After signing up (free), you can start creating your “traps” for content, based on a keyword, or series of keywords, or URL. Trap.it’s AI goes to work immediately, prompting you first to give a thumbs up or thumbs reaction to the content it initially delivers from over 50,000 original content sources on the Internet. By the fifth or sixth time you give input on the content you see, the software goes to work, refining the search results to fill your trap. You’re essentially training Trap.it to understand what you need and want.

Trap.it refines each of your traps based on both your explicit input and implicit actions, such as content you delete, to deliver the most relevant content based on your needs and tastes. You can set up as many traps as you’d like, based on everything from broad categories to extremely niche and specific information. Each trap contains a rich ontology that is unique to you, not a rehash of search results culled from other people.

You can consume your traps in three main ways:

1. A tile view where each article found is presented within a “cube” with an image and either summary text or a short excerpt of the content.
2. A list view that will be more familiar to you if you like to consume RSS feeds in a reader;
3. A page-by-page view where you can click on left or right arrows placed on either side of an article you’ve accessed to allow browsing of your trap content.

At the top of each article is the Trap.it navigation, where you can give thumbs up or down as well as save the article using the Read Later button which creates a reading list in a similar manner to Instapaper. Each trap you create can be shared publicly on Twitter or Facebook as well as shared privately by emailing a short URL generated automatically by the site.

Trap.it has worked hard to make the site and the presentation of content approachable and deceptively simple, but the technology behind the interface is sophisticated, robust and scalable.

From a work standpoint, Trap.it can distill and filter vast amounts of content produced daily on the Web into a highly targeted and constantly refined set of traps that you can access any time so you don’t just get the same old articles and posts you see retweeted in your Twitterstream. The folks at Trap.it hope you use their site for more than just professional work or research but for personal passions as well, from gardening to cooking to travel.

You can set up an account with Trap.it using Facebook Connect or Twitter OAuth, or manually by using this invite link (good for 500 new users).

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So what does that actually mean? The site presents a montage of images, video, animations and other visual resources culled from search results, and overlays it with real-time narration, using text-to-speech technology. The result is information as a watchable experience.

For me, the actual experience of watching the content is eerie and unsettling. I’ve never liked the way text-to-speech technology sounds; it’s strange and unnerving to my ears and brain, sounding almost, but not quite, human in a way that could mean trouble, like HAL in 2001: A Space Odyssey.

My first search was for “Tok,” the rural Alaskan community where I live and work. The text-to-speech voice sounded nearly human, but with mispronunciations and odd inflections that are inherent in the technology. Qwiki pronounced my community as “Tawk” rather than the correct pronunciation, “Toke.” Right away, this interfered with my ability to appreciate the visual montage.

The audio was accompanied by a flowing stream of imagery that seemed at first to correspond with the narration. But on closer examination, many images had nothing to do with what was being said, other than being from Tok. For example, when the narration mentioned Tok School, the images that appeared were of a gift shop and an RV park. Another image of a burned-out old gas station showed up, and I immediately wondered how I could remove such a photo, and replace it with something more representative of the community. Ditto for an image of a coffee shack that isn’t even in Tok, but is over 200 miles away, near the community of Glennallen.

My second search was for “karaoke.” I found the experience of this information less off-putting. However, the images in the presentation, while colorful and interesting, seemed less familiar. Many turned out to be of displays and equipment common in Japan.

My third search was for “social media.” The narration was a bit convoluted and the visual presentation consisted of a single static screenshot of Flickr.

My final test search was for…me. Here’s what I found (login required). And here’s what it looked like–apparently I have one of the dirtiest minds in business–or at least that’s what was displayed during the entire presentation!

Qwiki may give us a new phrase to replace “Googling ourselves.” We can now “get a Qwiki” and “give a Qwiki.”

Currently, Qwiki covers over two million reference terms, which feels sufficient for pretty good results when searching for a not-too-uncommon term. You can also search for people and places.

For me, the visual and audio dissonance of Qwiki was initially disturbing, but I tried to look past that and appreciate that I was “experiencing information.” Presentations are short–about 30 seconds–which is just enough time for narrative content from a paragraph or two from a Wikipedia entry.

Conceptually, Qwiki is a fascinating step forward in the presentation and consumption of search results. Since the site is in its alpha phase, it’s available only by invitation, although you can request one at Qwiki’s website. You’ll probably start itching to fix what isn’t working, but Qwiki doesn’t yet have a Wikipedia-like system for collaborating on editing information. However, the company is very open to input on ways to improve the experience.

Give Qwiki a try, and let me know what you think of it. What implications do you think it will have for the future of search?

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ReSearch.ly’s premise is that “search is a social act which relies on trust and community.” Developed by the folks behind PeopleBrowsr, ReSearch.ly creates “instant communities” around the things you publish, respond to, or search while you use Twitter. Your searches become “sharable objects” and the site purports to add context to your searches by providing additional related information–all from tweets on Twitter.

The site provides what they refer to as “degrees” of access to, and filtering of, information:

1. Geo Search. This is a local or regional search of the Twitter community that can increase relevant results, such as places to go for an evening out.
2. Local Trending Retweets. By seeing what others are retweeting, you can see what’s popular, and immediately participate in conversations of interest.
3. Your Community Search. You can search your Twitter stream for specific niche communities, and filter out less relevant conversations.
4. Search Within Search: You can drill deeper within a particular search by, for example, adding geo-searching to a topic-based community search.
5. Degrees of Separation. This is an analysis of your web of networks: who is connected to you and to other Twitter users.
6. Related Search. This allows you to enhance your search by providing other relevant information such as related hashtags, links or @ references.
7. Share Your Search. You can share your search, and make the way you are compiling and experiencing information into a social activity.

The premise of ReSearch.ly seems reasonable and potentially useful: When you search for tweets, you’ll be able to get more context to the content of interest. For a first-time user, the reality may be a bit confusing.

I tested the site by searching for “Napa” because I’m going to Napa Valley soon. By viewing search results through the Global filter, I quickly learned that “napa” is a word in Indonesian. But when I narrowed down results to my Twitter community (my followers or people I’m following), I begin to see much more relevance: reviews of Napa wines, mentions of Napa hotels, and tweets about Napa Valley events. I was able to narrow results to only male or only female Twitterers, only positive or only negative tweets, or only retweets. I could also click on the United States tab to get a broader view of who was tweeting “Napa.”

When I hovered over a person’s tweet, a “Degrees of Separation” link appeared. Clicking on that link showed the path between me and that particular Twitterer–how I might be connected to that user and, by extrapolation, how much I might be able to trust him or her. Based on the information I discovered, I could opt to follow individual Twitterers.

Search results also included charts showing global use of “napa” in the past 7 and 30 days. I could view the “Sentiment” for the word, and its popularity. I could also see words surrounding the original search term, such as “valley” and “wine,” but also “napas” and other words in Indonesian. Below that, I could see the most tweeted links where Napa was mentioned, related hashtags including #wine and #loveindonesia, and @ names referenced in tweets mentioning “napa.”

After that, there were images of pictures and videos where “napa” was mentioned, including wine-related images, plus random images where I couldn’t discern the context. They could have shown up because “napa” has other meanings internationally. A quick tweet to my followers revealed it’s short for “kanapa,” meaning “why.” So I learned something, but not directly from ReSearch.ly.

I’m all for slicing and dicing search results in new ways. At first blush, I found the results from ReSearch.ly to be curious. But ReSearch.ly is billed as a social search platform for “online marketers, brand managers and social media experts” that provides demographic data, psychographics, and instant viral analytics, along with location, gender, and retweets. I saw the location, gender and retweets data, but I didn’t immediately see how the information would help me as an online marketer, brand manager or social media expert.

I did another search for “SXSW” and the results were more relevant, most likely because SXSW is a much more distinctive term. The breakdown of the search results, however, didn’t seem particularly useful. Then again, I was searching not as a marketer or social media expert, just as someone thinking about attending the SXSW 2011 Interactive conference. I did discover when adding “Interactive” to the search that there are SXSW Interactive events in other cities happening in January. Now that’s interesting.

In conclusion, the service is complex enough that users may need more help from the company. You’ll need to decide whether the value of ReSearch.ly’s “social search” goes beyond mere curiosity by adding social pathways and context to search results.

What are some of your experiences with “social search” so far?

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The Search

My search was for my work: I’m doing some content strategy work for a client at the moment and I’d been wondering about the latest developments in the field.

First up, I entered “content strategy” into Google, without the quotes, and got over 45 million results. The top results were an A List Apart article from 2008, then Wikipedia, then a bunch of articles on the sites of people who sell content strategy services. Interesting results that Google turned up that I didn’t find elsewhere was a Google Knol on content strategy, as well as a link to a content strategy interest group from the Society for Technical Communication. This last result, in particular, was interesting from an academic and current discipline-based perspective.

Meanwhile, a search on Twitter turned up an similarly endless list of results. There was a lot of replication and retweeting, sure, but the first page of results presented an article published that day about an approach to setting content strategy. The retweeting gave the effect of reputation — multiple retweets of the same resource created the impression that the article was a good one, and worth looking at.

That first page of results also produced a more specific A List Apart article from March of this year on the usability and strategic purpose of FAQs. The results also informed me of a content strategy meetup that I didn’t know existed and provided anecdotal information on the importance of content strategy in product and service adoption. Of course, as I scrolled through the results, they kept being updated with further relevant tweets, in real time.

As you’d expect, Delicious provided a range of handy article-based results. Where both Google and Twitter had thrown up some articles designed merely to promote agencies and businesses in the content strategy arena, Delicious seemed to have more educationally focused results. Again, the number of bookmarks for each article implied a sort of “credibility meter” rating that I found helpful.

Some of the articles were classics going way back into the annals of content strategy history (2007!). Others were current articles published in the last couple of weeks, blogs focused on content strategy, and highly regarded “news” web sites devoted entirely to the topic of content.

My Facebook search predictably turned up more results for businesses and services than it did any other type of content. Although I’d expected to be unimpressed, some of these results lead to professional blogs, articles, and other content that was intriguing and informative.

The good news for those selling their wares through social networking is that Facebook associates a name or personality with the content with far more power than any of the other networks I’d tried until this point: it seemed as if the individuals I’d selected from the search results “owned” the topic of content strategy somehow.

Harnessing Social Media Search

My search as pretty broad, but when we don’t know much about the topic we’re searching on, broad searches are the kinds of searches we tend to use.

My little social media search experiment suggested to me that I’ve been wasting my time being frustrated by the major search engines. I’m always a little suspicious of the results they show, and the searches I performed on various social networks here showed me why: in the often impersonal digital realm, I appreciate personal recommendations. This is one of the reasons that more people are moving on social networks for their search needs; it’s a topic that Om discusses in more depth in “Why Google Should Fear the Social Web” (GigaOM Pro link, sub. req.)

The other benefit of social media is, of course, that I could ask my followers and contacts directly for their recommendations of content related to the topic I was interested in, and, if they had a similar interest, they might oblige me with good resources. That’s something that definitely can’t be said for a search engine.

I also enjoy the social network benefits of real-time results, and the ability to tap into content that isn’t necessarily so heavily optimized for search engines that it sits on the first page of results indefinitely. If someone has come up with an exciting new take on my topic in the last, say, week or so, I’d like to access that information quickly and effectively. I think this might be where social network search really wins out.

Accounting for Search Bias

Each of the services I searched on had some kind of bias — whether it was a business-related bias (like Google presenting Google Knol in its results) or a user-based bias (such as Facebook presenting people with content strategy businesses in its results). Ultimately, it’s important for us as searchers to understand the limitations of each service, and use the tool that best suits our searching needs at any time. Overall, though, I found some great material using social network search, and I’ll happily be using it from now on.

Do you use social networks for research? How?

Photo by stock.xchng user GlennPeb.

It means you get instant access to stuff that’s happening as it happens, including up-to-the-minute results from Yahoo! Answers, news and blog posts, and Twitter content. Real-time results are accessible on mobile platforms like the iPhone and Android devices, too, making it even more useful.

Google made an official announcement regarding the service today, posting images of and detailing the new real-time results, but it has yet to implement the new features in all areas. I couldn’t access the real-time searching, for instance, though other recent improvements like the super-clean redesigned home page were active.

The results don’t overrule or occlude the more established type of content you’re used to seeing in Google searches. Instead, they sit alongside sites which contain general information and context related to your query. Judging by the screenshots and preview videos, it’s an elegant marriage of the two types of information, and, best of all, you don’t have to go to a separate site or do any kind of special settings changes to enable the new real-time searching.

If you do want to focus your search on only the most current information, however, you can select “Latest” from the search options menu to view an entire page full of tweets, new blog posts, and fresh news content related to the topic you’re searching. Finally, you can check out “hot topics” on Google Trends to see a list akin to the trending topics on Twitter, except covering all the types of publications instead.

This development has huge implications for web workers. Web research can now speak to the immediate present as well as information that’s had time to percolate. Obviously, that has both good and bad sides. On the one hand, you can better handle major industry shifts as a subject-matter expert, and impress clients with your currency. On the other, people will have to be much more dependent on their own common sense, since real-time information is much more vulnerable to the dissemination of falsehoods, intentional or otherwise.

Check out the following video for more about the new addition to Google’s arsenal:

Let us know when Google gets updated in your area as real-time search rolls out worldwide.

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But the problem with Twitter is that it’s kind of unwieldy. I follow a lot of people, and even though I have multiple accounts to follow different groups of people, a lot gets lost in the stream. Twitter clients with built-in search help, but at a glance, Google Alert-like results would be ideal. Thankfully, there’s a service that does almost precisely that. It’s called TweetAlert.

At first glance, it seemed to me like a way to quickly and easily create your own spam bot, which obviously isn’t something I’d be interested in doing. Upon closer inspection, though, it actually offers a very manageable and unobtrusive way to create a tweet stream with a razor-sharp focus that should prove much more effective than the catch-all net fishing that is Twitter search.

What TweetAlert does is retweet any status update it finds that contains a hashtag of your choosing. For example, you could use #apple, and it would automatically search and retweet any post containing that variable using the account you register with the service. Obviously, you don’t want to use your main account for this otherwise you’ll end up spamming all of your followers; TweetAlert recommends that you create a new account specifically for this purpose.

Once you’ve created an account and set it up on TweetAlert, you can use it in two ways. First, you can follow that account with your main identity to keep on top of that topic. This is especially handy if an account on TweetAlert already exists looking for the same thing you are, so you don’t have to set up a new one. I’m more interested in the second use, which is to add the new account you create to your Twitter client of choice. That way, it’s a simple matter of viewing its timeline whenever you want to check your results, all in one place and without any static from your regular account.

Is it a perfect solution? No, but TweetAlert does go out of its way to make sure it isn’t being too spammy. When it retweets the updates it finds, it changes the hashtag to avoid clogging up regular Twitter search results. That means it isn’t particularly pretty to look at, but it could help you catch something important to your work that you would otherwise have missed entirely, and that’s nothing to sneeze at.

Are you using TweetAlert? Share your thoughts on the service below.

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What do I mean by that? Well, for one, you have Twitter’s trending topics, but more than the 10 you normally see, and they’re arranged in a tag cloud. I also noticed that some from the official Twitter search page aren’t actually present, but it looks like it’s cut out the hashtagged, frivolous stuff, and left the more meaty subjects.

Clicking on any of the tending topics (Bing calls them the “Hottest Topics on Twitter”) generates a search for that term, which at the time of this writing isn’t returning any results. The site is still in beta, and this will no doubt be resolved, possibly by the time you’re reading this post, even. You also get to see some links below the Hottest Topics pertaining to individual trends, complete with some examples of tweets containing those links below it for context.

For now, it seems to be more of a promise of what’s to come than a fully functioning feature, but what it does provide, along with Bing’s usual helpful sidebar results, promise a much more thoughtfully organized, searchable and usable service for people using Twitter for research or to track trends. There’s even a “retweet” icon next to each Twitter result, which leads you directly to your Twitter page, so you can share your discoveries with your followers.

I’ve been skeptical of Bing in the past, but if this is what the future holds, it won’t take much to convince me that Microsoft has some great ideas about search.

What do you think of the new Bing Twitter search?

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The trick is in using Google’s “Search Options,” a new feature added in May of this year that allows you to filter your results a number of ways, including according to how recently something was published. The closest you can get to real-time results using the official Google menu options is “Past 24 hours,” which is handy, but if currency is central to how well you do your job, getting even closer is ideal. Here’s how to do it.

To narrow your results further still, you’ll have to do some manual editing of the results URL you get from conducting a time-specific Google search. Simply conduct a search for the term of your choice and narrow it using the “Past 24 hours” filter. For the sake of this walkthrough, I used “Beatles 2009 Remaster” as my search term. This is what your URL should look like:

http://www.google.com/#q=Beatles%202009%20Remaster&hl=en&safe=off&sa=G&output=search&tbs=qdr:d&tbo=1&fp=b89dc01650a86922

The “qdr:d” portion of this URL specifies the date range for your search. Changing the “:d” part of this formula will change the time frame of your search query. If you replace it with an “n”, so that it looks like “qdr:n,” you get results in the past minute. “qdr:s” returns results posted within the last second.

You can also specify a time frame by putting a number after the “qdr:n,” like so:

http://www.google.com/#q=Beatles%202009%20Remaster&hl=en&safe=off&sa=G&output=search&tbs=qdr:n15&tbo=1&fp=b89dc01650a86922

Which produces these results, published in the last 15 minutes:

You may not need this degree of granularity in your Google search results, but if the nature of your business depends on staying as up-to-date as possible, as it does in my field, then searching Google in real-time is a significant boon.

Share your favorite Google URL hacks in the comments.

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A much-improved version is out of uberVU, a site that helps you track the flow of conversations on the web, whether they’re taking place on Twitter, Digg, Reddit, in the comments sections of blogs, or elsewhere. There are many tools available for searching specific social sites (including lots of them for Twitter), but uberVU is particularly useful for checking on what people are saying all over the social web. In this post, I’ll look at some of the improvements to the app, and what you can get done with it.

If you do any blogging, you may be familiar with going to various sites or search engines to keep track of what’s being said about a particular post you wrote. Or, if you’re following a particularly newsworthy development, you may do the same just to see what the social web’s reaction is to the news. uberVU aims to provide one-stop shopping for that type of task.

AltSearchEngines lists uberVU’s new features, including:

• Search – You can now search for keywords and URLs instead of just adding URLs.
• Faster tracking – You can track links on Twitter, Digg, Reddit and many more in close to real time.
• Analytics – You can view graphs and summaries for a big picture of a web conversation.
• Public – uberVU is now in public beta, with no invitation code required to register.

uberVU is definitely faster at gathering conversation threads from sites such as Twitter and Digg than it was before. Previously, if an event had just happened, and you went to search, you got very sparse reactions from a limited number of sites. That’s changed in the updated version.

The analytics are also useful, especially the graphics you can generate. While she isn’t a tech story, one of the big stories of this past Labor Day weekend was Melanie Oudin, the 17-year old tennis player who is competing at the U.S. Open. I searched on her name at uberVU, and discovered that there was actually a bigger spike in web conversations about her prior to the tournament than during it, as seen in late August, below:

You can also use uberVU’s analytics features to pull up distribution charts showing where conversations are taking place. Below is one for Melanie Oudin showing that Twitter is where most conversations are taking place:

If you haven’t tried uberVU before, give it a go. It can keep you from hopping between many search sites, and is greatly improved in its new version.

How do you track conversations that are happening across the web?

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One thing that Bing does well is give you categories and suggestions related to your searches on the left-hand side of your search results screen. You can get a real feel for how the two search engines differ in this regard by going to Bing-vs.-Google and entering, say, the name of a software application in which you’re interested. As seen in the screenshot above, I typed in “GIMP” for a search there, (GIMP is a popular open-source graphics application) and Bing gave me a number of links on the left side of my screen that were more helpful than Google’s links, including a prominently placed link for downloading the app.

As I’ve noted before, Bing is also very good at natural language searches, for answering questions such as “Which companies has Google acquired?“ It’s good at these because technology from Powerset, leveraging the clustered query intelligence found in the Hadoop software framework, is built into Bing. Using Bing vs. Google, I was able to get several better answers to natural language questions from Bing than I was from Google.

One thing that I wish Bing vs. Google could do is allow me to search for images and video. I can’t see any way to do so, and it’s a shame, because both search engines are good at retrieving pictures and video, and both have their own advantages. For example, Bing lets you hover your mouse arrow over video thumbnails, and see the videos playing in thumbnails before you go to the trouble of visiting the pages on which they’re housed. I wish I could do that on the left of Bing vs. Google’s dual-paned view, while viewing Google’s results on the right.

Google remains my favorite search engine for its reliability and accuracy, but Bing shines at some tasks, and I wouldn’t be surprised to see some of the Bing/Google mashup applications grow and become useful. For now, Bing vs. Google is mainly a novelty, but it does help drive home some of the unique advantages that the two search engines have.

Do you turn to Bing for certain tasks, or does Google remain your default browser?

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Ask Blog Search

While Google Blog Search has sorting by date and relevance, Ask Blog Search has an additional option to sort results by popularity. With the popularity search, the results might be slightly less relevant, but you’ll be able to more easily find the popular blogs talking about a particular topic. You can also search for words in the title of the post, the body, the author, the subject, the description and more in order to help narrow your search. Ask also allows for filtering by date, so you can search for posts only within a certain date range.

Bloglines

While both Bloglines and Ask are from the same company, their searches have slightly different options and different results. Bloglines has similar options, but with a few interesting twists. Bloglines can limit searches using date ranges and sort results by date, relevancy and popularity. However, Bloglines can also sort by date and filtered by popularity, with options to only find results with at least two subscribers or many subscribers. You can even include or exclude news sources within your search.

Technorati

The Technorati blog search has a couple of interesting search options that are worth talking about here. First, you can limit your search to find your results only if the search term appears in a tag. This is great for finding very relevant results (assuming people are accurately tagging their posts). My favorite Technorati option is to search only posts with a lot of authority. You can also see the authority measure right in your search results, and as a bonus, the authority measure is also included when you get RSS feeds of the results if you want to run your results through some tool, like Yahoo Pipes, to do some additional filtering or processing of the results.

These are the three blog searches that I use most frequently along with Google Blog Search, but they are only three out of the many blog search engines that are available.

What is your favorite blog search to find the most authoritative results?

Image by stock.xchng user chidsey

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First, let’s cover a couple of differences between Google Blog Search and the standard Google search along with a few of its advantages. I use these two search engines in very different ways. When I need some piece of information, I use the standard Google search. I use Google Blog Search to monitor information, or to find the newest results for a particular query.

Google Blog Search has a few additional features over standard Google search that make it perfect for monitoring:

• Limited to blogs. This is the “well, duh” difference.
• RSS feeds. This is the key for me. Blog Search has RSS feeds. For anyone familiar with my previous posts, you know that I am an RSS junkie, so I love having RSS feeds available for my searches.

Common Searches

The Advanced Blog Search page has several interesting options that you will find useful in addition to the standard options found in most search engines (AND, OR, exact phrase, etc.)

• Words in the post title. This option is a great way to increase the relevance for your search when searching for common words, by limiting searches to posts that have the search terms in the post title. I tend to use it when searching for topics about RSS or Twitter, for example, since many blog posts mention them in the text of the post, even when the post is actually about some other topic.
• Words in the blog title or at a specific URL. I use these searches almost daily to search a particular blog for a specific article or to see what they have written on a certain topic. While most blogs have a built-in search engine, I generally don’t want to navigate to the blog to type in a search, especially since the search engines used by many blogs aren’t as good or as fast as Google.
• By author. This is a great way to narrow the results if you are looking for something written by a particular author, especially on some of the larger multi-author blogs.

Incoming Links

This is one of my favorite Google search tips, since it finds incoming links to any URL. I use it to find when people link to one of my posts, especially when they don’t use my name or the name of my blog, which would show up in one of my other vanity feeds. Here’s how it works:

• link:fastwonderblog.com — finds links to my personal blog, fastwonderblog.com

I also have a couple of caveats with this one. When some blogs link to my web site in a sidebar, it will show up as a new link for every single new post on that blog, even though the text of the blog post doesn’t link to my web site. This can generate a considerable number of false positives when a prolific blogger links to a web site in a sidebar and you get a new search result for every single post they publish. It is also worth mentioning that while I love to use this operator, I don’t think it is officially supported by Google.

More RSS Results

As I mentioned earlier, I am a self-confessed RSS junkie. I take various search results from different Google searches, and use Yahoo Pipes to construct the searches using lists of keywords with some additional filtering on content and removing duplicate results. Google defaults to RSS feeds with only 10 items, which is fine for low volume queries, but it just isn’t enough for higher-volume searches. The only way I have found to change the number of results in the RSS feed is by tweaking the variable in the URL.

By default, the RSS feed with 10 items will look something like this one. I’ve simplified it by removing any optional parameters to make it easier to read.

• http://blogsearch.google.com/blogsearch_feeds?q=%22Yahoo+Pipes%22&num=10&output=rss

Here’s a version where I have tweaked the “num” variable to show 50 results:

• http://blogsearch.google.com/blogsearch_feeds?q=%22Yahoo+Pipes%22&num=50&output=rss

Many of the search options that I discussed above are also available in the standard Google search, but I tried to focus on the ones that I find most useful when using blog search. You can get a few more advanced search operators out of the Google help pages; however, this unofficial Google guide has many more, and most of them should work with Google Blog Search.

What are your favorite Google Blog Search hacks?

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Standard Operators

FriendFeed’s search uses the AND operator by default, but its implementation of the OR operator can be a little confusing. You can use the standard OR operator between keywords to state that one or other (or both) of the keywords must be present, but if you want to use OR with the advanced operators, you need to use a “,” (example: meetup OR tweetup service:delicious,upcoming). You can also search for phrases using quotes and exclude results using the “-” operator.

Subsets

It is important to note that you can search across all of FriendFeed (the default) or limit the search to results only from your friends. For example, here’s a search for monitoring across all of FriendFeed, and the same search with results from my friends:

• monitoring
• monitoring friends:geekygirldawn

I keep several friend lists. I have a list for the people who are involved in community management and another list of people who have a knack for knowing about new technologies before most people. Those are my two favorite friend lists to search. You can get to this option using the advanced search page or with the following syntax to search for the word “monitoring” in my “community” friend list.

• monitoring list:community

There are also a few other useful subset searches to narrow your search to posts from a particular friend or a group:

• facebook from:gigaom
• panel group:sxsw

Services

Filtering a FriendFeed search by service can be really useful. For example, I often filter the Twitter posts out of my searches to cut down on the noise in my search.

As I mentioned in my previous post about Twitter search, Twitter search only returns results from the last 10 days or so. You can  actually use FriendFeed to search a little further back into the Twitter timeline, at least for those Twitter posts that have also been sent to FriendFeed, by limiting your search just to the Twitter service. I’m not sure exactly how far back in time FriendFeed searches, since it seems to vary by service; however, I am seeing search results from Twitter that are around 40 days old and results from blogs that are much older.

Here are a few examples of searching for “monitoring conversations.” The first example excludes posts from Twitter from the results, while the second just includes results from Delicious and Google Reader:

• “monitoring conversations” -service:twitter
• “monitoring conversations” service:delicious,googlereader

Popularity

As usual, I have saved the best for last. Searching based on popularity measures is what makes the FriendFeed search so powerful. The volume of posts on FriendFeed is so high that it can be difficult to find the most interesting posts on a topic. Filtering your results by the number of likes and comments particular posts have received is a great way to find the posts that are most interesting to people. Here are some simple examples:

• monitoring comments:20
• “community management” likes:10

Where this becomes really powerful is when you use it in combination with some of the search operators mentioned in the sections above.

• facebook comments:5 likes:5 list:news-makers
• facebook research comments:20 likes:20 -service:twitter
• comments:20 likes:20 from:jowyang -service:twitter

Consuming Search

The fun doesn’t stop with the advanced searches. You can also consume FriendFeed searches in so many different ways.

• RSS: Get your search as an RSS feed and put it in your favorite reader.
• Saved searches: Save your searches to reuse them over and over.
• Share: You can share your search with other people.
• Embed: Embed your search to display the results on other sites.

In this post I covered most of the advanced search operators for FriendFeed, but for the full list, visit the advanced search page.

What are your favorite uses for FriendFeed search?

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Lately, many people have been experimenting with Bing, Microsoft’s new search engine offering, which we covered here. I agree with the many people who are noting improvements that need to arrive in Bing, such as blog searching and more varied search results for basic keywords. However, not everyone realizes that Bing is built on a powerful search engine technology from an open source-focused company that Microsoft acquired last year: Powerset. As I covered in this post, the Powerset technology underlying Bing introduces some powerful features that many people aren’t trying. You may find them useful.

Powerset originally got noticed in the search community because it leveraged Hadoop, which is an open-source software framework that allows clusters of computers to make very quick work of mining large data sets. (Hadoop also powers Yahoo’s search engine.) Powerset’s idea was to leverage Hadoop to improve natural language searching, where you type in questions in sentence form instead of using keywords. If you’ve followed natural language searching,  you’ll know that it’s had a rocky, and generally unsuccessful, history.

Hadoop brought Powerset more speed at mining through the mountains of possibly relevant search returns that come back in natural language search engines. Powerset doesn’t underlie all of Bing, but this unique facility with natural language searching is in Bing, and you may find it useful if you haven’t tried it.

Here are some example queries to try at Bing.com, to get a sense for how it works:

• Which companies has Google acquired?
• Which Firefox extensions block online ads?
• What is the semantic web?
• How much was MySQL acquired for?

You’ll notice that many of the search results that come back in these types of searches at Bing are mined from Wikipedia, because Powerset has always specialized in Wikipedia search. Entries on Wikipedia aren’t always correct, so you have to take results with a grain of salt, but Microsoft has extended Bing’s facility with natural language search beyond just Wikipedia searches, and it can be quite good at providing quick answers to natural language questions.

What do you think of Bing’s natural language search capabilities?

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AltSearchEngines has a post up on an interesting search engine concept currently in beta: Springo. The site’s tagline is “shortcutting the Web,” and it specializes in providing categorized results as well as thumbnails of sites related to your search terms, where the thumbnails can keep you from having to click through to various sites until you arrive at what you’re looking for. I wouldn’t use Springo for common search tasks I do every day, such as sifting through news headlines and announcements, but as a way to preview relevant sites in various site categories, it is useful.

A good way to get the feel of Springo is to go to the home page and enter the keyword “jobs” in the search field, then press “Go.” If you do this, on the left side of your search results page, you’ll get a “Narrow” categorized list of job-related site categories, with an “Expand” tab that will give you more if you want. In the “Narrow” list you get categories such as “Work from Home,” “Professionals and Freelancers,” and “Job Search Engines,” as seen to the right.

I clicked on the category “Professionals and Freelancers,” and got a collection of thumbnail views of sites in the category, as seen below. (There are more of these thumbnails available to scan.) Elance and RentACoder both show up as thumbnails, and both sites you should be familiar with, as we’ve written about them many times before. The expanded list contains many other similar sites that we’ve written about for freelancers, such as oDesk.

Springo looks equally useful for other category-oriented types of site discovery searches. For example, do a search on “Browsers” and you’ll get back four neat thumbnails for IE, Firefox, Safari and Google Chrome. You’ll also get categorized collections of sites specializing in toolbars and add-ons, and more.

I wouldn’t use Springo for granular searches on the day’s news, or for definitions and targeted types of research. However, as a site discovery tool within categories you specify with keywords, it does a good job.

What niche search engines do you use?

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Basic Search

Before looking at some of its more advanced features, let’s compare it in terms of a straight-up, simple keyword search on a subject close to my heart. Finding information on Apple is a part of my job, and I run Apple-related searches on an hourly basis, if not even more frequently, over the course of the day.

Searching just for the keyword “Apple,” I found the results fairly telling. Bing returned mostly product pages and sub-sections of the official Apple site. While useful to some degree, these pages are not generally the kind of thing that I’m looking for.

Google returns far more context in the first page of results, including Wikipedia results, news results, the Apple store, Apple Developer Connection, and Slashdot pages relating to the subject. This wider view provides much more material for actually accumulating knowledge about any particular subject.

No Blog Search

Bing looks a lot like Google, and it has a lot of the same features, in the same places. Along the top, you have different search options. A news search is available, along with videos, images, and something called “xRank“, which displays the most popular search results.

Notably lacking, though, is a blog search like the one Google has. The news results page in general is far less powerful and detailed than Google’s, and less easy to navigate. There are blogger rankings in the xRank results, but these appear to be more of a popularity contest and less of a useful feature.

More Advanced Searches

Using keywords to try to deliver instantly useful results for things like travel and quick calculation is definitely something that comes in handy in a search engine. Looking up “travel boston” returned nearly identical results in both search engines, though I did appreciate Bing’s “related searches” in the left-hand column. You can turn on related searches in Google, but they’re more hit or miss than Bing, and they’re switched off by default.

Performing a local search showed another vast gap between the two engines, though. Entering “restaurants near” followed by my postal code returned a long list of actual restaurants and a map displaying their proximity in Google, while it just returned a regular list of results, and not particularly useful ones at that, when entered into Bing.

Bing does calculations just as well as Google, though neither search engine provides a really smart or intuitive way to do currency conversion as of yet, in my opinion.

Verdict

For now, Microsoft still seems to be playing catch-up. Maybe it should stop being so concerned with name/branding changes, and start trying to make leaps in usability instead. This web worker is definitely sticking with Google, at any rate.

Will you be adding Bing to your search toolbox?

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