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\documentclass{acm_proc_article_sp}% http://www.acm.org/sigs/publications/acm_proc_article-sp.cls/view
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\title{Forever Blowing Bitcoins: Social Structure and Speculative Bubbles in Cryptocurrencies}

\numberofauthors{6} %  in this sample file, there are a *total*
% of EIGHT authors. SIX appear on the 'first-page' (for formatting
% reasons) and the remaining two appear in the \additionalauthors section.
%
\author{
% You can go ahead and credit any number of authors here,
% e.g. one 'row of three' or two rows (consisting of one row of three
% and a second row of one, two or three).
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% The command \alignauthor (no curly braces needed) should
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% e-mail address with \email.
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% 1st. author
\alignauthor
Nicolas Della Penna \titlenote{is a first co-author of this paper. He conceived the study, methodology, and wrote the initial manuscript and the notebook with the data analysis.}\\
       \affaddr{ANU}\\
       \email{n@nikete.com}
% 2nd. author
\alignauthor
Eaman Jahani\titlenote{is a first co-author of this paper. He wrote the forum scrapers, constructed networks and their measures, and wrote up the relevant sections in network data and variables.},  Peter Krafft\titlenote{helped with methodology and literature review} \\
       \affaddr{MIT}\\
        \email{eaman,pkrafft@mit.edu}
% 3rd. author
\alignauthor Octavio Bunge\titlenote{ wrote scrapers for coin prices, and the non-trivialness measure.}\\
       \affaddr{Universidad de Belgrano}\\
        \email{octavio.bunge@comunidad.ub.edu.ar}
\and  % use '\and' if you need 'another row' of author names
% 4th. author
\alignauthor 
Harper Reed\titlenote{helped with the writing and literature review}\\
%       \affaddr{Harper Rules LLC}\\
       \email{harper@nata2.org}
% 5th. author
\alignauthor Alex (Sandy) Pentland\titlenote{helped with methodology and writing}    \\
       \affaddr{MIT Media Lab}\\
       \email{sandy@media.mit.edu}
\alignauthor  Julian McAuley\titlenote{helped with methodology and writing}\\
       \affaddr{UC San Diego}\\
       \email{jmcauley@cse.ucsd.edu}
}
\begin{document}
\maketitle

\begin{abstract}

We study the power of structural features of the social network around cryptocurrencies to understand the severity of bubbles that occur in them. Our goal is to see whether bubbles in cryptocurrency markets can be predicted purely from structural features derived from the social networks that precede them. All our measures are constructed on the social network before the relevant cryptocurrency is ever traded. 

\end{abstract}



\input{intro.tex}
\input{lit.tex}
\input{data_nikete.tex}
\input{data_eaman.tex}
\input{data_otto.tex}
\input{variables_nikete.tex}
\input{variables_eaman.tex}
\input{method.tex}
\input{results.tex}
\input{tables/log_severity_forumAND.tex}
\input{tables/log_severity_forumOR.tex}
\input{tables/log_volume_forumAND.tex}
\input{tables/log_volume_forumOR.tex}

\input{limitations.tex}
\input{conclusion.tex}

%\input{tables/volume.tex}
%\input{tables/severity.tex}





\section{Acknowledgments}

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\bibliography{bubble}  % sigproc.bib is the name of the Bibliography in this case
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% latex bibtex latex latex
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%\balancecolumns
%\appendix
%Appendix A
%\section{Linear model coeficients}
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% That's all folks!
\end{document}