Picture: Athena’s Pix

1) Filter posts – Read only the posts that are interesting for you
Reading through the Stream there is a big problem finding the most important and interesting information. Facebook has the “Top News” but in Google+ you only get the most recent news.

The picture show an example of how easy the “Filter by Interest” feature could be implemented in the current UI.

I noticed that my stream get noisy with very few users and I need some type of filter to find the most relevant posts. The solution to this problem is to atomically find the most interesting posts and I want to take this one step further than what Facebook have done. I want to analyse the meaning of the content and based on what it is about show only posts that are interesting for me. By using information such as your Sparks, the posts (and links) you shared and the posts you commented on you can use advanced text analytics to predict the relevance of each post based on the users interests.

2) Automatically Recommend Sparks
The first page you see when you visit Sparks can be more interesting. Instead of getting standard Sparks you should get personal recommendations of Sparks that are interesting for you. As before this can be done using what you have written and commented on plus the sparks you already have and in combination with text analysis this will give you some great recommendations.

Get relevant information on a Spark page
Instead of just show the posts on the Spark-page there is an opportunity to show so much more relevant information. For instance;

3) Related Persons to the spark, showing people that often comment or share information in the area. This makes it possible for persons that are interested in an area to find other people to add to circles and to interact with them.

4) Related Sparks, showing other sparks that are related to this one and makes it easy to find more interesting material.

5) Related Posts, find other posts that are about the same subject/event so you can find out about what have happened before this article was written.

The picture shows how related persons, related Sparks and related posts can be implemented in Google+.

Summary
I think there are a few killer features that could be build very easily that would be able to change Google+’s position.
This are my top five
1) Smart filer of Stream
2) Automatic recommendation of Sparks
3) Related Persons
4) Related Sparks
5) Related Posts
Sure there is also an opportunity for Facebook to implement similar features before Google does it. So who will win, Google+ or Facebook?

Note: The features are not science fiction they can all be implemented using existing text analytics technologies.

The supported languages are Swedish and English, with additional languages coming in the future depending on interest.

The module works with Drupal 6.x and PHP 5 or later. If you’re interested in seeing a version for Drupal 7 please contact us. At this moment the module is being reviewed by the Drupal community, but you’re free to download it using Git from the sandbox page.

The Saplo Drupal module supports two of the main features from the Saplo API.

Tagging

Using our module you can – with the push of a button – extract tags from articles.
The benefits of this versus a manual approach are twofold; first of all it’s very convenient to have the tags magically appear with the click of a button. Second of all you add consistency to the tagging, since the Saplo Text Analysis API is based on machine learning and will intelligently analyze and extract the tags the same way every time. It’s like having a dedicated employee just doing your tagging.

Related Articles

The module also provides you with a means to display related content, for example lists of “Related articles” that are often found at the end of news articles.
Similar modules have the capability to do this as well, but are often powered solely on tags. In other words, they make the assumption that articles that share the same tags should be related.
The Saplo API goes beyond that; we use semantic analysis and machine learning to give a higher precision to this relevance.

The caveat is that the module can only give you related content if that content has been previously analyzed. So as you analyze more and more of your articles or text, naturally more related content will be able to be displayed.
We basically establish relationships between different pieces of content, which is measured in a perceptual value. E.g. “this article is 60% similar to that article”. These relationships will be stored in the database powering your Drupal installation; so you’re free to use it in interesting ways if you want to.

Included in the module is also a basic filter, where you can change the relevance thresholds for displayed related content. So if you only want to display articles that are very related, you can easily do so in the administrative interface.

Using the Saplo Drupal Module

Installing the module is easy; you will be able to find the complete guide on the module page. In essence, it goes like this:

1. Download and unpack the module inside your module folder.
2. Enable the module in the Drupal administrative interface.
3. Enter the API Key-pair that you’ve received from signing up at http://saplo.com/signup/free into the modules administrative interface.
4. Enable the service you want (tagging, related articles) for your node types.
5. Insert a new node, and when inside the view click the “Add Saplo Metadata”-button.

The “Add Saplo Metadata”-button is probably the most common way you will be interacting with the module, besides changing settings inside the administrative interface.
Pressing this button sends the text from the node to the Saplo API. Once the Saplo API is done analysing the text it sends back the the extracted metadata that you’ve requested. The data is then saved locally, and displayed when the node is viewed.

Other features

The module implements various useful Drupal hooks. Amongst others we have different permissions that you can enable for users to access the administrative interface and to extract metadata for articles.
We also provide a small template that you can further configure that shows the related articles.

The goal with our new text analysis demo is more then anything to make it easier to try out. That’s why the frontpage at demo.saplo.com now has a predefined text in the textarea. That way you as a visitor can just click submit and get results for the text immediately.

You can also toggle between English and Swedish texts or you can switch between news articles and tweets. If that doesn’t do it for you, there’s also the option of writing or pasting your own text into the textarea.

The demo provides you with three different kinds of results:

• Entity Tagging
• Similar Articles
• Similar Tweets

Give the demo a try at demo.saplo.com!

How is the demo built?
First of two different text collections is created through the Saplo Text Analysis API using the collection.create method. The first collections store articles and the second tweets.

We crawl news articles from a couple of news sites and we collect tweets from specific Twitter streams. Tweets and articles are added to the two different text collections using the API method text.create.

Next we create a third text collection, in this collection articles and tweets written by visitors will be stored.

Both Similiar Articles and Similar Tweets uses the same API method, text.relatedTexts. Entity tagging is performed using our text.tags method.

That’s it, nothing more fancy about it.

Just with Yahoo Pipes, the numbers of interesting use cases are vast. For instance, you could with some minor filtering send in an RSS-feed containing new movies, and only show the ones that are rated higher through a certain service (say, IMDB). Another example is enriching a feed with geographical information, perhaps even showing it on a map.

A more recent example of such a filter is the widely celebrated Priority Inbox-feature for Gmail, where using certain heuristics an email can be suggested to be more important than others.

Tools from text analytics fit very nicely in this category; and can really be an integral part of piecing together certain contexts or bits of information while pushing others further away from each other.

Our experiments in this foray was (and still is, although development has been rather slow lately) Saplo Stream, a small twitter integrated web application where links from people you followed were crawled, and depending on what the content you yourself had shared through your own tweets, different types of links where displayed to you inside the application.

The most interesting part however, was in the form of customizable filters for the incoming articles. We have all seen the “related articles” or “related content” at the bottom of news articles. In this case, the customizable filters could be tweaked and tuned to give a high relevance against certain types of content – meaning you could in fact filter out all the links coming in that for instance had to do with foreign policy, or mobile technology.

The filtering itself was done using our own text analysis API, where you can bunch together texts in different ways and infer how similar they are to one another in different ways.

The problem – Information Overload

Information on the Internet is growing by the minute and today’s fast paced society gives us less time to read it. We as humans are limited by a surplus rather than a lack of information. Current information technology (e.g., Google Search) produces enormous amounts of results which can be hard to survey. Even more information is discarded because your personal intent of a search query is unknown. Do you recognize the following situations:

- You have been away for a week and want to be updated on what has happened, where and how do you start reading?
– You have 10 minutes to spare when you travel by bus. How do you find the most relevant information to read?

In order to solve this problem of information overload there is an obvious need to augment current information gathering techniques with the ability to filter and sort large text masses.

The solution – a personalized and time constrained text stream

Saplo Stream will automatically filter text according to how relevant they are based on your personal interests. Thanks to filtering you can choose how many minutes you want to spend on reading. This service aspires to end the days of information overload. Whether you want to read the most interesting news from the past month in one hour or from the past day in 10 minutes, Saplo Stream will help you find the most relevant and thus valuable information.

For the time being, news sources are collected from your Twitter stream. However, we plan to add more sources in the future.

How do you sign up?
Sign up using your Twitter account on SaploStream.com

Keep in mind that this is an Alpha version and gradually more people will be given access. We will of course work as fast as we can to provide access to more people over time. Follow @SaploStream for updates.

Think-Tank FORES together with Axess-TV and makthavare.se (makthavare.se) evaluated the statements from party leaders during the political week in Visby, Almedalsveckan, Sweden. In “Ideologisk After Speech”, broadcasted daily by Axess-TV, the statement were scrutinised from every aspect under the stewardship of FORES director Martin Ådahl.
The statement underwent an ideological evaluation (liberal or conservative, left or right) by a political philosopher, a fact check was made by makthavare.se, and economist Andreas Bergh made a calculation of the cost from the Speech. In addition to this, we used the Saplo API to analyse the speeches.
Politicians are often accused of being unclear, and being hard to separate from each other. They all sound the same, don ´t they?
We were interested in finding out to which degree the party leaders sounded the same, but even more interested we were in finding out who they resemble. Is it true that Fredrik Reinfeldt (Prime Minister) sometimes sound more like a social democrat? In Almedalen, he apparently did, since his speech according to our analysis resembled Mona Sahlin”˜s (party leader, social democrat) previous speeches more than his own. By the way it seems like Mona Sahlin is the one party leader who can be said being difficult to differ from the others. She finished top three in every analysis, meaning that every statement was pretty similar to the statements Sahlin usually deliver.
On the other hand it seems like Lars Ohly (party leader, left-wing party) is the odd man out, since every speech other than his own were furthest away from being similar to the left party leader´s.
In order to do the analysis, we collected a large amount of speeches from every party leader and created a context (using Saplo Context) for every leader. We than compared the Almedalen speech to each context.
Being aware that it is no exact science, it still added an extra spice to the After Speech and now we know – Fredrik Reinfeldt is more Mona Sahlin than Fredrik Reinfeldt. And Lars Ohly´s statements are the black sheep of Swedish political statements.

http://fores.se/almedalen/ideologisk-after-speech-almedalen-2010/ (Swedish)

As many of you already know, Saplo´s main focus is to create an outstanding API for Text Analytics. What´s interesting with our new Widget is that we have built it entirely based on our API. This means that developers with access to our API could easily do the exact same thing.

Some of the news in Saplo Widget:

• Easy to use administration panel
• Blacklist
• Multiple User Accounts
• Edit Entity Tags
• Customizable Widget design

Important coming features:

• Add and edit related articles
• Statistics on Widget performance

Our metrics have shown that more then 1 (%) percentage of all visitors have clicked on a tag or related article presented by Saplo Widget. We are very excited to see if and how the placement of the Widget and the design of the Widget will affect the click-through-rate. When we know we will share the news.

We have been working on improvements for the Widget based on extremely valuable feedback from an amazing customer of ours. Big thanks and keep it coming!

Saplo Tags automatically extracts entities such as persons, companies and geo-names (in this case in Swedish). This is eliminating manually work for editors. Please notice that this is a beta version and Saplo will focus a lot on improving the service in the upcoming months.

Read more about the service in Sydsvenskans blog (links in the end of the document).

Please let us know if you have any suggestions or ideas.

For more information about Saplo Tags and how you can use it, please contact:
Mattias Tyrberg, CEO Saplo
+46709797724

Read more at Sydvenskan.se (Swedish)

The report is in Swedish (if you are interested in having the report in English please contact us at we@saplo.com).

Top 5 characteristics:
1) structured
2) independent
3) humble
4) enterprising
5) responsibility taking

The analysis is done automatically and the word represents the in meaning most valuable characteristics for the employer.

Information in Swedish

Saplo och Monster släpper jobbrapport – Viktigaste egenskaperna hos anställda 2009

Vad är det som krävs för att få drömjobbet på en sviktande marknad?

Saplo har gjort en analys på över 3000 jobbannonser och har automatiskt tagit ut de egenskaper som arbetsgivaren tycker är viktigast.

Listan får publiceras fritt så länge källan Saplo.com uppges tydligt i texten samt att det återges att det bygger på jobbannonser från Monster.

De vanligaste egenskaperna som eftersöks hos dig som letar jobb. Förra årets placering inom parentes.

1. Strukturerad (1)
2. Självgående (3)
3. Prestigelös (4)
4. Initiativrik (15)
5. Ansvarstagande (8)
6. Utåtriktad (6)
7. Positiv (5)
8. Serviceminded (7)
9. Flexibel (9)
10. Säljinriktad (NY)
11. Stresstålig (2)
12. Pedagogisk (NY)
13. Entusiastisk (NY)
14. Analytisk (NY)
15. Kommunikativ (NY)
16. Kreativ (NY)
17. Disciplinerad (17)
18. Resultatinriktad (NY)
19. Noggrann (10)
20. Tävlingsinriktad (NY)

Källa: Saplo/Monster

För frågor kring rapporten vänligen kontakta :
Mattias Tyrberg, VD Saplo
Email: Mattias@Saplo.com
Mobil: 0709-797724

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