Our reputation engine calculates Reputation by Association for every Friend relationshipyou have. At the end of the month, the system increases or decreases your score based on the following calculation:
Reputation score = monthly positive MPXR of your friends normalized to 1 – summation of monthly negative MPXR of your friends normalized to 2
When you click ‘Follow’, you give one person a Follower state and another person the Follower state. Following is an asymmetrical relationship between user A and user B, where A is interested in the events of user B. Follower describes the inverse relationship, where user B has followers, including user A. As a result, the monthly reputation by association is calculated in two different ways for user A and user B.
Your monthly reputation for having Followers is calculated like this: the summation of the monthly reputation of all your followers normalized to 5. Each of your followers’ monthly reputation is calculated as: their monthly_rep × their MPXR normalized to 1. Hence, if you have followers, at the end of the month, your reputation by association score from that interaction will be calculated as summation[each follower’s monthly rep×MPXR normalized to 1] normalized to 5. A Follower’s monthly reputation is calculated as the summation of: [the monthly positive reputation points of the following user multiplied by the follower’s cumulative MPXR normalized to 1] + the summation of [the monthly negative reputation points of the following multiplied by the follower’s cumulative MPXR normalized to 2] .
Your network – directly and indirectly – affects your reputation score. We call this effect Reputation by Association. Your ‘association’ is 1) your friends, 2) the people you follow, and 3) the people who follow you.
The system considers how you interact with the content of people on your network. Why are you giving a thumbs-up review for a post? Is it because the content creator is your friend?
Any positive or negative reputation score you collect from the above process is calculated as Reputation by Association.
All user-interactions with the Mindplex platform have different ranges and base values. The system calculates your reputation score with a fairly complex algorithm, and one of the key factors in the calculation is the base value of the type of interaction.
Comment has the highest value while Follow has the lowest.
A user who comments on content gets the highest reward (among the interaction-types), while the Content Creator who gets a positive comment also gets the highest reward. The same is true for punishment; a content creator who comments badly (spamming, bullying, disinformation, racism, sexism and all the other evil -isms) will get the highest punishment while a content creator who gets the Best Negative comments also gets the highest level of punishment of the interaction-types.
Commenting is given more weight than other interactions because it is the interaction type which truly shows the user’s feelings, and the intensity of those feelings; yes, the user is literally telling us what they think about the content! Second, the user is spending more time and effort commenting than clicking ‘like’; first the user spends time reading/listening/watching the content, and then the user is concerned enough to write the comment.
Comments are also content. They enrich the platform for later readers. If you provide a thoughtful comment, you attract other users who interact with the comment: comment on the comment, like/dislike the comment, share the comment, react to the comment, and as well consume the comment. Hence, a user will get rewarded first for commenting, and then keep collecting rewards/punishments as other users’ interact with that comment.
In the first phase of Mindplex, comments will be read and sorted by humans (editorial team and moderators) before approval. In the long run, the process will be fully automated. Below is the range and explanation of quantifying comments:
This is a constructive comment and it teaches! Its conclusions are supported by arguments, additional references are added, and it tries to fill missing information. It can be a positive or negative sentiment.
It is, at least, a strong argument. It has supportive arguments for the conclusion of the comment. It can be a positive or negative sentiment.
Any comment that is not deemed either as a teaching or backed by strong argument. It can be a positive or negative sentiment.
The above is for comments that are good. However, there are bad comments! In Mindplex bad comments will not be published, they will have no effect on the content creator’s reputation score. If a user posted a bad comment, only the user will be punished; the punishment is a direct reduction of MPXR. Below is the description and quantification of bad comments:
Share has the second-highest value of the interaction-types. Sharing is where a user helps content break out from Mindplex onto other content sharing platforms.
Sharing also shows the user’s certainty and zeal: if a user is sharing content, then it shows how motivated the user is to spread the idea. Share is one of the two Interaction types without a negative value; it can’t lose you points, only gain you points as described here:
For sharing via more than one social media platform, or sharing to more than 3k followers
Shares on one platform and to less than 3k followers
Reaction is the interaction-type with the third-highest value. On Mindplex beta, Reaction is limited to emoji-reactions: in later versions we will introduce different sorts of reactions like posting a super short video (10-20 second).
A user can React using emojis, and emojis communicate feelings. The system will attribute positive and negative values to each of the emojis. It is valued higher than the Thumbs Up/Thumbs Down because emojis give more insight to the user’s feelings. Below are our selected Reaction emojis and their value:
I love it
I like it
The Thumb Review is in fourth place. This where you share your general feeling about the content with the ‘thumbs up’ or ‘thumbs down’ button.
Content Consumption (quantified and qualified by time spent) has the 5th highest value among the interaction types. Content Consumption by itself is an Interaction – it can boost your reputation and the reputation of the content creator. Moreover, this interaction-type affects the weight of all other interactions (Comment, Share, React, and The Thumb Review). If you Comment on a content or React with emojis before reaching the Best range on Content Consumption (described below), the weight of that Comment or that React is affected and you and the content creator only receive a partial reputation score as reward/punishment. If you interact before consuming the content at least half way, the system will see that as a shallow engagement. Quality interaction comes after consuming content not before!
Content Consumption has three ranges:
A user who finished the content or consumed ≥95%.
A user who finished the content or consumed ≥50% and <95%.
A user who finished the content or consumed ≥25% and <50%
Note: TheContent Consumption interaction is quantified bytime: our system measures how much time the user spent consuming the particular content. For an article and image, the time is estimated by the average reading/watching time allocated to the specific piece. For video and audio content, consumption time will count the exact duration of the audio/video content.
The reputation effect of Voting is dynamic, and depends on intensity, quality, and appropriateness measurements. The following parameters (among others) determine intensity, quality, and appropriateness for Voting:
At which point did you vote (First, Early, Middle, Late) and how your vote compares to the final vote-count on the piece. If you ‘like it before it is cool’, you earn rewards for that.
Total number of voters
Total number of votes
Your MPXR score when you voted
The amount of your MPX tip to the content creator used to back your MPXR and your vote (in the content factory)
Popularity of the subject
Likability of the subject (‘popularity’ and ‘likability’ are very different)
Let’s say you vote thumbs-down on a certain content request in the Content Factory. Let’s also say that the majority of the voters then also vote down, so that the end result is a net negative vote. The MPXR reward for your vote will then be weighted according to the 1st parameter (at which point did you vote), and the last two parameters (popularity and likability of the subject).
Now, let’s say our reputation system labeled your vote “late” (after you saw the majority result of the other voters and at the closing of the vote). Let’s also say our reputation system labeled the nature of the subject as “popular but unlikable”. Now your MPXR reward will be reduced for these two reasons.
The intensity and appropriateness measurements matter as well. Let’s also say you voted using 10 MPXR out of your 150. This confirms that you already know the vote is heading to the down vote and you are saving your MPXRs to get involved in other voting procedures and you are involved in this one just to fish reputation rewards.
Note: The above is just an example; the reputation AI calculates all the measurements and parameters and it will not be simple as our example.
Rating (out of 5 stars) works similarly to the ‘Thumb Review’ interaction. As mentioned above, this interaction is not included in the initial version of Mindplex. However, other websites using our system can activate it.
When one person follows or unfollows another, there is no immediate effect on either person’s reputation score. However, follower-count affects reputation scores via ‘Reputation by Association’ which is explained in detail here.
Friend Request and Follow are different on Mindplex. The Friend Request interaction has a static value and you will be rewarded twice: first when you send the request (the system will reward you only with positive reputation scores, there is no negative reputation score/punishment), and a second time after the request is accepted. Here, the reward can be positive reputation score or negative reputation score/punishment. Then just like the Follow interaction, this interaction will generate reputation scores in your Reputation by Association which is explained in detail here.
Do not send friend requests indiscriminately – your friends are people with whom you will build friendship! You can always choose the other interaction, Follow, if you want to be kept up to date on someone’s posting. Note: Third-party users of our tools can configure all of the above interaction values via the Mindplex Reputation Plugin. The values stated above are configured for the Mindplex magazine. Website administrators can reconfigure these values as suits their websites and their users. As for Mindplex – when we activate our governance portal, our community will vote on these values. We think comments should have the highest value and we have set the reputation plugin in accordance with this belief, but you can vote and change this! Welcome to the revolution that cannot be centralized!
Mindplex has a reputation calculator AI backed by an on-chain and off-chain data management system. This reputation engine calculates the value of users’ interactions with the platform and adds or subtracts reputation points accordingly. These reputation points are tracked by an on-chain token called MPXR.
Your off-chain reputation score changes instantly. This affects the number you see in your profile, and the weight of your interactions. The Mindplex Reputation Escrow will push this score onto the blockchain at a certain time interval by burning/minting MPXR tokens and transferring these tokens to your Ethereum wallet address linked. This MPXR cannot be transferred from your wallet or sold.
Let’s take a closer look at what we mean when we say that, MPXR is a non-tradable and non-transferable token. It means you cannot sell your reputation or you can’t buy another’s reputation! On the same note, you cannot delegate (even temporarily) your reputation to others nor can others delegate their reputation to you. You can only earn reputation scores based on merit, so please use it carefully because it is a powerful weapon that can reward and punish other users and content creators in addition to its significant weight in our governance procedures.
N.B. Initially (current smart contract), the token transfer time interval is every 30 days. Depending on the price of gas, the interval will be decreased or increased.
On Mindplex, both content consumers and content creators generate reputation points based on how they interact with the platform.
Every time you interact with the Mindplex, the effect of the interaction on your reputation score is calculated based on several factors. These factors include the weight of the interactor, among others described below.
Interactor: is a user who expresses their feedback via the selected interaction types: namely commenting, liking, sharing, reacting with emojis, or simply by spending time reading or listening to content.
Weight of Interactor: is the interactor’s existing reputation. This is represented by their MPXR token at the time of the interaction. If someone with a high reputation score ‘likes’ your content, that boosts your reputation more than if someone with a low score does.
Reputation can be added as a reward or subtracted as a punishment. As you interact with the platform and spread content that other members like, you will start to see your reputation go up. When this happens, you start to have more influence on the platform.
As a Mindplex user, you influence the reputation of the community members around you, and they in turn influence your reputation. If someone interacts with a comment you made (i.e. clicks like, reacts with emojis, etc.), then they influence your reputation. If you read an article and interact with it, you influence the writer’s score. The effect of your interaction will be calculated, and the content creator will get a reputation reward – thanks to you. At the same time the quality and intensity of your interaction will be calculated and you will receive a reputation reward because you are contributing and helping us maintain quality: you also receive reputation while you give.
The foundation of Mindplex’s reputation reward system is Interaction. Any time you interact with the platform, your reputation can go up or go down. You can interact with content, interact with other users, and interact by voting. There are two types of voting: voting in the content factory and voting in governance.
The beta version will include the following interactions:
Content Consumption (reading articles, listening to podcasts etc.) quantified and qualified via the time you spent as a consumer
Share (sharing comments on other platforms)
Reaction (using emoticons)
The Thumb Review (liking and disliking a content using the thumbs up and thumbs down feature)
Rating (out of 5 stars)
Friend Request (sending a friend request to other users)
Follow (following other users)
Voting (giving and receiving upvote or downvote in content factory or governance)
Note: We will update this page whenever we add new interaction types. Furthermore, from the above interactions The star-based rating interaction is not included on the beta version of Mindplex magazine. However, the interaction is active on our Reputation Plugin and other platforms that use the plugin can include this interaction type in their respective websites. Our reputation system will calculate reputation points for this interaction on such platforms. Voting in the content factory will be active very soon (when we integrate our Content Factory). Voting in governance will be active when we issue our utility token.
Each of the above interactions (except Share, and Content Consumption) have a Positive or Negative value.
Every interaction is quantified. There are also range, intensity, and accuracy measurements. As a result, reputation is calculated based on the consequences of these interactions. Our reputation engine will calculate the interactions and convert it to reputation points. Depending on the quality of the interaction, the reputation points can be positive or negative. Click here to see the value of each interaction.