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News from The Semantic Sphere #IEML (4th of August 2012)

News from The Semantic Sphere #IEML (4th of August 2012) | Natural Language processing | Scoop.it
I had an epiphany yesterday. I understood that the Volume 2 of The Semantic Sphere will not contain the grammar and the dictionary of the language but only the rest of the theoretical, epistemological and transdisciplinary stuff that I have began...
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Natural Language processing
How can computers handle human language. Linguistic theory and research. What are the latest discoveries about languages. Latest research discoveries.
Curated by Mariana Soffer
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List of 25+ Natural Language Processing APIs

List of 25+ Natural Language Processing APIs | Natural Language processing | Scoop.it
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Natural Language Processing, or NLP, is a field of computer science, artificial intelligence, and linguistics concerned with the interactions between computers and human (natural) languages.
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NLP for Historical Texts

NLP for Historical Texts | Natural Language processing | Scoop.it
Mariana Soffer's insight:

In a narrow sense, “digital humanities” refers to the application of quantitative, computer-based methods for humanities research, usually complementing traditional qualitative methods (note that this definition involves both readings of “digital”). The important point is that it is humanities research, i.e., you’re applying these methods to answer a humanities research question.

In a wider sense, it may also refer to the application of computer-based tools in humanities research (note that this definition does not require the use of quantitative methods). For example, creating a digital edition is not digital humanities in the narrow sense (because it does not use quantitative methods), but it is in the wider sense. I think this extension is useful, because the creation of digital resources is a prerequisite for digital humanities in the narrow sense.

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Twitter Fan Wiki / MacApps

Twitter Fan Wiki / MacApps | Natural Language processing | Scoop.it
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Welcome to the Twitter Fan Wiki

We've set this up as a place to post cool ideas, uses and feature requests for Twitter.

Share anything you've found that you think the Twitter community might be interested in!

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Social Data in Academic Research

Social Data in Academic Research | Natural Language processing | Scoop.it

Via Stuart Shulman
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Stuart Shulman's curator insight, June 8, 2013 3:37 PM

Lots of great blog posts at blog.gnip.com after the highly successful 2nd Big Boulder social data conference. 

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SemantAPI – Downloads

SemantAPI – Downloads | Natural Language processing | Scoop.it
Mariana Soffer's insight:

Sentiment Analysis

 

The SemantAPI toolkit is a free, open source toolkit intended for a quick and easy comparison of the most popular NLP and sentiment analysis solutions on the market. The toolkit offers 2 independent analysis applications: SemantAPI.Robot and SemantAPI.Human, as well as a data stream application, GNIP to CSV.

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Sentiment Analysis on Twitter with Datumbox API

Sentiment Analysis on Twitter with Datumbox API | Natural Language processing | Scoop.it
Hey there! After my post about sentiment analysis using the Viralheat API I found another service. Datumbox ist offering special sentiment analysis for Twitter. But this API doesn´t just offer sent...
Mariana Soffer's insight:

Twitter Sentiment Analysis, Subjectivity Analysis, Topic Classification, Spam Detection, Adult Content Detection, Readability Assessment, Language Detection, Commercial Detection, Educational Detection, Gender Detection, Keyword Extraction, Text Extraction and Document Similarity.“

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luiy's curator insight, September 9, 2013 1:37 PM

Datumbox offers a large number of off-the-shelf Classifiers and Natural Language Processing services which can be used in a broad spectrum of applications including: Sentiment Analysis, Topic Classification, Language Detection, Subjectivity Analysis, Spam Detection, Reading Assessment, Keyword and Text Extraction and more. All services are accessible via our powerful REST API which allows you to develop your own smart Applications in no time.

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Why LinkedIn Became My Favorite Social Network

Why LinkedIn Became My Favorite Social Network | Natural Language processing | Scoop.it
It's nothing personal—just business.

 

Of the many social networks constantly vying for my attention—Facebook, Twitter, Google Plus, Pinterest, LinkedIn, Tumblr, and maybe YouTube—LinkedIn has won my heart. Here’s why:


Via Anita Windisman
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Natural Language Understanding- awards announced

Natural Language Understanding- awards announced | Natural Language processing | Scoop.it
Mariana Soffer's insight:

Some of the biggest challenges for the scientific community today involve understanding the principles and mechanisms that underlie natural language use on the Web. An example of long-standing problem is language ambiguity; when somebody types the word “Rio” in a query do they mean the city, a movie, a casino, or something else? Understanding the difference can be crucial to help users get the answer they are looking for. In the past few years, a significant effort in industry and academia has focused on disambiguating language with respect to Web-scale knowledge repositories such as Wikipedia and Freebase.

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Is language just a tool?

Is language just a tool? | Natural Language processing | Scoop.it

The use of language has an extended effect upon society and culture. This effect cannot be determined exactly and the intent behind its use is not the production of change but communication between individuals across time and space. Society uses language and the language grows with time and the number of it’s users.

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Language and philosophy by Chomsky

Language and philosophy by Chomsky | Natural Language processing | Scoop.it

You don't need language to communicate.

It's dogma that language and communication are the same thing. Any action you carry out communicates something. "A gesture, a hairstyle, almost anything. Sure, language behaviour also communicates something."

"Beyond that, almost all language is not involved in communication. We all know that, you can't go one minute without talking to yourself, it would take a tremendous effort of will to not think about what's going on in your head. That's communication with self."

Constraints of Knowledge

Just like a dog is incapable of learning quantum physics, humans have their own limits of intelligence and understanding. "This really shouldn't surprise anyone, we know we have constraints on what we can do physically, we can't fly like eagles let say. If there are also limits to our cognitive capacities, that really shouldn't surprise anyone. It would just say we're biological organisms, not angels." 

"Furthermore, instead of being unhappy about our limits we should be happy about them. If there were no constraints you couldn't learn anything, you couldn't acquire anything, you couldn't discover anything. If you don't have limits, you don't have scope, there's a logical connection between limit and scope. The fact that there are limits on what you can be, enables you to become what you did become. Instead of living a pointless existence."

Limits of Science. 

The point of Science is to understand as much as we can about the nature of things, a worthy objective. It is not however meant to understand everything, that's impossible. 

"Science can deal with simple things, but it doesn't get anywhere when it gets to complex things. It's hard, it's hard to explain even simple things, but when it does we find all kinds of surprising things, for example, you find our only intelligible concept of the world is wrong."

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Future syntax

Future syntax | Natural Language processing | Scoop.it
Mariana Soffer's insight:

As described by Terence McKenna in Ordinary Language, Visible Language and Virtual Reality:

The starships of the future that will explore the high frontier of the unknown will be syntactical. The engineers of the future will be poets. 

This is what virtual reality holds out to us—the possibility of walking in to the constructs of the imagination. In a way culture is that. I mean our cities, bridges, highways, airliners and art galleries are condensations out of the imagination, but at tremendous cost because we must make them out of matter. Once we can make them out of light, out of electrons, then we won't build skyscrapers a hundred and twenty stories high, we'll build them as high as we want. 

Roof height will no longer be a factor ruled by cost effectiveness and gravity, it will be a parameter ruled by the imagination as well all other parameters and then we will discover what man truly is—when we are able to erect, stabilize, share and explore our dreams in a kind of virtual hyperspace that, carefully analyzed, is seen to be linguistic.
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Twitter-Mining Captures Global Mood Patterns

Twitter-Mining Captures Global Mood Patterns | Natural Language processing | Scoop.it
Mariana Soffer's insight:

An analysis of mood patterns distilled from half a billion tweets has produced a civilization-scale picture of how moods rise and fall in tandem, over time and across the world.

The details seem intuitive: positive feelings peaking in the morning, dipping during work and rising at day’s end; negativity accumulated over the workweek dissipating late on Friday afternoon. But they’ve proved surprisingly tricky to measure.

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More Clever Tokenization of Spanish Text in Social Networks

More Clever Tokenization of Spanish Text in Social Networks | Natural Language processing | Scoop.it
Mariana Soffer's insight:

Text written by users in Social Networks is noisy: emoticons, chat codes, typos, grammar mistakes, and moreover, explicit noise created by users as a style, trend or fashion. 

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NLP Logix – Experts in Predictive Modeling and Machine Learning

NLP Logix – Experts in Predictive Modeling and Machine Learning | Natural Language processing | Scoop.it
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Mariana Soffer's insight:

NLP Logix uses next-generation sentiment analysis to increase customer loyalty and retention. Sentiment Analysis refers to the use of natural language processing, text analysis and computational linguistics to identify and extract subjective information in source materials. This cutting-edge technology gives an organization the ability to monitor client or customer sentiment on a real-time basis, and when combined with other transactional data, can provide a probability score of overall client satisfaction.

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Ontology for Media Resources 1.0

Ontology for Media Resources 1.0 | Natural Language processing | Scoop.it
Mariana Soffer's insight:

This document defines the Ontology for Media Resources 1.0. The term "Ontology" is used in its broadest possible definition: a core vocabulary. The intent of this vocabulary is to bridge the different descriptions of media resources, and provide a core set of descriptive properties. This document defines a core set of metadata properties for media resources, along with their mappings to elements from a set of existing metadata formats. Besides that, the document presents a Semantic Web compatible implementation of the abstract ontology using RDF/OWL.

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Collecting Data from Twitter: Firehose or API?

Collecting Data from Twitter: Firehose or API? | Natural Language processing | Scoop.it
In this post we explain the distinction between the streaming API and the search API, and how the sampling methodologies differ.

Via Stuart Shulman
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Stuart Shulman's curator insight, May 24, 2013 3:38 AM

More good work from the HMC.

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DiscoverText

DiscoverText | Natural Language processing | Scoop.it

Powerful online software tools for text analytics. Collect, archive, filter, search & classify data from surveys, public comments & social media. DiscoverText is a 'Swiss Army knife' for text. With one platform, DiscoverText, users can capture, filter, de-duplicate, cluster, search, human code, and machine-classify large numbers of small, unstructured units of text. Our approach mixes human and computer training in an elegant and powerful loop.


Via Stuart Shulman
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Stuart Shulman's curator insight, August 13, 2013 11:56 AM

Excitement is building for a late September release of the new DiscoverText interface.

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IBM Watson

IBM Watson | Natural Language processing | Scoop.it
Watson, the IBM computer that will compete on Jeopardy!, represents an impressive leap forward in analytics and systems design.
Mariana Soffer's insight:

For the first time, IBM will open up Watson as a development platform in the Cloud to spur innovation and fuel a new ecosystem of entrepreneurial software app providers who will bring forward a new generation of applications infused with Watson's cognitive computing intelligence.

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Deeply Moving: Deep Learning for #Sentiment Analysis

Deeply Moving: Deep Learning for #Sentiment Analysis | Natural Language processing | Scoop.it
This website provides a live demo for predicting the sentiment of movie reviews.

Via ukituki, luiy
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luiy's curator insight, September 8, 2013 7:50 AM

This website provides a live demo for predicting the sentiment of movie reviews. Most sentiment prediction systems work just by looking at words in isolation, giving positive points for positive words and negative points for negative words and then summing up these points. That way, the order of words is ignored and important information is lost. In constrast, our new deep learning model actually builds up a representation of whole sentences based on the sentence structure. It computes the sentiment based on how words compose the meaning of longer phrases. This way, the model is not as easily fooled as previous models. For example, our model learned that funny and witty are positive but the following sentence is still negative overall:

 

This movie was actually neither that funny, nor super witty.

The underlying technology of this demo is based on a new type of Recursive Neural Network that builds on top of grammatical structures. You can also browse the Stanford Sentiment Treebank, the dataset on which this model was trained. The model and dataset are described in an upcoming EMNLP paper. Of course, no model is perfect. You can help the model learn even more by labeling sentences we think would help the model or those you try in the live demo.

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The Complete Guide to Sentiment Analysis for Marketers

The Complete Guide to Sentiment Analysis for Marketers | Natural Language processing | Scoop.it

The bigger your company gets, however, the harder it becomes to keep a handle on how everyone feels about your brand. For large companies with thousands of daily mentions on social media, news sites and blogs, it’s extremely difficult to do manually.

 Read More: http://www.vocus.com/blog/the-complete-guide-sentiment-analysis-for-marketers/


Via Antonino Militello, Ralph Poole
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Artificial Intelligence For Language? Programming Content And Intuition In Semantics

Artificial Intelligence For Language? Programming Content And Intuition In Semantics | Natural Language processing | Scoop.it

Obviously language is easier than visual recognition and linguists and programmers have spent 50 years trying to program semantics as software. While IBM's Jeopardy-winning Watson system and Google Translate are high profile, successful applications of language technologies, the humorous answers and mistranslations they sometimes produce are evidence of the continuing difficulty of the problem: that computers lack a lifetime of experience. Using the context in which a word is used, an intrinsic understanding of syntax and logic, and a sense of the speaker's intention, we can intuit what another person is telling us and programs cannot. 

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Mariana Soffer: Reflections about Meaning

Mariana Soffer: Reflections about Meaning | Natural Language processing | Scoop.it


First, we need to examine “meaning” itself, and expose a mistake, a very basic mistake, in how many people think about it. To say that some event means something without at least some implicit understanding of who it means something to is to express an incomplete idea, no different than sentence fragments declaring that “Went to the bank” or “Exploded.” Without first specifying a particular subject and/or object, the very idea of meaning is incoherent.

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Meaning of natural words vs the meaning of artificial words

Meaning of natural words vs the meaning of artificial words | Natural Language processing | Scoop.it
Mariana Soffer's insight:

The fashionable ideology that “artificial” lacks the inherent goodness of “natural” is an appealing, but hopelessly simplistic notion of the intellectually chic. Artifice is the result of a deliberate intent to make. Nature also “makes” things, using a set of basic building blocks common throughout the universe. Exchanging infinite time for deliberate design, nature has ingeniously built plants, planets, galaxies and unimaginable constructs which seem to structure the univers itself. 

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The Early-Literacy Shift: New Words, New Media, New Friends

The Early-Literacy Shift: New Words, New Media, New Friends | Natural Language processing | Scoop.it

"Literacy is changing. It really is. Even in my grade one classroom as the students begin to learn their letters and sounds, as they start to put those letters and sounds together into words, and as they take their first hesitant steps to read and write —literacy is changing.

The change in our classroom was subtle at first. When my students began writing the word we with two i’s, I smiled and talked about the more traditional spelling of the word. When students came to school with a clear understanding of what it meant to get to the next level or to have several lives, I took notice of the new vocabulary they had."


Via Beth Dichter
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Beth Dichter's curator insight, July 28, 2013 4:03 PM

Putting young students together with technology creates a win-win situation in this classroom. Learn how one teacher has her students writing in blogs to share their work, using twitter, learning vocabulary (such as pingback) and much more. This post is complete with a video where students provide definitions of words and share how they use technology in their classroom.

Mariana Soffer's comment, July 29, 2013 2:53 AM
Great post, do you have a website or a blog?
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Join The Dots - Social Business

Join The Dots - Social Business | Natural Language processing | Scoop.it
Insight: …information as dots on a screen and the story is the way to connect those dots… "Professor Brian Sturm presents storytelling as a way of organizing information, conveying emotions, and building community.
Mariana Soffer's insight:

Professor Brian Sturm presents storytelling as a way of organizing information, conveying emotions, and building community. A model of #storytelling as altered state of consciousness (the story trance) is presented that includes 16 portals to altered states. Three stories are told to illustrate the theoretical model: Truth and Story; What happens when you really listen; and The stone cutter. Storytelling ethics and the need for trust and truth are discussed

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