, Bernd Fröhlich, Dora Kiesel, Patrick Riehmann, Rosemary Adejoh, Benno Stein, Giuliano Castiglia |
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| Rok vydání: | 2018 |
| Předmět: |
Information retrieval
Computer science Interface (Java) 02 engineering and technology Space (commercial competition) Visualization 03 medical and health sciences Search engine 0302 clinical medicine Ranking Argument 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Relevance (information retrieval) 030216 legal & forensic medicine Fake news |
| Zdroj: | EMNLP (Demonstration) |
| DOI: | 10.18653/v1/d18-2011 |
| Popis: | In times of fake news and alternative facts, pro and con arguments on controversial topics are of increasing importance. Recently, we presented args.me as the first search engine for arguments on the web. In its initial version, args.me ranked arguments solely by their relevance to a topic queried for, making it hard to learn about the diverse topical aspects covered by the search results. To tackle this shortcoming, we integrated a visualization interface for result exploration in args.me that provides an instant overview of the main aspects in a barycentric coordinate system. This topic space is generated ad-hoc from controversial issues on Wikipedia and argument-specific LDA models. In two case studies, we demonstrate how individual arguments can be found easily through interactions with the visualization, such as highlighting and filtering. |
| Databáze: | OpenAIRE |
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