Teasr

Creators post “teaser” videos showcasing concept ideas they have for longer productions like a podcast season or film that they want to generate support for.

When creating a post on Teasr, creators set a funding goal for their production that supporters can contribute towards by collecting the post on Lens for an amount of their choosing.

In case amazing video content isn’t enough to convince a potential supporter, Teasr also enables creators to come to launch a campaign with an existing social track record, by assigning them a reputation score derived from their Lens social graph.

Fans can discover and support creator campaigns on Teasr.xyz and view the creator’s reputation on the creator’s Teasr profile page.

TEASR REPUTATION PROTOCOL

The reputation algorithm we have developed solves a big problem by providing a flexible and scalable framework for analyzing and ranking content that can have a diverse variety of factors. We have verified the data from Lens data set improving their existing ranking mechanism as a proof of concept.

Weighted Score New Rank Handle 3.570191065 2 lensprotocol 3.873831021 1 stani.lens 0.83189664 9 aaveaave.lens 1.202529981 4 yoginth.lens 1.409861832 3 lenster.lens 0.853696275 8 bradorbradley.lens 0.557207446 15 wagmi.lens 1.037036669 5 christina.lens 0.394541736 22 sasicodes.lens 0.256179269 36 wassim.lens 0.34112894 26 tamrat.lens 0.234209709 40 davidev.lens 0.276220487 32 web3lover.lens ✔️ 0.220622028 42 mariariivari.lens 0.444282474 17 nelsonrodmar.lens ✔️ 0.300613979 29 phaver.lens 0.266375981 34 dydymoon.lens ✔️ 0.364858211 24 ufoclub.lens 0.405398009 20 thesmurfssociety.lens 0.254011998 38 levychain.lens 0.322607535 27 ameerna17958863.lens 0.542455702 16 justinsunset.lens 0.216015455 43 aavechan.lens 0.623525748 13 web3academy.lens 0.934115074 6 freedogecoin.lens 0.239779355 39 nohussle.lens ✔️ 0.165785778 50 guild.lens 0.15281569 53 t2world.lens 0.274550051 33 paris.lens 0.670599792 11 kingjunaid12.lens

The algorithm accomplishes this through several key features:

Normalization: By normalizing the data using few statistical steps, the algorithm first balances the all factors.

Weightage: It allows for the addition of weighted signals, giving greater importance to certain factors over others WITHOUT standard coefficients decided arbitrarily, rather by using an enforced ranking.

Segmentation Capabilities: The algorithm can work with multiple data inputs, even under the same factor, allowing for greater granularity and specificity in the analysis.

Infinitely Scalable/Flexible: The algorithm works with any number of dimensions, without rigidly confining the analysis to a set number of factors. Also, the signals can be added at any time to tune the further ranks without affecting previous snapshots or wildly moving away from older results.

Evolving Response: As more signals are added to the analysis, the algorithm fine-tunes its response, ensuring that the ranking of content remains up-to-date and relevant.

TEASR BACKEND

Custom graphQL API that imports the creator's Lens social graph to generate a reputation score using our reputation algorithm. Reputation score can be generated for any Lens profile before a post is made. Score is based on the users existing Lens history and future publication metrics for the Teasr post (the better the content the higher the score).

TEASR FRONTEND

Sign-in to Teasr triggers call to our backend API and Lens social graph for that user. When a creator logs-in to teasr.xyz their reputation score is generated and appears on their Teasr profile page.

Video upload and playback using Livepeer SDK and appears as a collectable post on Lens. We encountered issues with the Lens SDK which did not allow us to add the funding goal to the post’s metadata.