Inspire

Whrrl: Mobile Social Networking Using LBS, Reviews and Recommendations

A great new app for mobile social networking, LBS and recommendations in this post on Technology Review (MIT). I love Magitti even more than Whrrl as it is a more integrated and holistic way to give more relevant recommendations using social network analysis more elaborately.

Furthermore, the below quotes touch upon the importance of lifelogging using mobile phones as a way to authenticity, self awareness and filtering. In my view clearly the way forward, followed up by tight integration of key life goals and aspirations in the long run.

"The idea of community-generated reviews is, of course, not new. The popular recommendation service Yelp, for example, is already integrated into Google Maps. And the concept of locating friends using a mobile phone has also been around for years; Loopt, a service that runs on Sprint and Boost Mobile phones, is one of the most common examples. Whrrl, which can also be downloaded onto BlackBerry Pearl, Curve, and Nokia N95 smart phones, is commonly compared to both types of service. But it differs from either in that it combines aspects of both. In addition, Vengroff explains, Whrrl has collected details on establishments in 17 cities, which allows the service to provide fine-tuned local search, letting the user narrow down the hunt for, say, a café to one that has outdoor seating and vegetarian options and is recommended by at least one friend.

In the future, she suspects, location-based services will include more predictive features. For instance, instead of explicitly requiring you to write a review, the software might recognize how often you visit a restaurant and infer that it is a favorite. "Eventually, I think that a whole lot of exciting technology will emerge that figures out how to reduce the burden on the user," Choudhury says. "There will always be the case where user input will be important, but when we find the sweet spot, that's when I think it will take off."

A Search Engine for Virtual Worlds by Google and Linden Lab

Search within Virtual Worlds is reaching the next level in post from Technology Review on searching more effectively and socially within Second Life. Tagging is useful but fallable. Long term, objects in virtual worlds will in my view be recognized just like in (Mobile) Augmented Reality.

"In addition to being able to search for objects, residents can now look for information--about hobbies, for example--in each other's profiles. Dzwigalski says she expects that being able to search profile information will improve Second Life's social features.

Before Linden Lab announced its new tool, third-party companies, such as Electric Sheep, were working on their own to improve search in Second Life and other virtual worlds. "The search capability in the worlds has been historically quite basic," says Giff Constable, who leads the Electric Sheep's software business unit. Constable says that his company was sending bots into Second Life to pick up virtual objects and extract data from them in order to compile search results. "The analogy would be to Alta Vista in the early days of the Web, before Google came around and became able to rank things for popularity," Constable says. He adds that his company hopes to take advantage of the new search tool from Linden Lab and will focus on providing additional tools for social networking and e-commerce."

On Lifelogging, Co-Presence, Augmented Reality, Being John Malkovich and its Impact on eMarketing, Identity and Innovation

Some musings from my side on Lifelogging (storing and sharing all your life experiences digitally; all you see, hear, read, share, say etc.). Kevin Kelly and this post from Fast Company inspired me in this respect. People who are interested in reading more on this topic might look at the Metaverse Roadmap Report coming out this week.

My 2 cents why lifelogging will be on the rise:

• It is a logical extension of current trends like location based services (Plazes), social networking (MySpace), blogs (Typepad), RSS feeds, co-presence/microblogging (Twitter and Jaiku) and live webcasting (UStream and Justin.tv)
• It relates to software-based, bottom-up, automatically text-based, speech-based and video-based indexing solutions like Autonomy, Nuance and Blinkx respectively enabling the value and searchability of lifelogging
• Convergence of lifelogging and Augmented Reality applications like Steve Mann/MIT uses
• Convergence of lifelogging and virtual worlds like Second Life
• Convergence of lifelogging and the increasing importance of Transformation
  
• Convergence of lifelogging with the Semantic Web (Radar Networks and Metaweb). More structured, targeted and relevant RSS feeds will be integrated into our lifestreams
• It feeds on the popular movies called Being John Malkovich ("subscribe to a friend" in an extreme way) and Truman Show
• It relates strongly to the key emerging themes Identity, Creativity/Innovation and Authenticity. More in my previous, elaborate post on the interrelationships between these three concepts and how it fits with lifelogging. Lifelogging will only deepen the saliency and importance of these three concepts in the future and these concepts will feed the adoption of lifelogging. It is an interactive , self reinforcing relationship in my view.

In my view lifelogging will have a huge impact on the evolution of eMarketing and digital advertising. Why ? Because this will result on User Owned Data, the User will be the one in controlk permanently of their lifelogging data. This data is the most valuable marketing resource as it is complete, socially networked, actual, behavorial, contextual, personalized and deep. Access to this lifestream of users/customers will be rewarded, both in monetary and non-monetary ways. Attention, permission, trust and collective intelligence will be key themes in eMarketing going forward.

So what do you expect of lifelogging ? Will it become mainstream ? Why (not) ? When ?
Do you see other trends merging with the lifelogging trend ? Which ones ? What will be the impact on eMarketing or digital advertising ?

Web = Youniversity ; Fora.TV and Research Channel Complement TED, Edge, Google TechTalks and YouTube

We already have YouTube Science, TED, Edge and Google TechTalks (all of favorites of mine). That is a real blessing ! But now we also have Fora.TV and Research Channel. Thanks to Wall Street Journal for pointing these two out. Just great !

When will Joost (P2P on demand TV coming soon) integrate all of these videos while leveraging the social networking options, annotations, tags and other metadata (more in my earlier post on Joost) ?

Who needs a university or any other physical school ? The stuff available in these six (video) sites is just mind-boggling and growing every day.

Two questions remain:

• Is there any way in which we can reduce our sleep period ? ;-)
• How can integrate Nintendo Wii technology in these sites to guarantee our physical workout and reduce obesity ? ;-)

On Danny Hillis, eLearning, Freebase, Metaweb, Semantic Web and Web 3.0

A highly recommended and very long post from Edge on Danny Hillis and his view on the future evolution of the web with interesting comments from leading thinkers like Stewart Brand (GBN), Jaron Lanier, Douglas Rushkoff, Marc Hauser, Bruce Sterling (Wired, WorldChanging), Esther Dyson, Freeman Dyson and Howard Gardner. It touches many, many emergent web trends.

Semantic Web or Web 3.0 is about the World Wide Database instead of WWW. It is about structured, more machine readable data and information on the web. It is about advanced and accellerating eLearning, the next phase of the web after the current entertainment and community phase within Web 2.0. Focusing in factual and procedural knowledge. There are many interesting and current case studies integrating some aspects or technologies of the semantic web. Examples: FreeBase, Hakia, Radar Networks, MetaWeb, Joost and RealTravel. While I am not 100% sure about this at this moment, I do believe Google Base can be included in this space as well. It combines structured data with bottom-up, collective tagging systems.

What does this all mean ?
- Machine learning -> more outsourcing of (factual) tasks to bots and agents -> people will devote more time towards local low-end services, higher-level (symbolic) thinking and other human-specific skills/talents like soft skills (intuitive creativity, communicative/emotional/social skills). 
- Better search engine results/experiences -> higher productivity and more innovation
- More self-aware/correcting nature of online articles/posts dynamically integrating feedback loops on predictions in their texts. This allows for more easily deciphering the true nature of experts making future claims in their fields. This is a boost for reputational systems. Think more structured Wikipedia self regulation.
- Better data remixes/mash-ups -> higher productivity and more innovation
- Less impact of SEO (spam) tactics due to rise of structured and verified (!) data (formats) like PICS, Content Labels and microformats. The content of (commercial) websites will be indexed more authentically bringing back a better search engine experience for end users
- Deepens the impact, breadth and relevance of Mixed and Augmented Reality (AR) applications

Most importantly in my view is that a Knowledge Web has to take into account the mental, evolutionary state of the recipient as to be truly effective. Communication and learning is a two-way street. How does the Knowledge Web know about this mental state ? Through personalization ? Behavorial, contextual, profiled, social networked history ? Through emotional sensing ? MIT and DARPA (Pentagon) are working on these (recipient) items as well (Emotional Computing and Cognitive Augmentation).

"As useful as the Web is, it still falls far short of Alexander's tutor or even Vennavar Bush's Memex. For one thing, the Web knows very little about you (except maybe your credit card number). It has no model of how you learn, or what you do and do not know—or, for that matter, what it does and does not know. The information in the Web is disorganized, inconsistent, and often incorrect. Yet for all its faults, the Web is good enough to give us a hint of what is possible.

It is changing the way we learn. For example, one topic in the knowledge web might be Kepler's third law (that the square of a planet's orbital period is proportional to the cube of its distance from the sun). This concept would be connected to examples and demonstrations of the law, experiments showing that it is true, graphical and mathematical descriptions, stories about the history of its discovery, and explanations of the law in terms of other concepts. For instance, there might be a mathematical explanation of the law in terms of angular momentum, using calculus. Such an explanation might be perfect for a calculus-loving student who is familiar with angular momentum. Another student might prefer a picture or an interactive simulation. The database would contain information, presumably learned from experience, about which explanations would work well for which student. It would contain representations of many successful paths to understanding Kepler's law.

In retrospect the key idea in the "Aristotle" essay was this: if humans could contribute their knowledge to a database that could be read by computers, then the computers could present that knowledge to humans in the time, place and format that would be most useful to them.  The missing link to make the idea work was a universal database containing all human knowledge, represented in a form that could be accessed, filtered and interpreted by computers.

One might reasonably ask: Why isn't that database the Wikipedia or even the World Wide Web? The answer is that these depositories of knowledge are designed to be read directly by humans, not interpreted by computers. They confound the presentation of information with the information itself. The crucial difference of the knowledge web is that the information is represented in the database, while the presentation is generated dynamically. Like Neal Stephenson's storybook, the information is filtered, selected and presented according to the specific needs of the viewer.

Most search engines are about algorithms and statistics without structure, while databases have been solely about structure until now, Esther Dyson said."In the middle there is something that represents things as they are," she said. "Something that captures the relationships between things." That addition has long been a vision of researchers in artificial intelligence. "It's like a system for building the synapses for the global brain," said Tim O'Reilly."

On Branding = PR = Search = Wikipedia = Loss of Control ?

Modern marketing, branding and PR is more about how a company is ranked in different (blog) search engines, especially Google and Technorati due to their market share and impact. However, more and more searchers on the internet skip Google and Technorati alltogether and go directly to Wikipedia. Why ? Because Wikipedia is in most cases in the top 5 results of a search query anyway and so the searcher can be more efficient by going directly to Wikipedia as a starting point for discovery. And this is where very interesting (legal, philosophical and commercial) issues come to mind:

If Wikipedia becomes so fundamental to PR, branding and marketing, how can a company prevent and correct false statements from third parties when one can not afford an effective lawyer ? What is the impact of false statements - after being approved by the (social, cultural and technical) reputational systems of Wikipedia - on PR as the entries increasingly are distributed by means of RSS, SMS and/or e-mail ? Who is the real owner of Wikipedia entries ? Wikipedia, individual contributors, the topic item itself, none ? Is there a key difference in legal and non-legal claims ? What is acceptable diversity and what is unacceptable diversity of views ?

And how does this relate to the value and impact of tagging ? If people perceive and label you (collectively) one way but you see yourself in different (commercial) terms, how does this play out in terms of branding and PR ? Does this mean the advertising one-liner or positioning statements can be elusive or democratized ?

Can companies ultimately only accept the current policies of Wikipedia and tagging services and influence the Wikipedia results/pages and tagging effects by giving input themselves, albeit anonymously ?

Jimmy Wales talks about neutrality (NPOV policy; Neutral Point Of View) as a social (not legal !) concept and sharing the different views side by side when truth or objectivity can not be guaranteed. In the case above, this boils down to the situation that a false statement from a journalist in some media will be juxtaposed in a Wikipedia article with the 'correct' version(s) from the brand / company. As a result, this might dilute the brand value and equity. This is different from the situation in which there is a non-legal issue concerning a brand or company. This is about legal mistakes and the follow-up procedure within user generated content sites in general. This is about online identity and control. This is about the scope of your online identity. This is about BrandGossip, about BrandLies and about media relations. This is about the drawbacks of Digital Maoism as stated by Jaron Lanier in Edge.org in 2006. 

On Google Your Life, Total Recall and Creativity

This article from Fast Company shows us a very broad and deep overview of the topic of digitization of our lives (Flickr, YouTube, geotagging, blogs etc.). It is a great story about a.o. Gordon Bell, total recall, the sources of creativity and daydreaming, search engines, agents, LifeBrowser, MyLifeBits, SenseCam, FacetMap, DevonThink and Remembrance Agent. Strongly resonates with my postings on Augmented Reality and Steve Mann from MIT as a first cyborg. New concepts like Bliin might be a new way in this respect to present and organize the different LifeBits content on a global scale.

Recommended reading even though this article is quite long.

"This turns out to be the central question behind MyLifeBits: Yes, it's possible to store a lifetime of memories, but what do you do with them? To figure that out, I made a visit to Mary Czerwinski, a principal research scientist at Microsoft Research Labs whose team has developed "Facetmap," an audacious piece of software designed to visualize the contents of Bell's cybermemory.

When I meet the energetic, hyperverbal Czerwinski, she pulls me over to a massive 3-foot-by-3-foot LCD monitor on her office wall. On-screen there's a collection of colorful blobs representing different parts of Bell's life. There's a blob for people, another for calendar dates, and a bunch for different types of documents like email or Word files. She shows me how it works: If you click on any blob, it instantly expands to show you everything it contains. Click on the blob for "Jim Gemmell," Bell's main collaborator, and you'll see a blob containing all their email traffic, another with documents that mention Gemmell's name, and a third with events where he appears. The more data in each category, the bigger the blob, "so you can quickly see which area has had the most action," she notes. But the truly intriguing part about Facetmap is that it shows how Bell's information is connected."

Time-Based Tag Cloud: Evolution of Popular Words used by US Presidents

This one is special to me. It is about time-based tag cloud overviews on a particular topic. This link will give you an example using the popular words from US presidents. This evolutionary, dynamic view of a topic is so much more interesting than a static view. It gives clear insights into the relationship between particular personalites, economic circumstances and popular tags or words. E.g., I invite you to use the slider in the above link to look at the Reagan period.

Highly recommended. Looking forward to see time-based tag clouds in scientific journals/disciplines, song texts, movie texts, words during TV programs etc. etc.

Later on, I will elaborate on the strong and logical rise of time-based concepts and concepting in digital media in general ranging from evolutionary layered Google Earth/GeoWeb content, time-based e-mail capsules, DNA profiling to pre-eCommerce and much more...

Evaluation of Filters like Recommendations, Cross/Up Selling, Search and New Releases

A new insight from the blog The Long Tail in this post by Chris Anderson. My experience resonates strongly with the quote below. Recommendations are the best social filter in most cases leading to the highest satisfaction level. More about software-based, mobile and/or personal recommendations in my own musings on this topic.

"DVD renters are much happier with the DVDs they get from recommendations (which tend to be to older DVDs) as opposed to new releases, as shown by the following slide from a presentation that Netflix's Jim Bennett gave at the Recommenders06 conference in Bilbao last month.

Additionally, search, recommendations and other filters tend to drive demand down the tail, from the hits down to the niches where minority tastes are often better satisfied. Aside from happier customers, this also has some clear economics benefits for Netflix. It so happens that older titles, well down the Long Tail of time, are both cheaper to acquire and tend to get higher ratings than new titles (mostly because they've passed the test of time and have moved beyond the fog of hype that accompanies new releases). Not only that, but Netflix can also buy fewer of them, since as you go further down the curve the demand is spread out over more titles and there's less of a need to buy stacks of expensive new blockbusters to satisfy the rush of rentals requests around the release date."

The Future of Tags and Tag Clouds

Some fresh perspective on the future of tags and tag clouds. In summer of 1996 I saw a program on Dutch TV (VPRO) on a particular MIT initiative focusing on how concepts are processed by the brain and how this can be visualised using computers. This was an epiphany moment that has been materializing increasingly ever since. My realization was primarily that to boost user experience, creativity and user satisfaction to the maximum level, we need to emulate the exact brain processes in their respective software systems. Neuroscience driving usability. More in this post from Joe Lamantia, especially the control features related to tag clouds.

"To date, tag clouds have been applied to just a few kinds of focuses (links, photos, albums, blog posts are the more recognizable). In the future, expect to see specialized tag cloud implementations emerge for a tremendous variety of semantic fields and focuses: celebrities, cars, properties or homes for sale, hotels and travel destinations, products, sports teams, media of all types, political campaigns, financial markets, brands, etc.. In the first instance, tag clouds will continue to become recognizable and comprehensible to a greater share of users as they move down the novelty curve from nouveau to known. In step with this growing awareness and familiarity, tag cloud usage will become:

1. More frequent
2. More common
3. More specialized
4. More sophisticated

In the second instance, tag cloud structures and interactions will become more complex. Expect to see:

1. More support for cloud consumers to meet their needs for context
2. Refined presentation of the semantic fields underlying clouds
3. Attached controls or features and functionality that allow cloud consumers to directly change the context, content, and presentation of clouds

From a business viewpoint, these tag cloud implementations will aim to advance business ventures exploring the potential value of aggregating and exposing semantic fields for a variety of strategic purposes:

1. Creating new markets
2. Understanding or changing existing markets
3. Providing value-added services
4. Establishing communities of interest / need / activity
5. Aiding oversight and regulatory imperatives for transparency and accountability."