Truthy is a research project to study how memes spread on social media. A meme is a transmissible unit of information, such as a hashtag, phrase, or link.
This website highlights some of the research coming from this effort and showcases some visualizations, tools, and data resources demonstrating broader impacts of the project.
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More Tweets, More Votes


Truthy team members Karissa McKelvey and Johan Bollen collaborated with IU Department of Sociology members Joseph DiGrazia and Fabio Rojas on the paper More Tweets, More Votes: Social Media as a Quantitative Indicator of Political Behavior published in PLoS ONE. The paper aimed to see if the share of social media attention garnered by political candidates is significantly and reliably correlated with electoral performance. Their research suggests that indeed, holding other factors constant, candidates who received a larger share of attention on Twitter were more likely to win than their opponents.

Popular news outlets including Wall Street Journal, NPR and Washington Post picked up the story, many focusing in particular on potential ramifications the research will have on the current methods of political polling. More press links for this paper can be found at Karissa's website.

Let me try to simplify it into core concept points.

1) Algorithmic hiring via smart contracts: This means the shareholders define a "policy" and this "policy" has an objective which must be met in order for an entity matching the "attributes" to receive the "automatic votes" to be made a delegate.

2) Attributes: This includes the criteria that the policy is looking for. So if the criteria is referrals as part of a marketing smart contract then the contract will only say the attributes are met when and if they surpass a certain amount of referrals to win the votes as a reward.

3) Hired: This is what occurs whenever the attributes are reached and the terms of the contract are met. This means any random person could refer a bunch of people and the moment they pass the threshold within a specific time period (or unlimited time period) then they are approved by the contract. Once this happens the contract gives them all the automatic votes necessary to make them into a delegate.


I hope these concept points are enough to make it understood what I mean. The result of these ideas should be a system where we give out votes to smart contracts instead of delegates. The smart contracts would then give out votes to whichever delegates match our criteria and automatically fire those delegates by removing votes when they don't meet the terms of the contract.

Abstract

Information about user preferences plays a key role in automated decision making. In
many domains it is desirable to assess such preferences in a qualitative rather than quanti-
tative way. In this paper, we propose a qualitative graphical representation of preferences
that reflects conditional dependence and independence of preference statements under a
ceteris paribus (all else being equal) interpretation. Such a representation is often compact
and arguably quite natural in many circumstances. We provide a formal semantics for this
model, and describe how the structure of the network can be exploited in several inference
tasks, such as determining whether one outcome dominates (is preferred to) another, order-
ing a set outcomes according to the preference relation, and constructing the best outcome
subject to available evidence.

Preferences have been studied in philosophy, economics,
psychology, and computer science and have a wide range
of applications, such as e-commerce, recommender systems,
decision support systems, and control of automated systems.
A variety of methods have been proposed for modeling pref-
erences. The one that I consider here is that of conditional
preference networks (CP-nets). First studied by Boutilier et
al. (2004), CP-nets exploit the power of conditional ceteris
paribus preference rules to enable (in many cases) a compact
representation of human preferences.

Some voting procedures can be controlled by the authority conducting the elec-
tion (hereinafter, the chairman) to achieve strategic results. For example, it
might be possible to influence the outcome of an election by specifying the se-
quence in which alternatives will be considered, or by specifying the composition
of subcommittees that nominate candidates. We study whether the chairman
can easily or only with great difficulty determine how to control a specific elec-
tion, and conclude that voting procedures can differ significantly in the effort
1required to control them. This suggests that some voting procedures can be in-
herently resistant to abuse, while others are vulnerable. We base this distinction
on a measure that is new to voting theory—computational complexity.