We want and are asked by analysers for help them doing better their popularity recommending task, for further mediatic consensualisms
This post briefly exposes the flaws of not willing to develop bottom up categorization because of the overrelying in the top down machinery for that.
«Analytical Informatics are so advanced that we don’t need to care about designing further features and usabilities for open thessauruses» is an argument that is gaining popularity, while bictiopedia rather focuses in developing open semantical categorizations for bottom up inputs, aimed to further smooth top down analytics too.
Bottom up categorization is about the decentralization of content input types and platforms to gather so, while top down categorization is a final centralized platform itself that exposes the custom selected in a decentralized way and or the more broadly accepted categories from bottom up inputs in a more centralized way.
Regardless of the more or less we want to rely in the broad picture we tend to call society, or social norms, we have a constant need for resuming those. For that, we apply bipolar (fuzzy) logic and or (probabilistic) statistics to the biggest possible pools of data available. In a small level, we call it consciousness or shared beliefs to promote from our personal and or local experiences. At a bigger level, we have the law and mass media. So called social networks are something in the middle between the media and our more personal and local top down resumy mechanisms and platforms.
The social (top down) law is a macro pole of what a dictionary tries to top down in a more micro scale. Bictiopedia wants to be a middle tool for that, specialising in developing the bottom up inputs for those areas the more openly possible.
Top down analytics would get a pool of data, would make its semantical networks there with its tools and will produce results out of it (structure analisis andso could recommended complementary content to it). Every platform defines categories to add data to it more openly or less. The more open ones would follow open standards for data management, will implement usabilities for their users to be able to categorize more within it and will also inform them and let them use (and or block) a variety of analisers to recommended them some content or none. In the other side, there are platforms that want to make very unaccesible the how their final content recommendations are being done. They could use different strategies for doing so. Like everyone else, they have to give a open bottom up categories input model (their usability of seeable content types), which they combine it with open and more opaque metadata models used by their topdown analisers, in a platform centralization model that is open to everyone (facebook, twitter, etc) or a centralization that is not necessarily related to a certain platform but getting the most possible your browsing as a centralised platform itself (cookies, spiders for google ads, etc…).
It may look easier for an analiser to have the data more easily accesible through a centralized platform. But this bicitiopedia way bets for a more centralizing of open standards and more decentralizing of federations of them. If google crawlers can get and categorize those ammounts of data from different sources that could be very poorly categorized themselves, they (and others) could do better their job if the data is better categorized at the platforms they categorize on the top of them. Let’s make easier the job of a crawler for it to become a dictionary we really trust more than the actual dictionary (de)centralization models.
Analitical Informatics is the real name of Artificial Intelligence bloat
Thessaurus developments are marginated because an increasing many of us want to rely all semantics development or evolution (the core of linguistics, and subsequently from all sciences too) in top down analitical software that will tell to the very lazy idiots of us about the more meaningful links of the data we dump them without we needing to further estructure any bottom up inputs along.
This trend keeps endured with big data: The more data (bigger) we will dump to machines, the easier they will estructure it andso the lesser we will need to estructure it ourselves… . We can easily think that machinery that access faceboogle data for giving us data recommendations to consume, to be a higher inteligence than any of us because is capable of some semantical analizing much quicker than us and it does it in a much more richer pool.
Facebook bottom up data architecture input looks like a lot of categorized with profile fields, personal pages links, interests buttons, albums, tags for posts, lists with different groups of friends, favourite follows, different reactions to almost everything, many settings configurations… but some of these features don’t work (i.e. you can’t tune the posts it is going to display you… not all likes you give count the same for that and favourite follows is a fake feature) and there are other parts that are not categorized and could rather save a lot other more complex categorizations they implement. For example, you can categorize your posts with emojis and with quite useless tags (as and less useless in twitter) but not with profiles custom categories, tabs shown at your profile that could filter your different posts about that. These categories could be very useful for you allowing some of your friends to subscribe-follow (defaulty see your wall) to only some of your types of posts. But you can’t do that, you should create a new Page for any new specific content type category of yours if you want, which would not be very much shown to who you would like to.
This messy categorizing can look contradictory, but they consider this an optimal usability strategy to make people thirsty of fast data (as fast food). This specific deliberated uncategorizing of the more root part of it along a lot of other superfluos categorizing make us more desperate at willing to add and read data. So we become to choose a specialised subject to post about for not becoming too much of a hassle to our readers. People is not bothered about having 1000 different and varied friends and you can have pages about many of your varied arts, but you should be posting mostly about a single category of things you do to reply the simple phrase of «What is in your mind?», for others to follow you. People like many people but want to quickly categorize each.
Pages, Groups of friends and groups are featured, but very poorly, and that’s, along the poor search, it is done on purpose for giving you a fake corporate image of themselves being servicial to your feeling the platform customizable to you, when more in fact they don’t have this intention of enabling interactivity that could let us scale our personal walls up, choose the variety we want and enjoying a more customized experience overall. No, they want to guide you more to some sexy echo chambers for you through what is popularly called the algorithm.
That is not even bad at all, facebook has given a lot of joy and wisdom to many of us and it is the best friend of many people. But, as shown, this increasingly powerful top down analitical capacity wants us to bring it more equivalent loads of finer bottom up data to it anyway. The opaque content feeds management algorithm, the most centralized platform nowadays, could look very almighty, but it wants us more addicted not only to its interfaces, but to add content to them. We may be seeing more silently more videos, series or films, but we are still giving our phisiological signals when interacting with that, and surely we will still be likely to communicate those to others, maybe not that publickly to all in a wall, but defeinetely more to people through a chat, that looks more private to us, but that is just more precious data for the analisers that spy you in exchange of their comfortable service to you.
We could also have something better along, with more open and flexible categories and realer privacy, where such top down analitical machinery will also learn more neatly in, and would value it more because could get better phisiologies from us if we think we are more hidden from that, and for sure would more deliberately give a more clear emotion to whatever we decide to more publickly share. Bictiopedia wishes to display biometries of the adding of data through its standards, that surely analisers will find it very worthy. We should incentivate a race for analisers to reward us further when we follow their recommendations.
LAW: PRIVATE AND PUBLIC
Law is the analitical justification for the top down enforcement of violence.
Practices are being subject to change and to produce novel situations that may be disliked and so willing to de discouraged or forcedly stopping them to happen.
There is natural law which tends to be better identified as costitudinary law. There is personal law which tends to be named as private-contract law. These are the bottom up input types for categories of laws. These decentralized – bottom up law trends are the first ones in caring about integrating into formalities the new practices that are being considered informal, paralegal or else, which at some point they will influence the phrasing of more centralized top down laws.
Centralized laws and decentralized ones both rely in sets of values represented by keywords and dictionaries centralized definitions of them. Laws don’t look at wiktionary to do so, but they could be looking more to it, specially if wiktionary gets powered by a further decentralized thessaurus such as the one proposed by bictiopedia. Bictiopedia aims to serve for developing guidances for the bottom up side of lawing (costitudinary and personal-contract law) andso also facilitate the expression of underlying values for their rethorics.