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%!TEX root = ../presentation.tex
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\section{Theoretical Background}
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\section{Theoretical Background}
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\begin{frame}
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\frametitle{Why Twitter?}
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\begin{itemize}
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\item Reliable in previous studies \citep{Barbosa2010}
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\begin{itemize}
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\item Public opinion \citep{Oconnor2010a,Patodkar2016a}
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\item Stock market prediction \citep{Bollen2011a,Mittal2012a,Nguyen2015a,Pagolu2016a,Zhang2011a}
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\end{itemize}
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\item Short messages of up to 280 characters \citep{Rosen2017}
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\item One topic is assumed due limited characters \citep{Pagolu2016a,Patodkar2016a}
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\end{itemize}
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\end{frame}
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\note[itemize]{
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\item Page 11
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}
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\begin{frame}
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\frametitle{Sentiment Detection Algorithms}
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\begin{itemize}
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\item TextBlob
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\item Naive Bayes
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\item Maximum Entropy
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\item Support Vector Machine
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\end{itemize}
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\end{frame}
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\note[itemize]{
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\item TODO
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}

presentation-includes/03-chapter-casestudy.tex

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\end{frame}
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\note[itemize]{
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\item Table 3.1: Keywords/Brands, page 13-15
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\item Table 3.1: Keywords/Brands, page 13-15 (ranking in paranthesis)
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\begin{itemize}
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\item Ford
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\item Ford (5)
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\begin{itemize}
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\item Ford, Lincoln
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\end{itemize}
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\item GM
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\item GM (4)
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\begin{itemize}
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\item Baojun, Buick, Cadillac, Chevrolet, GMC, Holden, Jiefang, Wuling
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\end{itemize}
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\item Hyundai
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\item Hyundai (3)
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\begin{itemize}
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\item Hyundai, KIA
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\end{itemize}
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\item Toyota
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\item Toyota (1)
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\begin{itemize}
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\item Daihatsu, Lexus, Toyota
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\end{itemize}
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\item VW
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\item VW (2)
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\begin{itemize}
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\item Audi, Bentley, Bugatti, Lamborghini, Porsche, Seat, Škoda, Volkswagen
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\end{itemize}
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\item Table 3.2: Five Companies, page 15
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}
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\begin{frame}
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\frametitle{Stock Symbols}
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{\footnotesize
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\begin{table}
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\centering
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\begin{tabular}[c]{!l ^r ^l ^l}
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\hline
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\rowstyle{\bfseries}
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Company & \#cars\citep{OICA2016} & Market & Symbol \\ \hline
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\ford{} & 6,429,485 & New York & F \\
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\gm{} & 7,793,066 & New York & GM \\
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\hyundai{} & 7,889,538 & Korea & 005380.KS \\
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\toyota{} & 10,213,486 & Tokyo & 7203.T \\
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\vw{} & 10,126,281 & Frankfurt & VOW.F \\ \hline
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\end{tabular}
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\end{table}
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}
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\end{frame}
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\note[itemize]{
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\item Same as Table 3.2: Five Companies, page 15
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\item OICA = Organisation Internationale des Constructeurs d'Automobiles (engl. International Organization of Motor Vehicle Manufacturers)
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\item Daten von dem OICA corresponds survey 2016
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}
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\begin{frame}
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\frametitle{Gather Data}
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\note[itemize]{
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\item Why DMI-TCAT?: page 16/17
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\item Description of datasets beginning with page 24
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}
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}
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\begin{frame}
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\frametitle{Tweets}
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{\footnotesize
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\begin{table}
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\centering
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\begin{tabular}{!l ^r ^r}
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\hline
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\rowstyle{\bfseries}
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Company & \# captured tweets & \# English tweets \\ \hline
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\ford{} & \num{4518198} & \num{3745447} \\
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\gm{} & \num{575547} & \num{413817} \\
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\hyundai{} & \num{1895306} & \num{697221} \\
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\toyota{} & \num{915868} & \num{488913} \\
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\vw{} & \num{8244083} & \num{6219350} \\ \hline
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Total & \num{16149002} & \num{11565283} \\ \hline
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\end{tabular}
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\end{table}
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}
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\end{frame}

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