% THIS IS SIGPROC-SP.TEX - VERSION 3.1
% WORKS WITH V3.2SP OF ACM_PROC_ARTICLE-SP.CLS
% APRIL 2009
%
% It is an example file showing how to use the 'acm_proc_article-sp.cls' V3.2SP
% LaTeX2e document class file for Conference Proceedings submissions.
% ----------------------------------------------------------------------------------------------------------------
% This .tex file (and associated .cls V3.2SP) *DOES NOT* produce:
%       1) The Permission Statement
%       2) The Conference (location) Info information
%       3) The Copyright Line with ACM data
%       4) Page numbering
% ---------------------------------------------------------------------------------------------------------------
% It is an example which *does* use the .bib file (from which the .bbl file
% is produced).
% REMEMBER HOWEVER: After having produced the .bbl file,
% and prior to final submission,
% you need to 'insert'  your .bbl file into your source .tex file so as to provide
% ONE 'self-contained' source file.
%
% Questions regarding SIGS should be sent to
% Adrienne Griscti ---> griscti@acm.org
%
% Questions/suggestions regarding the guidelines, .tex and .cls files, etc. to
% Gerald Murray ---> murray@hq.acm.org
%
% For tracking purposes - this is V3.1SP - APRIL 2009

\documentclass{acm_proc_article-sp}
\usepackage{graphicx}
\usepackage{subcaption}
\usepackage{booktabs}
\usepackage{color, colortbl}
\usepackage[utf8]{inputenc}
\usepackage{multirow}

\usepackage[usenames,dvipsnames]{xcolor}

\begin{document}

\title{Is Your Recommender System Amplifying or Dampening Filter Bubble? A User-Centric Approach}

% You need the command \numberofauthors to handle the 'placement
% and alignment' of the authors beneath the title.
%
% For aesthetic reasons, we recommend 'three authors at a time'
% i.e. three 'name/affiliation blocks' be placed beneath the title.
%
% NOTE: You are NOT restricted in how many 'rows' of
% "name/affiliations" may appear. We just ask that you restrict
% the number of 'columns' to three.
%
% Because of the available 'opening page real-estate'
% we ask you to refrain from putting more than six authors
% (two rows with three columns) beneath the article title.
% More than six makes the first-page appear very cluttered indeed.
%
% Use the \alignauthor commands to handle the names
% and affiliations for an 'aesthetic maximum' of six authors.
% Add names, affiliations, addresses for
% the seventh etc. author(s) as the argument for the
% \additionalauthors command.
% These 'additional authors' will be output/set for you
% without further effort on your part as the last section in
% the body of your article BEFORE References or any Appendices.

% \numberofauthors{8} %  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).
%
% The command \alignauthor (no curly braces needed) should
% precede each author name, affiliation/snail-mail address and
% e-mail address. Additionally, tag each line of
% affiliation/address with \affaddr, and tag the
% e-mail address with \email.
%
% 1st. author
% \alignauthor
% Ben Trovato\titlenote{Dr.~Trovato insisted his name be first.}\\
%        \affaddr{Institute for Clarity in Documentation}\\
%        \affaddr{1932 Wallamaloo Lane}\\
%        \affaddr{Wallamaloo, New Zealand}\\
%        \email{trovato@corporation.com}
% % 2nd. author
% \alignauthor
% G.K.M. Tobin\titlenote{The secretary disavows
% any knowledge of this author's actions.}\\
%        \affaddr{Institute for Clarity in Documentation}\\
%        \affaddr{P.O. Box 1212}\\
%        \affaddr{Dublin, Ohio 43017-6221}\\
%        \email{webmaster@marysville-ohio.com}
% % 3rd. author
% \alignauthor Lars Th{\o}rv{\"a}ld\titlenote{This author is the
% one who did all the really hard work.}\\
%        \affaddr{The Th{\o}rv{\"a}ld Group}\\
%        \affaddr{1 Th{\o}rv{\"a}ld Circle}\\
%        \affaddr{Hekla, Iceland}\\
%        \email{larst@affiliation.org}
% \and  % use '\and' if you need 'another row' of author names
% % 4th. author
% \alignauthor Lawrence P. Leipuner\\
%        \affaddr{Brookhaven Laboratories}\\
%        \affaddr{Brookhaven National Lab}\\
%        \affaddr{P.O. Box 5000}\\
%        \email{lleipuner@researchlabs.org}
% % 5th. author
% \alignauthor Sean Fogarty\\
%        \affaddr{NASA Ames Research Center}\\
%        \affaddr{Moffett Field}\\
%        \affaddr{California 94035}\\
%        \email{fogartys@amesres.org}
% % 6th. author
% \alignauthor Charles Palmer\\
%        \affaddr{Palmer Research Laboratories}\\
%        \affaddr{8600 Datapoint Drive}\\
%        \affaddr{San Antonio, Texas 78229}\\
%        \email{cpalmer@prl.com}
}



% There's nothing stopping you putting the seventh, eighth, etc.
% author on the opening page (as the 'third row') but we ask,
% for aesthetic reasons that you place these 'additional authors'
% in the \additional authors block, viz.


% \additionalauthors{Additional authors: John Smith (The Th{\o}rv{\"a}ld Group,
% email: {\texttt{jsmith@affiliation.org}}) and Julius P.~Kumquat
% (The Kumquat Consortium, email: {\texttt{jpkumquat@consortium.net}}).}
% \date{30 July 1999}


% Just remember to make sure that the TOTAL number of authors
% is the number that will appear on the first page PLUS the
% number that will appear in the \additionalauthors section.

\maketitle

%opening
\title{Content Consumption patterns: quantifying customization}
\author{}


\maketitle

\begin{abstract}

 Recommendation is the selection of useful information items from  an overwhelming  number of available items for the user to consume.  The main operationalization of recommendation is personalization, which is the tailoring of recommendations to the tastes and preferences of the user.  
% The two extreme ends of recommendation are 1) No-difference in the information that is made available to different users resulting in information overload, and 2) extreme personalization resulting in filter bubble. It is in the interest of the user and the information service provider (company) to alleviate information overload, but there is a concern that recommendation is creating a filter bubble effect,  a phenomenon  where society is balkanized along real or percieved lines of difference. The filter bubble is the  phenomenon that a  user is isolated from content that an algorithm decides as being not relevant to them. 
The fundamental assumption in personalization is that there are differences between users' information interests and preferences. Personalization is deemed in the interest of the user, in the absence of which, the user has to contend with all the available content, resulting in information overload. There is, however, a concern that personalized recommendation can result in filter bubble effects, where people end up being isolated from certain types of content outside of their interest sphere. An interesting question here when examining specific recommender systems is whether the difference in content served to distinct groups of users, is amplifying or weakening the potential bubble of the groups' distinct interests. 

%%%% << We here explore whether we can quantify to which extent the content served  difference between the distance between user groups in terms of their interests

%
%The below is not what you're actually doing - I would posit this in a different way, as I've done above.
%%For an informed criticism of personalized recommendation, it would be useful to be able to quantify it. How can we measure whether a system is doing extreme personalization resulting in filter bubble or no personalization resulting in information overload. 

In this study, we view personalization as having two components: 1) the separation of available content according to user interests, a sort of drawing imprecise borders between the users' preferences, and 2) the ranking of a particular user's information items. %As the  second is the classical ranking in information retrieval, 
We focus on the separation component of personalization and propose a method for measuring personalization as the ability to separate information items according to user preferences. 
The proposed method views personalization as the ability to maintain  the same distances (similarities) between the vectors of users' personalized recommendations as there is between the vectors of users' engagement histories.  We apply the method to two recommendation datasets, and show how it can be used to suggest improvements to  a system that does personalized recommendation. 
\end{abstract}


\input{intro}
\input{related}
\input{background}
\input{method}
\input{analysis}
\input{improve}
\input{conclusion}
\bibliographystyle{abbrv}
\bibliography{ref} 

\end{document}