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                               InfoTokens
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Simulates an open-content discourse community (e.g. a wiki).
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Author:      William Breathitt Gray
Date:        November 20, 2012
Version:     1.0
Copyright:   Simplified BSD License
 
Language:    C
Standard:    C99
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Copyright (c) 2012, William Breathitt Gray

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are
met:

1. Redistributions of source code must retain the above copyright
   notice, this list of conditions and the following disclaimer.

2. Redistributions in binary form must reproduce the above copyright
   notice, this list of conditions and the following disclaimer in the
   documentation and/or other materials provided with the distribution.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS
IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A
PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
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TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
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LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
========================================================================
========================================================================


-------------------
 Table of Contents
-------------------
I.      About
II.     Usage
III.    Output
IV.     Contact


----------
 I. About
----------
InfoTokens simulates the accumulation of information by a virtual
discourse community. Information is represented as tokens whose states
can be either true or false. Individuals in the virtual community can
add, delete, and change tokens. The accumulation of true and false
information -- due to the population's accuracy, rate of vandalism,
correction of vandalism, and population growth -- can then be studied
for trends.

I created InfoTokens to study how open-content communities such as
Wikipedia are able to produce reliable documents, despite having little
intervention in the selection of community members and external auditing
of the accuracy of the information accumulated; how could order come out
of such anarchy?

My hypothesis is that the amount of true information accrues at a faster
rate than the amount of false information; in general, I suspect that as
the population size increases, the percentage of false information
approaches zero as time passes. The only requirements I would add are
that the accuracy of population is more than 50%, and over half of the
population is sincerely attempting to maintain an accurate document.
Furthermore, I expect this trend to occur in both open-content and
closed-content communities.

The reasoning is rather simple: there is a buildup of true information
because the sincere individuals aim for such; similarly, false
information is actively removed by the sincere individuals, thus
creating a natural resistence to the accumulation of false information.
Following from this logic, an open-content community may produce more
reliable documents than a closed-content community because the
open-content community consists of more individuals (even if those
individuals are less accurate).

During my first year as a student at the University of Central Florida,
I had the opportunity in my English Composition class to write a
research paper on open-content discourse communities; I naturally used
this as an excuse to program InfoTokens. However, my initial attempt at
programming InfoTokens (infotokens-0.1) failed due to an overly complex
design and a deadline for my research paper. As such, I made up the
results attributed to InfoTokens in the conclusion of my research paper
and put the development of the program on hold until I would have enough
free time to finish it. The research I did for school is provided under
the "research" directory for the sake of completion, in the hopes that
it proves useful to someone.

Three years after my first attempt, I completed InfoTokens
(infotokens-1.0) with a more frugal design based on average effect
rather than random selections. After running the simulation several
times with different configurations, I discover that the accuracy of the
information produced by the population trends toward a limit.
This does not match with my hypothesis of an ever increasing accuracy,
nor with the real life examples of wikis. I suspect this limit is
arising due to the nature of the simulation: tokens accrue in set
intervals (by generation) rather than the decentralized nature of true
discourse. For now however, I leave the task of properly dissecting the
behavior of InfoTokens, and open-content communities in general, to
whomever decides to undertake it.


-----------
 II. Usage
-----------
To build from source, use the Makefile in the source root directory:

    # make

For more specific build instructions, refer to the INSTALL file in the
source root directory.

Execute the infotokens file to run the main program:

    # ./infotokens

InfoTokens will present several prompts for input to configure the
simulation.

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 III. Output
-------------
If the simulation was configured for file output, InfoTokens will output
the simulation data for each generation in the following format:

    Generation_Number True_Tokens False_Tokens Accuracy Population_Size

After the simulation ends, InfoTokens will output a summary line to the
the standard input in the following format:

    True_Tokens False_Tokens Accuracy Population_Size


-------------
 IV. Contact
-------------
Send bug reports, feature requests, and salutations to:

    vilhelm.gray@gmail.com

Feel free to send a message about anything you find interesting or if
you just want to talk. The life of a FOSS developer can get rather
lonely at times. :)