Argument Mining: Manual and automatic
      annotation of short user-generated texts

                                   Manfred Stede

                     University of Potsdam, Potsdam, Germany
                               stede@uni-potsdam.de

    In the last few years, argument mining has emerged as a new field that aims
to identify argumentative portions in natural language text, and to uncover the
structure of the underlying arguments. Domains that have been addressed in-
clude legal text, student essays, and customer reviews (as a follow-up step to
sentiment analysis). In this talk, I suggest an annotation scheme for argumenta-
tion, and present results on automatic analysis of our argumentative microtext
corpus - a collection of 115 short texts that have been produced by students in
response to a trigger question, which usually bears the form “Should one (not)
do X ?” I give results from a joint-inference approach to this task, present various
extensions, and then discuss how the approach scales up to longer text.
Biography. Manfred Stede studied Computer Science and Linguistics at TU Berlin
and Edinburgh University, and received an M.Sc. in Computer Science from Purdue
University (USA). In 1996, he earned his Ph.D. at the University of Toronto with a
thesis on multilingual text generation. From 1995 to 2000, he worked at TU Berlin in
the large national “Verbmobil” project, which built a system for translating spoken lan-
guage between German, English, and Japanese. After a short interlude at a company
in Berlin, he became a professor in Applied Computational Linguistics at Potsdam
University in 2001. His research mainly revolves around issues of text structure, rang-
ing from theoretical models to its automatic analysis, with applications in, e.g., text
mining and summarization. Recently, a focus of his research is on different dimensions
of subjectivity in language, where speakers convey their attitudes, opinions, and argu-
ments. The well-known computational application is Sentiment Analysis, where Stede
contributed to a successful system implementing a lexicon-based approach for English.
As a follow-up step, he is now interested in Argument Mining, i.e., the automatic
discovery of authors claims, reasons supporting them, and possible objections.
    Stede published three monographs, fifteen journal papers, and numerous confer-
ence papers and book chapters. He directed research projects funded by various Ger-
man national agencies and the European Union, sometimes in collaboration with local
companies.