Argument mining

Mining argument (also argument Mining ) is a research area within the Natural Language Processing ( natural language processing ). The aim is to automatically extract argumentation structures from natural language texts in order to be able to analyze them more closely with the help of computer programs. Arguments structures include B. Prerequisites, conclusions, the argumentation scheme, links between main and secondary argument or argument and counter-argument.

Argumentation mining is a continuation of text mining and should also be used to analyze big data .

Applications

Argumentation mining offers great potential to be used for the qualitative analysis of content from social media (e.g. Twitter ). Such analyzes offer e.g. B. political decision-makers or marketing departments new tools.

Argument mining is also being researched, e.g. B. in the field of legal documents, online debates of scientific literature and newspaper articles. Planned applications of argument mining include e.g. B. to improve information retrieval and information extraction or to present complex information summarized or visually.

Individual evidence

^ ^A ^b Marco Lippi and Paolo Torroni: Argumentation mining: State of the art and emerging trends In: ACM Trans. Internet Technol. 16, 2, Article 10, Mar. 2016. doi : 10.1145 / 2850417
↑ ^a ^b “3rd Workshop on Argument Mining”. Retrieved November 28, 2016
↑ Katarzyna Budzynska and Serena Villata: “Argumentation Mining, Tutorial.” http://www.i3s.unice.fr/~villata/tutorialIJCAI2016.html . Retrieved November 28, 2016

[Lippi_Torrini-1] A ^b Marco Lippi and Paolo Torroni: Argumentation mining: State of the art and emerging trends In: ACM Trans. Internet Technol. 16, 2, Article 10, Mar. 2016. doi : 10.1145 / 2850417

[3rd_Workshop-2] “3rd Workshop on Argument Mining”. Retrieved November 28, 2016

[Tutorial-3] Katarzyna Budzynska and Serena Villata: “Argumentation Mining, Tutorial.” http://www.i3s.unice.fr/~villata/tutorialIJCAI2016.html . Retrieved November 28, 2016