First, I have analyzed the agency of the average YouTube user by setting up an ontology of content-controlling tools. From a software studies perspective, I showed in the first chapter how these tools affect the content and how they can be subdivided according to similarities and differences.
Flagging is the only user-controlled tool that can get content removed from the site. For the community to have control over what stays on the site and what has to go is the key point of interest for me to do this research. Therefore I will elaborate extensively on the flagging aspect of the model. By breaking down the regulation model of YouTube in three levels, I came to see how flagging is part of the overall strategy of YouTube. And in how far they rely on this coded aspect as a means to control the data.
“people experience these controls as nature. And that experience, I [ed. Lawrence Lessig] suggested, could weaken democratic resolve.” (Lessig, 2006, p. 138)
A textual analysis of the companies blog reveals not necessarily the technical aspects of the flagging system, but more the way YouTube wants to keep their regulation system as open and democratic as possible and how the company experiences the problems and solutions in the flagging system. This is followed up by a textual analysis of different videos addressing flagging on YouTube as an empirical test case, in order to get an insight on what the problems are as experienced by the user community.
To get a sense of how these problems are experienced, I follow this up with a case study that focuses on the problems that the Lesbian, Gay, Bi-sexual and Transgender (LGBT) community is faced with on YouTube and how they deal with this.
After that I compared the flagging system on YouTube with flagging systems of other platforms and systems that are alike these flagging systems; to see which problems can be avoided from within a flagging system and which problems remain.
Concluding with a look at hierarchical moderation systems and what the benefits and downsides would be when applied to the YouTube ontology. Amongst which is the increase of transparency in the decision making process and whether that is a good thing;
“to which extent should something be transparent; More particularly, where transparency would interfere with the function itself, then there’s a good argument against transparency.” (Lessig, 2006, p.141)
Followed by a proposal as to how a reputation system amongst flags and YouTube users would work in a similar way to Slashdot’s meta-moderation system.