Here is something new from Gigaom: “Stanford Researchers To Open Source Model They Say Has Nailed Sentiment Analysis.”Richard Socher and a team from Stanford have created a computer program that can classify the sentiment of sentence with 85% accurately. They tested the model on movie reviews with a positive or negative tone. Even more amazing is that Socher and his team are making the project available to everyone. Why not capitalize on it instead? After all, companies have been trying for years to analyze social media and would pay the big bucks for said technology.
What makes Sucher’s project different from other sentiment software is that is reads whole sentences rather than just words.
“The team then built a new model it calls a Recursive Neural Tensor Network (it’s an evolution of existing models called Recursive Neural Networks), which is what actually processes all the words and phrases to create numeric representations for them and calculate how they interact with one another. When you’re dealing with text like movie reviews that contain linguistic intricacies, Socher explained, you need a model that can really understand how words play off each other to alter the meaning of sentences. The order in which they come, and what connects them, matters a lot.”
Socher hopes to reach a 95% accuracy, but the technology will never be 100% accurate because of jargon, idioms, odd word combinations, and slang. The project is making landmark strides in machine learning, logical reasoning, and grammatical analysis.
It means better news for online translators and speech technology, but commercial sentiment analytics vendors may see a decline in their profits.
Analyzing Fake Content on Twitter During Boston Marathon Bombings
As iRevolution readers already know, the application of Information Forensics to social media is one of my primary areas of interest. So I’m always on the lookout for new and related studies, such as this one (PDF), which was just published by colleagues of mine in India. The study by Aditi Gupta et al. analyzes fake content shared on Twitter during the Boston Marathon Bombings earlier this year.
Gupta et al. collected close to 8 million unique tweets posted by 3.7 million unique users between April 15-19th, 2013. The table below provides more details. The authors found that rumors and fake content comprised 29% of the content that went viral on Twitter, while 51% of the content constituted generic opinions and comments. The remaining 20% relayed true information. Interestingly, approximately 75% of fake tweets were propagated via mobile phone devices compared to true tweets which comprised 64% of tweets posted via mobiles.
The authors also found that many users with high social reputation and verified accounts were responsible for spreading the bulk of the fake content posted to Twitter. Indeed, the study shows that fake content did not travel rapidly during the first hour after the bombing. Rumors and fake information only goes viral after Twitter users with large numbers of followers start propagating the fake content. To this end, “determining whether some information is true or fake, based on only factors based on high number of followers and verified accounts is not possible in the initial hours.”
I was invited to a potluck dinner on Wednesday to meet a bunch of strangers and discuss the importance of sharing. Well, kind of. Our hosts were looking to bolster the so-called sharing economy, which, depending on who you talk to, is either a lightweight form of socialism or an artisanal flavor of capitalism spawned by the Internet.
The event had clearly attracted people from both camps. It wasn’t long before one guest trumpeted a desire to “kick capitalism in the crotch,” while several others gently reminded people to sign a petition supporting Airbnb, the peer-to-peer apartment renting service. One man offered to sing a few songs. I spent much of the evening wondering why my red pepper hummus, which is always a hit at Super Bowl parties, wasn’t as popular as the vegan mac ‘n’ cheese. Plus whoever made the salad put in way too many red onions.
Standing in the cloudy center of all this was a group called Peers, which popped up over the summer with the goal of becoming a grassroots movement based on sharing. The potluck dinner—and about 130 other events taking place in 90 cities around the world on the same week—is its first big push to bring people to the cause.
There have been movements based on sharing before, as my aging hippie parents remind me with increasing regularity. But the brand-name version is relatively new. In the past few years, a series of startups have based their business models on creating online platforms where people can sell one another access to their homes (Airbnb), labor (Taskrabbit), or possessions (Lyft, Sidecar). These companies bathe in the spirit of cooperation—and it’s clearly to their benefit to frame themselves as facilitators of generosity—but they are also marketplaces looking for commissions.
If you're passionate about free software, the Free Software Foundation wants you to be a part of LibrePlanet 2014.
We're excited to announce three new ways to get involved in next year's conference: answer our Call for Sessions, apply to join our Exhibit Hall, or join our new Volunteer Committee. We are now accepting applications for each one of these exciting ways to be a part of this annual gathering for free software advocates, contributors, and users.
Click on Image to Enlarge
LibrePlanet is the annual conference of the Free Software Foundation and will be held in March 2014 in Cambridge, MA. This year, the theme of LibrePlanet is “Free Software, Free Society.” How can free software protect journalists, whistleblowers, activists, and regular computer users from government and corporate surveillance? How can free software, or free software values like copyleft, community development, and transparency, be used by people fighting to create free societies around the world? What challenges are standing between us and our goal of free software ubiquity? With your help, we'll tackle these questions and more at LibrePlanet 2014.
All associate members of the FSF may attend LibrePlanet gratis. Be sure to join our announcement list to be the first to know when the conference dates and venue are officially announced!
Red Hat used to wear the open source crown. Then Google. But Facebook and other web giants now contribute the most to open source.
Matt Asay
ReadWrite, October 17, 2013
Quick question: which is the largest open source company on Earth? That's easy, right? It's clearly Red Hat. After all, the company pulls in over $1 billion each year selling services around open-source software like Linux and JBoss.
But as I've argued before, such a distinction fits a very old-school understanding of open source business. Back in 2009, I suggested that Google was the world's biggest open source company, given the copious quantities of code it contributes, not to mention its source code repository, inspiration of massive projects like Hadoop and other contributions. While some took exception to my classification of Google as an open source company, I still think it was accurate.
Except that Google is no longer the biggest open source company. Facebook is.
Information and knowledge have been both feared and sought in the past. New information brings change, and change is often met with fear and resistance. In the past books were burned by the church and new technology destroyed by Luddites. The change that new information and knowledge brought was often regarded as threat to established interests. But inevitably with time, it brings benefits for all. New information changes our perception of ourselves, others and our environment. It breeds ideas and solutions for the obstacles we face and creates a positive feedback loop which is the driving force behind progress.
In prehistory people were educated by the demonstration of acquired skills directly to one another and from generation to generation. Ideas were communicated through storytelling, song and rituals, but it wasn't until approximately 3500 years ago symbolism and finally written language emerged. This drastically changed the way people learned, communicated and organized information because now it could be stored outside of the brain and retrieved later for use. Written language also helped reduce loss and corruption of information because recall was no longer limited to physical memory.
