Concept

Summary

Meta Mesh as the name implies is an artwork deployed using cellphones, which visualizes the rich semantic structure we all create when organizing the people we meet. Unlike the traditional mental maps, which remain locked away in the mind, Meta Mesh interweaves these highly personal maps into rich folksonomies, which develop virally as the artwork grows.

Explanation

Cellphones are implicitly associated with personal connectivity and therefore an appropriate choice as technical and conceptual platform from which to build Meta Mesh. The cellphone is synonymous with the term being connected; which means to be reachable from single point of contact, while affording ever increasing mobility. Much of technology today focuses on shortening the mental distance between people while elongating the physical one. However, when social interactions are in question, we are quite far from transcending the importance of physical distance. Meta Mesh addresses this dichotomy by creating a visual and experiential juxtaposition of a social network bounded with the physical proximity. It utilizes the nascent local proximity networks built into many cellphones.

Meta Mesh, extends the nascent ad-hoc networking to afford users the ability to store and retrieve succinct and oftentimes highly personal evaluations about others in their immediate physical space.Over time, a personal cellphone will become a unique record of what people think of the owner. In addition to storing the information, Meta Mesh also stores the link between the author and the subject so inferences may also be drawn about the writer too.

In technical terms, Meta Mesh is a folksonomic random network which enables its users to retrieve information about their local vicinity in the form of open-ended tags that categorize other local users. The tags assist users to grasp the nature of local vicinity both in terms of its familiarity and characterization. Familiarity information is provided by the user, whereas characterization is the aggregated knowledge contributed by all users. Meta Mesh, replicates these two affordances by allowing users to view previously tagged users (familiarity) and read collective tags appended to every user by every other user that they come in contact with (characterization).

The gathered data functions in two distinct ways, which we call "splitting" and "joining" modalities. The composition of many keywords onto one mental record affords our minds the ability to distinguish "split" one person from the next. Additionally, we can also collect "join" many users together into affinity groups based keywords.

Meta Mesh differs from its online counterparts by incorporating the requirement of physical encounter to enable tagging and viewing the tags. This key distinction has an important implication which can be summarized as bridging the virtual and physical identities of its users in online and physical environments. When a physical encounter is required to tag someone, it is natural to associate snippets of information along with a mental image of his/her physical likeness. Therefore, the tags in Meta Mesh will inevitably harness the mental image of the user to the appended information snippet.

The constraint of physical encounter also renders the deployment of Meta Mesh unique in that it links the geographical and social landscape. When a compatible device is tagged for the first time, it will receive an invitation to join the network.
The device owner will then be queried for permission to install the software. Starting from a single user, the software will spread through a process of socially interactive deployment.

Meta Mesh also allows users to indirectly traverse the network of associations (sometimes referred to as "friends of friends network") searching a user's network with one of the keywords that have been affixed to them. In this way Meta Mesh, works like an expert system. For example, if a user has a reputation for being a skilled artist, then searching that user's network for other people labeled with similar phrases would infer a validation of others' expertise.