X-Git-Url: https://projects.mako.cc/source/state_of_wikimedia_research_2015/blobdiff_plain/841d41634e8da07a12dc770dd9b191a3de619589..5962c62847b1dd9bd0a07321f9775372bde402e1:/20150717-wikimania_research.tex?ds=inline

diff --git a/20150717-wikimania_research.tex b/20150717-wikimania_research.tex
index 2bf29df..54730ee 100644
--- a/20150717-wikimania_research.tex
+++ b/20150717-wikimania_research.tex
@@ -185,7 +185,7 @@
       {\spaceskip 0.3em%
         \fontsize{2.5em}{2.5em}
         \selectfont {\bf \color{makopurple4} The State of Wikimedia\\
-          Research: 2013-2014} \par}
+          Research: 2014-2015} \par}
 
       \vspace{1em}
 
@@ -307,6 +307,7 @@
   \item Represent \e{important themes} from Wikipedia in the last year.
   \item Research that is likely to be of \e{interest} to Wikimedians.
   \item Research by people who are \e{not at Wikimania}.
+  \item \ldots with a bias towards \e{peer-reviewed} publications 
   \end{itemize}
 
   \note{This is my disclaimer slide...
@@ -318,46 +319,75 @@
 \section{Paper Summaries}
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
-% \subsection{Event Prediction}
+\subsection{Content quality}
 
-% \begin{frame}
-%   \centertext{6em}{Event Prediction}
+\begin{frame}
+   \centertext{6em}{Content quality}
 
-%   \note{Mako
+   \note{Tilman
 
-%     This was the year that studies of readership of Wikipedia really
-%     blossomed. People figured out how to use the view data. Much of
-%     what they used it for was prediction.}
-% \end{frame}
+     A decade after the landmark "Nature" study, there still aren't too
+     many systematic evaluations of the accuracy of Wikipedia's content. 
+     Health articles continue to receive scrutiny, though. With good 
+     reason: Wikipedia is "the most frequently consulted online health 
+     care resource globally" [NEJM article].}
+\end{frame}
 
-% \begin{frame}
+\begin{frame}
   
-%   \frametitle{Wikipedia Viewership and Flu Prediction}
-
-%   \larger \larger McIver, David J., and John
-%   S. Brownstein. ``\e{Wikipedia Usage Estimates Prevalence of
-%     Influenza-Like Illness in the United States in Near Real-Time}.''
-%   PLoS Comput Biol 10, no. 4 (April 17, 2014):
-%   e1003581. \href{http://dx.doi.org/10.1371/journal.pcbi.1003581}{doi:10.1371/journal.pcbi.1003581}.
-
-% \end{frame}
-
-% \begin{frame}
+\frametitle{Quality of drug articles}
+
+   \larger \larger
+   Hwang et al., ``\e{Drug Safety in the Digital Age}.'' 
+   N Engl J Med 2014; 370:2460-2462 June 26, 2014 
+   \href{http://dx.doi.org/10.1056/NEJMp1401767}{doi: 10.1056/NEJMp1401767}.
+   \bigskip
+   
+   Kräenbring et al., \e{Accuracy and completeness of drug 
+   information in Wikipedia: a comparison with standard textbooks of 
+   pharmacology}. PLoS One 9 (9): e106930. 
+   \href{http://dx.doi.org/10.1371/journal.pone.0106930}
+   {doi:10.1371/journal.pone.0106930}
+   
+
+   \note{Tilman
+   
+     We selected two papers that evaluated drug articles, with 
+     different approaches. The first one is a short article in the 
+     extremely prestigious NEJM.}
+\end{frame}
 
-%   \frametitle{Wikipedia Viewership and Flu Prediction: Motivation}
+\begin{frame}
+  
+\frametitle{Quality of drug articles: NEJM}
 
-%   \begin{itemize}
-%     \larger \larger
-%   \item \e{Google Flu Trends} uses search engine queries to try to
-%     predict influenza epidemics more quickly than traditional methods.
-%   \item ..but it has been criticized as being biased (e.g., by media coverage).
-%   \item WP is freely available and viewership data is free, unlike
-%     Google which is proprietary.
+   \includegraphics[width=0.49\textwidth]{figures/Pradaxa_tweet_FDAMedWach.png}
+   % from https://twitter.com/FDAMedWatch/status/281547908095041536
+   % = first one in the list at http://www.nejm.org/doi/suppl/10.1056/NEJMp1401767/suppl_file/nejmp1401767_appendix.pdf
+   \includegraphics[width=0.49\textwidth]{figures/Dabitragan_Contraindications_WP_FDA_warning}
+  
+   \tikz{\node [yshift=1.5cm,xshift=-0.4cm] at (current page.center) {\includegraphics[width=1.5cm]{figures/long-arrow-right.png}};}
+   \begin{itemize}
+     \larger \larger
+     \item The US Food and Drug Administration (\e{FDA}) frequently 
+     issues safety warnings about prescription drugs. How long does it 
+     take until these are reflected on English Wikipedia?
+     \item 41\% updated within two weeks (58\% for high-prevalent 
+     diseases), but 36\% still unchanged after more than a year.
+   \end{itemize}
+   
+   \note{Tilman
+   
+   Articles about drugs used to treat high-prevalent diseases (affecting 
+   > 1 m Americans / year) were updated faster.\\ 
+   But the result still caused concern.\\
+   Authors find "there may be a benefit to enabling the FDA to update or 
+   automatically feed new safety communications to Wikipedia pages, as 
+   it does with WebMD". The paper raised awareness among WikiProject 
+   Medicine editors, but there's no systematic updating mechanism yet.}
 
-%   \end{itemize}
 
-%   \note{2009 H1N1 Swine Flu broke GFT.}
-% \end{frame}
+\end{frame}
 
 % \begin{frame}
 
@@ -398,8 +428,8 @@
 
   \begin{itemize}
     \larger \larger
-  \item \e{Wikimedia Research Newsletter} [[:meta:Research:Newsletter]]
-  \item \e{WikiSym} (Later this month in Berlin!)
+  \item \e{Wikimedia Research Newsletter} [[:meta:Research:Newsletter]] / @WikiResearch
+  \item \e{WikiSym/OpenSym} (This August in San Francisco!)
   \item \e{WikiPapers Repository} [http://wikipapers.referata.com]
   \item \e{Much More}
   \end{itemize}