Archive for the ‘Argumentation Mining’ Category

Argument Interchange

Sunday, January 8th, 2012

Argument Interchange

From the post:

A first glimpse of how AIF is supporting interchange on the Argument Web

Prototype development on infrastructure and basic tools has reached the point where we can get a first glimpse of how the Argument Web will support a wide range of argument-related practice online. The video shows how different argument analysis tools can interact with each other, and how tools for analysis can work in harmony with tools for argument authoring and debate.

All the software is currently available, and going through some final testing before release. Later on in January, we will open access to the AIF database, and the first set of import/export filters. Then in February, we will release a public beta of the first practical Argument Web tool: FireBack, a Firefox plugin for argublogging. Tools for debate, analysis and automated computation will then follow later in the Spring.

I must admit to being curious what “argublogging” looks like. I suspect it will have a remarkable resemblance to what we call “flame wars” on email discussion lists.

Jack Park, who forwarded this link, assures me that there are other forms of argumentation, sometimes using the term “dialogue.” I don’t doubt that to be true, but how common it is in fact? I have my doubts.

If I were to watch any of the political “debates” for the U.S. presidential election, I would assure Jack that “debates” they were not. Incivility, lying, false factual claims, non-responsiveness, all with the goal of saying what they came to say, would be a better characterization. And that is from just reading the newspaper accounts. (Easier to skim and so not to waste time on being mis-informed by the candidates.) A Magic 8-Ball would be a better source of answers for public policy.

Argumentation mining

Friday, May 6th, 2011

Argumentation mining by Raquel Mochales and Marie-Francine Moens, Artificial Intelligence and Law Volume 19, Number 1, 1-22, DOI: 10.1007/s10506-010-9104-x.


Argumentation mining aims to automatically detect, classify and structure argumentation in text. Therefore, argumentation mining is an important part of a complete argumentation analyisis, i.e. understanding the content of serial arguments, their linguistic structure, the relationship between the preceding and following arguments, recognizing the underlying conceptual beliefs, and understanding within the comprehensive coherence of the specific topic. We present different methods to aid argumentation mining, starting with plain argumentation detection and moving forward to a more structural analysis of the detected argumentation. Different state-of-the-art techniques on machine learning and context free grammars are applied to solve the challenges of argumentation mining. We also highlight fundamental questions found during our research and analyse different issues for future research on argumentation mining.

I mention this for two reasons.

First, a close friend of mine thinks tracking argumentation is a way to guide diverse audiences into useful discussions about globally important issues. On the other hand, I have observed as few as seven or eight committee members be unable to find a common place for a lunch break. Perhaps some decisions are harder than others. ­čśë

Second, and perhaps more pragmatically, I think identification of arguments in texts are an important part of textual analysis, from a scholarly perspective. Any tool that can play the role of assistant in that task, is of interest to me.