\section{Dataset}

\subsection{Corpus}
\begin{frame}
	\frametitle{Corpus}
	\begin{itemize}
		\item For our study, we used the Webis-ArgRank2017 dataset by \cite{wachsmuth:2017a}.
		\item Webis-ArgRank2017 contains a ground-truth argument graph
		      as well as a benchmark for argument ranking
		\item The data was originally collected within the Argument-Web
	\end{itemize}
\end{frame}

\begin{frame}
	\frametitle{Corpus}
	\begin{itemize}
		\item In the resulting argument graph G = (A, E)
		      \begin{itemize}
			      \item Each node represents an argument $a_i \in A$ consisting of a conclusion
			            $c_i$ and a not-empty set of premises $P_i$ $\Rightarrow$ $a_i = \langle c_i, P_i \rangle$
			      \item An edge $(a_j, a_i)$ is given if the conclusion $a_j$ is used as a premise
			            of $a_i$
			      \item Consequently, $P_i = \{c_1,...,c_k\}, k \geq 1$
		      \end{itemize}
	\end{itemize}
	\begin{figure}
		\includegraphics[width=0.7\linewidth]{bilder/DatasetLocalView2.png}
		\caption{Part of the Argument-Web used to create Webis-ArgRank2017.}
	\end{figure}
\end{frame}


\subsection{Benchmark Argument Ranking}
\begin{frame}
	\frametitle{Benchmark Argument Ranking}
	\cite{wachsmuth:2017a} kept those arguments fulfilling:
	\begin{itemize}
		\item The conclusion was part in more than one argument
		\item Real claim
	\end{itemize}
	Additionally, an argument had to be:
	\begin{itemize}
		\item a valid counterargument
		\item based on reasonable premises
		\item logically consistent
	\end{itemize}
\end{frame}

\begin{frame}
	\frametitle{Benchmark Argument Ranking}
	\begin{itemize}
		\item The resulting benchmark dataset consist of 32 conclusions which
		      participated in 110 arguments
		\item Those 110 arguments were ranked by seven experts from computational
		      linguistics and information retrieval
		\item Each argument was ranked by how much each of its premises contributes to
		      the acceptance or rejection of the conclusion
	\end{itemize}
\end{frame}


\subsection{Evaluation Method}
\begin{frame}
	\frametitle{Evaluation Method}
	\begin{itemize}
		\item \cite{wachsmuth:2017a} used Kendall's $\tau \in [-1, 1]$ to evaluate the agreement between the experts and to ensure comparability
		\item The mean over all experts for the evaluation of the benchmark is $\tau \approx 0.36$
	\end{itemize}
\end{frame}