web 2.0

The Coming Web 2.0 Dead Pool

Jerry Sheehan — Wed, 22 Oct 2008 10:29:48 -0700

Description

Yahoo's announcement of a 64 percent drop in third-quarter profits is a source of major concern for all Web 2.0 companies relying on online ad spending as their major source of revenue. Advertisers have already cut back in anticipation of the slowing economy, and in Yahoo's case this impact will cause 1500 employees to be laid off.[1]

Given our current economic predicament a number of technologists are beginning to ask what the ripple effect will be for Web 2.0 companies? Many of these entities, much like their .com dead pool brethren from 2001, are offering non-essential services with hard to articulate business models.

The boon days of the explosive growth of Internet advertising are over and will be replaced with either meager growth or flat budgets. As these resources disappear companies will be less likely to experiment with unproven brands. While this won't spell immediate problems for heavyweights such as MySpace and Facebook it likely will push lesser players out of the market.[2] Advertising Age perhaps gives the most relevant and succinct advise, "If advertising was your panacea, better think of something else and quick."[2]

What are the Likely Outcomes for Web 2.0?:
1) Web 2.0 Companies Get Focused On The Bottom Line: The slowdown will also have another ripple in the Web 2.0 as it will become increasingly difficult to get investment capital. Ron Conway, a prolific angel investor who has backed little startups like Google in the past, recently sent a letter to all of the companies he provides funding for telling them to reduce their burn rates and essential raise the next round of their funding through cost-cutting activities.[3]

2)Layoff 2.0: Those Web 2.0 companies already launched will struggle to keep their bottom-lines from becoming crimson and their first major efforts will result in a new round of technology layoffs. Prior to the announcement by Yahoo today, ClickZ had already tracked almost ~2,100 layoffs in the digital ad and marketing industry including companies as Zillow, eBay, Heavy, and AdBrite. Perhaps the most troubling component here will be the likelihood of multiple rounds of layoffs, already seen with sites such as Yahoo and Heavy.com

3)Web 2.0 DeadPool: Only fiscally strong or technologically relevant companies will survive the bursting of the Web 2.0 bubble. It is impossible to know which companies will succeed and fail in this regards, but interestingly a number of major "players" in Web 2.0 (Twitter, Pandora, Zillow) have been mentioned as likely dead pool candidates.[5]

Are there good things that may come out of bursting of Web 2.0? The answer is likely yes, a contracting market will force consolidation of offerings which is certainly needed in areas such as social networking. It will also be interesting to see if new opportunities for monetizing user created content arise as 2.0 companies get creative in finding new ways to raise revenue.

Computer & Information Science

Source

[1]"Yahoo Dims Outlook After Disappointing 3Q", Associated Press, October 21,2008, http://biz.yahoo.com/ap/081021/yahoo_outlook.html?.v=2
[2] "Woe to Web 2.0 Star-Ups: Too Few Ads to Go Around", Michael Learmonth, October 20, 2008, Advertising Age, http://adage.com/digital/article?article_id=131847
[3]"Is That the Sound of the Silicon Valley Web 2.0 Bubble Bursting", Rob Hof, October 9, 2008, BusinessWeek, http://www.businessweek.com/the_thread/techbeat/archives/2008/10/is_that_the_sou.html
[4]"Introducing ClickZ's Layoff Tracker for Digital Marketing Jobs", Zachary Rodgers, Oct 21, 2008, ClickZ, http://www.clickz.com/showPage.html?page=3631231
[5]"From Web 2.0 to DotBomb2.0", John Sheesley, October 14, 2008, TechRepublic, http://blogs.techrepublic.com.com/decisioncentral/?p=159

Social software and the spread of tacit knowledge in science

Alex Soojung-Kim Pang — Tue, 23 Sep 2008 15:40:45 -0700

Description

One of the more interesting discussions at the Perimeter Institute-sponsored conference Science in the 21st Century involved the role that Web 2.0 technologies could play in the dissemination of tacit knowledge in science.

Sociologist of science Harry Collins made the argument that there are three kinds of tacit knowledge that scientists share:

1) "Contingent tacit knowledge" is knowledge we don't talk about. There can be several reasons for this. We may not realize it's important, because it's enshrined in custom or everyday routines, and thus is never absent. We may not share it because we don't know for sure what others know or don't know. It may remain ambiguous because different groups have different meanings for common terms. Contingent tacit knowledge could be formalized and shared, but it's not.
2) "Somatic tacit knowledge" is physical knowledge. Riding a bicycle is the canonical example: describing all the physics of bicycle-riding doesn't make it possible for a novice to stay stable. (Surgery is another great example of a body of practice that has a strong intellectual component, but is also very physical.) You have to learn by doing.
3) "Collective tacit knowledge" is knowledge that you can only get by immersing yourself in a culture or society. As Collins put it, if riding a bicycle is somatic tacit knowledge, knowing how to ride a bicycle in traffic is collective tacit knowledge. The rules for successful riding are different in San Francisco, Copenhagen, and Mumbai: even if you're successful riding in one place, you can fail in the others.

All three of these forms of tacit knowledge, Collins argues, are important for the success of science. This suggests that there are some hard limits to the gains or transformational impacts of formal publishing efforts like arXiv. As Collins put it, "The Internet is really useful because we've already got all the socialization necessary to use it." Circulating papers more efficiently offers advantages to communities that are already connected, but is not going to be sufficient to build science in the developing world, or support the creation of new scientific communities.

What difference could Web 2.0 technologies-- in particular, social software, but also short-form video, web cams, and other relatively light media-- make for the transmission of tacit knowledge? We've tended to think of the Web's impact on science in terms of displacing publishing, or making the sharing of data easier; but social software tends not to be about moving around large bodies of formal knowledge, so much as facilitating the sharing of small amounts of knowledge, at highly specific times, and in particular contexts. In other words, social software edges toward tacit knowledge.

While more conventional kinds of publishing are useful for communicating formal knowledge, published results are the tip of the iceberg; most of science consists of informal and tacit knowledge, and it's that knowledge that defines and binds together communities of practice, specialties, and other functional groups within science. In the long run, then, it may be that social software is as significant as arXiv, or open publishing, or new modes of peer review, precisely because of its disorganized, informal, contextual nature.

Structure, Tools, and Platforms of Science

Source

Automatic recognition of chemical terms in free text

Andrew Walkingshaw — Fri, 02 May 2008 12:07:50 -0700

Description

Recently, ClearForest (a division of Reuters) launched OpenCalais - a web service which reads the news for you:

The Calais web service automatically attaches rich semantic metadata to the content you submit – in well under a second. Using natural language processing, machine learning and other methods, Calais categorizes and links your document with entities (people, places, organizations, etc.), facts (person ‘x’ works for company ‘y’), and events (person ‘z’ was appointed chairman of company ‘y’ on date ‘x’).

In other words, it annotates text and marks up four of the journalistic 5 Ws - who, what, where and when, hopefully making it easier for journalists to join the dots and supply the why and how.

This seems only tangentially relevant to chemistry, at first glance, but chemistry's in a sense just a special case - we want to pull the whats (chemicals) and the hows (experimental methods) out of free text - papers, theses, and journal articles. That means chemical named entity recognition, and conveniently:

Oscar3 is a system for chemical natural language processing, focussing on chemical named entity recognition.

The Royal Society of Chemistry use OSCAR3 to annotate journals as part of Project Prospect; it lets them build, automatically, a searchable index of molecular structures (and substructures) published in their journals.

So, in that, there's some overlap with what the service the Chemical Abstracts Service provides; but the CAS model is based on a small army of editors indexing papers by hand, and as such can only scale up so far. On the other hand, there's no reason OSCAR-like robot annotators, even if less accurate than the humans, can't be turned loose on much more - patent applications, university thesis repositories, scientific blogs, mainstream scientific journalism, or anywhere there's chemical text to be read. That has the potential to open up a lot of 'hidden', informal or otherwise unpublished research to chemically-meaningful indexing and search.

Future of chemistry

Source

http://opencalais.com/
http://en.wikipedia.org/wiki/5_Ws
http://oscar3-chem.sourceforge.net/
http://www.rsc.org/Publishing/Journals/ProjectProspect/
http://www.cas.org/
http://cb.openmolecules.net/

Social networks constructed by blog and SMS in China

Jess Hemerly — Tue, 05 Feb 2008 10:06:48 -0800

Description

From the blog post:

Blog was not invented in China, but it has been hugely popular in this country. Nowadays, almost everybody has a blog, presenting whatever he/she feels like to. Its users range from Nintendo DSL gamers to pop stars, and its hosts range from Windows Live Spaces to the Chinese native blog host www.bokee.com. And nonetheless, many of these hosts are reported to have attracted a large number of users.

This popularity can be probably attributed to the common Chinese character of being self-contained. Many Chinese prefer to keep their opinions to themselves rather than speaking out aloud. However, they do have a desire to share their experiences and knowledge, if the communications channel is right. Blogs are clearly one of those. Very often, the Chinese simply exchange their blog addresses, and then, when sitting back at home, they talk to each other over the blog. Blogs have obviously facilitated information flow and the construction of social networks in this country and particularly among the youth.

China: Science & Technology

Source

"Social networks constructed by blog and SMS in China." Xtract blog, November 14, 2007.

Post-semantic web enhances society and the meaning of data

David Gutelius — Sat, 24 Nov 2007 16:57:31 -0800

Description

In 1999, Tim Berners-Lee first described the semantic web in this way: " I have a dream for the Web [in which computers] become capable of analyzing all the data on the Web – the content, links, and transactions between people and computers. A ‘Semantic Web’, which should make this possible, has yet to emerge, but when it does, the day-to-day mechanisms of trade, bureaucracy and our daily lives will be handled by machines talking to machines. The ‘intelligent agents’ people have touted for ages will finally materialize."

Since that time, there has been significant progress towards making such an idea reality (note Radar Networks' Twine, or Metaweb's Freebase). It has also become more tightly constrained and defined (e.g. Wikipedia's current definition: "The Semantic Web is an evolving extension of the World Wide Web in which web content can be expressed not only in natural language, but also in a format that can be read and used by software agents, thus permitting them to find, share and integrate information more easily.").

Going beyond RDF-related technologies OWL and other ontology frameworks, however, we may be approaching a post-semantic web phase of development of the Internet. It's not that the "semantic web" as Tim B-L dreamed it or Wikipedia defines has really fully appeared. In fact, I have a suspicion that in either case, it may never appear and function the way its proponents envision. For one, there is still deep disagreement over standards - for all its Sematicness, the community can't even agree on the semantics!

By post-semantic web, I do not mean that it has become irrelevant - but it is beginning to show signs of turning out far differently than anyone could have imagined.

We are now seeing advanced machine learning combined with natural language processing, social graph analysis, and data mining techniques that half a decade ago few could have imagined. These technologies are being put to use by incredibly powerful compute resources (particularly those in mesh or p2p networks) to pick up and analyze a tremendous array of "signals". By signals, I mean not just those most in vogue in "web 2.0" like tags or networks of friends, although these are new and valuable sources for machines to learn to serve people more effectively. I also mean "digital gestures" - small signals that convey meaning to others but differently than "natural language" typically conveys; examples might include symbology or avatars. We are becoming more expressive digitally, and we are now just beginning to be able to also harvest these expressions and have machines learn from them in order to adapt to us.

The artificial intelligence field has for many years been fascinated with the idea of autonomous agents - semi-stupid digital servants that can act on our behalf under certain circumstances. The recent push into probabilistic reasoning and advances in a particular subfield of AI called machine learning (a characteristically poor name for a field of inquiry, but oh well) has begun to produce something better than semi-stupid in terms of serving us users.

The promise of a post-semantic web goes beyond just a language and representation framework (the techno-wonk vision of the semantic web) or a series of agents that do things for people. It's really a combination of 1) the power of distributed computing, 2) the growing expressivity of digital life and the signals such a life leaves behind, and 3) a way for software to learn and adapt itself to serve users and the human communities that they belong to, better. The implications for such powerful applications are not that they necessarily do things for us (although that would be a useful side effect), but rather give us new cognitive, and perhaps social, capabilities that let us do what we humans already do - just more and better.

AAAI Symposium on Social Information Processing - http://www.aaai.org/Symposia/Spring/sss08symposia.php#ss06

iLink KDD - http://www.ai.sri.com/pub_list/1523

Radar Networks' Twine: http://www.radarnetworks.com/

Metaweb - http://www.metaweb.com/

Signals

Radar Networks: Twine

Machine-to-Machine Intelligence (m2mi) Corporation

Social Information Processing