Category Archives: Technology

The Influence of Homogeneity on Choice and the Web

Posted on by
2

One thing that consistently occurs in markets is a trend towards homogeneity, it’s nothing new, it’s been happening for millennia. The occurrence in the web is a bit disturbing, however, because of time and focus. Alas, I’m getting ahead of myself, I should probably talk about the various forms of homogeneity, that occur naturally and in our daily lives.

Homogeneity, in nature, it is as common as a step in the evolutionary process. As species adapt, the mean difference, across the whole corpus of the species, becomes smaller, and the species pick up both positives and negatives, that affect the species future. The huge negative for homogeneity is that the corpus, minus the mutated(outliers), is that susceptibility to a common tragedy. A tragedy, by contagion,  can be common, if a disease does infect one entity, it can easily spread to those that are also susceptible, though the entities with mutated genetics, assuming theses genetics, increase resistance or provide immunity to the disease, or any common tragedy.  If the tragedy is large enough, it can cause the mean difference to go up, or even hit an maxima,  which it comes back down from in favor of the  mutates.

Homogeneity, in business and our daily lives, occurs quite frequently, and it is an influencing factor over choice. To look into the idea of choice and homogeneity, you don’t have to look further than skin deep, or in this case clothing. Every one of us has a desire to fit in, and this desire results in us commonly grouping, even, subconsciously with those who are like us. From this desire, we find ways to look, sound, or interact the same way; our desire also has a side effect, it removes the necessity of thought in many circumstances, just go with what everyone else is doing. Of course, there will always be a few who don’t want to be classified, or collated with others, sadly they create their own group, through these actions: non-conformists.

To see the corporate side of homogeneity, look into the restaurant/fast food industry, or supermarkets. Mom & Pop’s have been gobbled up by the McDonalds and Wal-Marts , because the layperson doesn’t know what they have to offer. If you go with one of these household names, you have a good idea that the food is going to be decent, or that the store will have what you’re looking for within its doors. This homogeneity, decreases local competition, but it’s okay, because it saved the average consumer time and money, because these chains get reductions for ordering extremely large amounts of goods. Of course, some people will stick to the Mom & Pop’s, to be contrarian, or because they know it just as well and it has become ritual.

When it comes to the web, however, the steps toward homogeneity become much easier, but there is even fewer checks and balances, than in any of the other cases. We interact with the web on a time basis, and this time is limited, so we find a subset of sites to stay in constant contact with, normally staying within a triumvirate: search, networking, and news-history. However, the common solutions for these problems are reduced to a common set of sites, there are alternatives, but it requires more rigor on part of the consumer. So what do we do, we choose, by what provides the most tools, where are my friends, and how can I find out more.

What happens when you’re playing this zero-sum game of choice, Louis Gray says there is no zero-sum game?  You end up selecting those that might not be the best, but save you time and trouble. Want to use e-mail, read blogs, or just IM with friends, you can go use any random email host, any old RSS-reader, or link walk the sites, or anyone who offers an IM service, OR you can just use Google, and get all of these services simultaneously, plus several dozen other services.  Do you see what just happened? Multiple services where just reduced, they were hit by a common tragedy, and now there is one hyper-efficient service provider, which most people are going to use because it’s simple, and they don’t have to think about where they are going to go, or what they are going to do.  Where can I share images, discuss things with my close friends and family, and provide a set of personal information for people that people can use as entrance sources? Well there are a large number of services that will let you share images, and any number of places and ways to share that information, but to truly access everyone, without making them do work hard, and that site is becoming Facebook. The case is you don’t see a corresponding 1-1 gain loss, gains are primarily individualistic, while losses are primarily distributed, there are cases where the inverse occurs, but they are few and far between.

These companies are becoming goliaths, that are going to harm the web, if they continue to grow, it won’t happen immediately, but even now Facebook is trying to change the rules. And you can say all you want that there are other services out there, I’ll admit that, but when you’re playing a zero-sum game, based on how much time you spend interacting in different locations, you have to focus on where you’ll get the optimal return.  There will always be alternatives, for those who truly want them, but for the general public, they don’t mind as far as they know, everyone does the majority of the same things on the web. Until, something happens that causes the homogenous species, to see what the mutates have already seen and adapted for we’re looking at an interesting ride for the next 2-3 years.

Graph Attention Profiles – GAP(ML)

Posted on by
Reply

This was an idea I had earlier this morning about how to optimize social ad placement services, (MyLikes (Aff. Link), Magpie, etc. ) These services work by placing ads into the a social stream , I like MyLikes model, they let you decide what to put into the stream based on what you like, but this doesn’t factor in what your followers like, the ad needs to be relative to them, not you*. Thinking about how to determine the relevancy to a group, I came up with an idea based around averaging individual APMLs(Attention Profiling Mark-up Language).

I haven’t thought it out fully, it’s only been a few hours, but using APMLs as the starting ground. You sum the weights, per topic, for all of your followers and then divide by #number of followers, to get the APML for your Social Graph, per network which I’m calling GAP currently. I see this as an extended OPML format for APMLs , handling not only weights of relevant interest, but also handling access to the APMLs monitored by the graph.

One thing that would conflict with the APML format, which the GAP could stay very close to, is what is deemed Explicit Data. You aren’t the one determining relevancy, so it isn’t necessary. I’d either use or replace it for something that handles the APML list being monitored, the list becomes the explicit data for the weighting, but it also allows you to weight the APML’s individually as well, I don’t know that this is necessary, but it allows accessibility to possibly increase relevance to your graph, based on who is likely to interact more with you.

So this is just a thought, about a open-method for sharing graphs and relevance between services, rather than every service handling a proprietary model of the graph, and a proprietary model of relevant data. First things first, is that we need support for APML, which we have Chris Saad to thank for, then we can handle how we manage our networks relevancy.

One final issue with the GAP is that it has a specific use case, is that it is a way to share graphs and relevancy to exterior networks, but the file size for the GAP if it handled all the networks simultaneously it would become quite large, implicit data would be 1 line per topic, per network, and explicit data would be 1 line per person, per network. For early adopters and people with large following bases this could become quite large, even for a regular user on one network it would likely be 300-1000 lines.

*= MyLikes already uses a similar model, influenced by clicks per ad and number of ads you share. MyLikes Influence Rank

An Antithetical Post On How Narrowing Is The Key to Curated Data

Posted on by
2

So this whole thing about curation , has my head in a state, where I am seeing the data, meta-data, and users, as distinct entities in three-dimensional space. I’d love to provide an image of how they are related, but I can’t because when it comes to placing them in a 2-D or even 3-D state, there is warping and tunneling between these objects, outside of the third-dimension, to maintain proper relations.

Still here? Good. This post may be a bit vague, I’m going to try and keep it simple and understandable, for you as well as myself, I’m already a bit confused after several hours of trying to map this. If you would like to discuss this, for a more in depth, though possibly less coherent form, feel free.

To begin, we have three entities: data, meta-data, and users. These entities all have various ranges of relationship, which go from near to distant, and occasionally don’t exist. To describe the range as an example of friends, “Those best-friends, with very similar taste, are near(1), friends, much different taste(2), acquaintances, similar taste(3), acquaintances, different taste(4), and people you’ve never met(0).” We’ll approach range using this method, based on relational distance, between entities.

Data is, in my view, the front facing objects, whether that be text, images, video, or even tactile objects. Data itself exists in a weak presence, as far as to what value it represents, when coupled with meta-data, it becomes stronger.

Meta-data is data about data. It is the entity that is manipulated and understood, to provide us with relationship information, on any level. There are many forms of meta-data, temporal, location, authorship, topics, etc., that provide us with fantastic ways of connecting data, but often times it includes disparate entities, that aren’t necessary.

The user in my case is a human which interprets the regular data, and may create tags of meta-data, but can be a machine in which case it is likely to work with meta-data, either directly or in composition of meta-data from data sources.

Now that the entities are somewhat defined, I can get into the discussion of how these various entities are connected in creating relevant connections, both in basic terms, and user specific terms.

Often times, the simplest way to construct a relevancy map between data objects, is to use meta-data about the objects, social-bookmarking tools work this way by way of topical tagging, the distance between objects is the range of 4. Making the system a bit more complex you add methods, you take your tagged set, and add in user selection, by how much a user likes various items to manipulate what topics they are likely to see, this is in the range of 3 because it is still picking out items by topic which is a very wide. Or you can provide what your user’s friends have read recently, this is still in the range of 3, because by adding in what other people read, can narrow the area of focus, it’s possible to be in areas that the user doesn’t care as much for. If you add in what the user’s friends like, rather than just what they read, you get closer to the range of 2.

In order to get to the optimal range 1 you have to add two more things to your system: direct relations between data-objects and concentrated interaction between users, these can both be defined explicitly by users, and can be shown as a simple social-graph, with one object/user in the center, and the closest elements near by.  Direct-relations, which are somewhat like Techmeme, can be created on a broad scale by a user-based system of bundling links to content, based on relationship. Concentrated Interaction is a bit more complex, because it requires an analysis of interaction, but presents an interesting system, helps reach the range of 1.

Note: If you treat Users like data-objects, which they are in a database, you can apply meta-data, to make the concentrated interaction, more specific by what topics the user is most familiar.

So I’ve discussed 5 ways in varying levels of implementation to reduce the range of relevancy.

The use of tagging to create a quick reduction in the range of relevant data.
User selection to narrow down what topics the user likes, or aggregate content that the users friends are looking at.
Further narrow it down by what these friends like.
Allow Bundling of content that is directly related.
Analyze the concentrated interaction graph to narrow down trust sources.

I’m sure I’ve lost someone in this antithetical pile, as I had to get this off my head it was driving me crazy, and I’m going to call it the beginning of a new arcling, to be adjusted down the line. So if  you are interested, I’m sure that we can possibly make it a bit clearer by having a discussion.

The Future Of Privacy Is Full Publicy

Posted on by
9

Zuckerburg was right, “privacy was no longer a ‘social norm’,” being public is the new social norm, though most people will still tend to reject reality, even myself. I’ve finally gotten over about 90% of privacy issues, I might get upset by/at them, but even if there is something exposed, I’m preparing for it now. Anyone under the age of 21, within the US, who has ever used the internet has already lost their identity, so why should they worry, about what any company is exposing about them? It’s time to get over these feelings and accept the change that is coming, a ton of privacy isn’t worth an ounce of knowledgeable protection.

Just the other day, Facebook, proposed an update to their privacy policy to allow third-parties to have access to your data, some point in the future, and with this comes, yet, another wave of criticism, some. People are jumping all over Facebook, because they feel people will be paranoid that their data is vulnerable, and that their data shouldn’t be given out willie-nillie to just any third-party site that Facebook comes to agreement with. You would think people would be used to this type of position coming from Facebook, by now, this is their fourth or fifth slip up, but still people complain for a few months and then calm down, until it happens again.

Our most personal data in the US, social security numbers, is insecure, especially if you were born after 1988. The numbers can be defined through 2 data points, date & location of birth, and a little brute forcing. So for the younger generation, nothing is private, not even our government provided personal identification. If we aren’t protected in that regard, should we really be worried about those images from last weekend or who our friends are, what our opinions are? I think Eric Schmidt said it best, in an interview where he discussed privacy, “If you have something that you don’t want anyone to know, maybe you shouldn’t be doing it in the first place.”

I know I jumped on Facebook, but they aren’t the only sites that have huge inventories of data on their users, in hopes of adding relevancy, Google, Yahoo, Microsoft, et al. Facebook is the simplest site to jump on because of it’s repeated transgressions in the area. Google has faced it as well, though, when it didn’t take enough discretion in opening up their Gmail users privacy through Buzz. As the web keeps advancing, privacy options are going to be set to off on default, it will be up to the users to change the settings to keep themselves private, this has been called ‘publicy’.

Are you prepared for the next generation, the age of publicy? Are you ready to get dirty mucking around with settings to protect what little privacy, you will have in the future? Will you let everything go, and change how you interact on the web? These are questions that we will all face, but I think I’m prepared to be completely open in my environment when it comes to social matters, they aren’t anything compared to my financial information or my social security number, which can apparently be brute forced by a bot-net of 10,000 machines in ~1.27 seconds.

Update: Tyler Romeo’s latest post, Why I Dislike Facebook & Foursquare, makes a great point in contrast to the opinions I made here, I agree with quite a bit of what he has to say as far as respecting your users and offering secure protocols, to help protect your users. Take your time and go check that post out.

Social Geo-Location Is A Weak Medium

Posted on by
1

Earlier, I was watching an Iron Maiden concert and realized that any decent medium can be used to express a story or culture. Social Geo-location might be able to pass a story, but the majority of the usage I’ve seen, thus far, doesn’t. This is just one of a few issues that make social geo-location weak, there is the issue of user base, barrier to entry, and application of the data.

I feel that the location services aren’t proper for expressing the story. They don’t describe the why and what is happening the majority of the time, and when they do the data is extremely condensed to fit within the minuscule boxes of Twitter or SMS. Twitter is hard enough to express a story through, though you can still manage to get it or a cultural message across in one tweet. Sharing a cultural message through one of these locations is likely even harder, with the exception of religious establishments.

How social can you really be with these applications? These applications all have tiny user bases, even after quite a bit of promotion on large blogs and a period of time. Foursquare, which is one the most publicly discussed ones, only has half-a-million, even after breaking out at SxSW, last year. Compared to Foursquare, few of the other services come close in size comparisons. The problem with low user adoption is that without your friends, how relevant can the product be, which I’ll discuss a little later.

The barrier to entry for nearly all of these services, is that they are limited to internet enabled phones, or smart phones. In fact, only one service of the several that I’ve looked at, had a entry level that wasn’t quite restrictive of it’s base, and it’s none other than Foursquare, with SMS check-in’s, which still appears to be hit or miss. If you’re reducing your initial growth capabilities, immediately, in a social market, you’re damaging your product.

The services use the location data, in their own ways, but I don’t know if they are applying it where it would actually be of value, as an addition of context. If you can take the data from these products and connect it to events and people as they occur, you simplify the enrichment of the story. It’s still pretty easy to just say where the event’s took place, with the addition of maybe 2 dozen key strokes, as I write this at my house.

Another issue is that the product might not be relevant to users, especially, when people begin using them to check in as they leave. If I were to use these services, it would be to let my friends know where I am, so now you have users undermining the principles of your product, way to go. You’re app actually ends up being even more irrelevant than it already is. The likelihood that your friends are even on the service is an anomaly in the first place, unless you live in a metropolitan area(e.g. New York, San Francisco, LA, Portland, Miami, etc.).

I give all the people who work on these applications props, though, because they discovered a great system. They created a user-promotion based advertising system, which you encourage by having deals with various venues to reward the heavy users, and little trophies for reaching little milestones for the rest of the users. They have also brought the idea of geo-location to the fore, which sometime in the future will be used to add context to real stories or cultural messages. So I would like to thank all the people, who work on these apps, for their work, but you guys apparently don’t understand geo-location, it is better served to add context to other mediums, than as an independent social medium.