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% HIER DEN TITEL DER ARBEIT EINTRAGEN
\title{Argument Mining and Twitter}
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\author{Marc Feger M.Sc.}
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\date{\today}
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\institute{Heinrich-Heine-University Düsseldorf\\Institute of Computer Science\\
Department for Computer-Networks and Communication-Systems}
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\begin{document}
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\begin{frame}
\thispagestyle{empty}
\titlepage
\frametitle{Argument Mining and Twitter}
\end{frame}
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\section{Motivation}
\begin{frame}{Motivation}
\begin{itemize}
\item Online \textbf{Argumentation} daily on Twitter
\begin{itemize}
\item \textbf{Argumentation}: Usage of \textbf{Arguments}
\item \textbf{Arguments}: Motivated conclusions
\end{itemize}
\item Tweets vary strongly
\item How to find \textbf{argumentative} Tweets
\begin{itemize}
\item \textbf{Argumentive}: At least one \textbf{Argument} included
\end{itemize}
\end{itemize}
\end{frame}
\begin{frame}{Related Work}
\begin{itemize}
\item 10 paper according to \cite{schaefer2021}
\item Hardly any public data
\item Mostly \emph{SVM}, \emph{NB}, \emph{LR}, \emph{RF}, hardly any \emph{Transformer}
\end{itemize}
\end{frame}
\begin{frame}{Targets}
\begin{itemize}
\item [1] Collect and provide annotated Tweets in line with Twitter guidelines
\item [2] Find valid baselines
\item [3] Fine-tune \emph{BERT} or \emph{BERTweet} with \emph{classification-head}
\begin{itemize}
\item with MLM
\item with NSP
\end{itemize}
\end{itemize}
\end{frame}
\section{Data}
\begin{frame}{About the data}
\textbf{Argument}: $\langle c, P\rangle$
\textbf{Conclusion}: $c$
\textbf{Premises}: $P = \{p_1, ..., p_n | n \geq 1\}$
\begin{tcolorbox}[colback=cyan!5!white,colframe=cyan!75!black,title=Example:]
\textcolor{red}{RT} \textcolor{magenta}{@SaysSheToday}: The $[$Dixie Chicks$]_{c}$ were attacked just for $[$using 1A right$]_{p_1}$ to say they were ashamed of GWB. They $[$didn’t commit treason$]_{c}$ $[$like the \textcolor{orange}{\#47Senators}$]_{p_2}$
\end{tcolorbox}
\end{frame}
\begin{frame}{About the data}
\begin{center}
\begin{columns}
\column{0.5\textwidth}
\begin{itemize}
\item Twitter API v2
\item Graph-Database Neo4j
\item Thematic Reply Trees
\end{itemize}
\column{0.5\textwidth}
\includegraphics[scale=0.5]{bilder/ConversationStore}
\end{columns}
\end{center}
\end{frame}
\begin{frame}{\#abortion}
\begin{itemize}
\item Entrypoint: \url{https://api.twitter.com/2/tweets/search/all}
\item Parameter:
\begin{itemize}
\item start\_time: 2021-08-15T00:00:00.000Z
\item end\_time: 2021-10-16T00:00:01.000Z
\item query: (\#abortion) lang:en -is:reply -is:retweet -is:quote
\item tweet.fields: created\_at, public\_metrics, conversation\_id, entities, author\_id
\item max\_results: 500
\end{itemize}
\item [$\Rightarrow$] Real Root-Tweets
\end{itemize}
\end{frame}
\begin{frame}{\#abortion}
\begin{itemize}
\item Entrypoint: \url{https://api.twitter.com/2/tweets/search/all}
\item Parameter:
\begin{itemize}
\item start\_time: 2021-08-15T00:00:00.000Z
\item query: conversation\_id: $\langle$Root-Tweet-ID$\rangle$ lang:en
\end{itemize}
\item [$\Rightarrow$] Conversation-Tweets
\end{itemize}
\end{frame}
\begin{frame}{\#abortion}
\begin{itemize}
\item [1] 15.269 Root-Tweets
\item [2] 17.779 Conversation-Tweets
\begin{itemize}
\item [$\Rightarrow$] having 2.347 Root-Tweets
\end{itemize}
\end{itemize}
\end{frame}
\begin{frame}{\#abortion}
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\includegraphics[width=0.7\textwidth]{bilder/ExampleGraph}
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\includegraphics[width=\textwidth]{bilder/AbortionTimeline}
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\includegraphics[width=\textwidth]{bilder/AbortionWords}
\end{center}
\end{frame}
\begin{frame}{Argument Pre-Selection/Annotation}
\begin{center}
\begin{columns}
\column{0.5\textwidth}
\textbf{Pre-Selection:}
\begin{itemize}
\item Candidates:
\begin{itemize}
\item [1] Replies $\geq$ 10
\item [2] Text $\geq$ 200 characters
\item [3] The term \emph{for} in any word of text
\end{itemize}
\item [$\Rightarrow$] 28 candidates
\end{itemize}
\column{0.5\textwidth}
\textbf{Annotation:}
\begin{itemize}
\item 3 Annotators:
\begin{itemize}
\item 2 Computer Science, 1 Law
\item Annotation Schema Training
\end{itemize}
\item [$\Rightarrow$] 19 Selections ($~$67\%)
\item [$\Rightarrow$] 7 Uncertain (4 Deb., 3 Hidden)
\end{itemize}
\end{columns}
\end{center}
\end{frame}
\begin{frame}{Examples}
\begin{tcolorbox}[colback=cyan!5!white,colframe=cyan!75!black,title=Classic argument]
BREAKING: $[$U.S. Judge Robert Pitman has temporarily blocked \textcolor{orange}{\#SB8}$]_c$, the \textcolor{orange}{\#Texas} near-total \textcolor{orange}{\#abortion} ban in the case brought forth against TX by the DOJ, \textbf{saying} $[$the law is an "offensive deprivation" of women's constitutional rights$]_p$.
\end{tcolorbox}
\end{frame}
\begin{frame}{Examples}
\begin{tcolorbox}[colback=cyan!5!white,colframe=cyan!75!black,title=No argument]
\textcolor{orange}{\#BREAKING}: In United States v. Texas (challenging the constitutionality of \textcolor{orange}{\#SB8}), Judge Pitman has issued a preliminary injunction temporarily barring enforcement of the controversial six-week \textcolor{orange}{\#abortion} ban by "the State" — *including* judges and clerks:
\textcolor{blue}{https://t.co/U98yko04X3}
\end{tcolorbox}
\end{frame}
\begin{frame}{Examples}
\begin{tcolorbox}[colback=cyan!5!white,colframe=cyan!75!black,title=Obvious argument with progression]
$[$\textcolor{orange}{\#Catholic} social teaching urges us to provide a preferential option \textbf{for} the poor$]_p$. $[$\textbf{This means} prioritizing the well-being of the disadvantaged in society$]_{cp}$. $[$Access to legal \textcolor{orange}{\#abortion} \textbf{cannot be} considered outside the context of poverty \textbf{and without} the viewpoint of the poor$]_{c}$.
\end{tcolorbox}
\end{frame}
\section{Next Steps}
\begin{frame}{Next Steps}
\begin{itemize}
\item Preselection: Weak Labels + Annotation
\item ID-based reconstruction via API-V1
\end{itemize}
\end{frame}
\section{Possibilities}
\begin{frame}{Possibilities}
\begin{itemize}
\item Independence from external data providers
\item Question specific real world data generation
\begin{itemize}
\item User behavior on conversation data
\item Platform-shifted Comment Section for News-Paper
\item \dots
\end{itemize}
\end{itemize}
\end{frame}
\begin{frame}
\begin{center}
\begin{columns}
\column{0.7\textwidth}
\begin{center}
\huge {\color{hhuUniBlau} Thank you!}
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\includegraphics[scale=0.08]{bilder/pngfuel-answere.png}
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\end{center}
\end{frame}
\begin{frame}
\bibliographystyle{plainnat}
\bibliography{references}
\end{frame}
\end{document}
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