fredmcclimans.com Study: Social media is 'brain candy' - Vote for the best company in Austin's business competition ACBJ archive Researchers at Harvard say that social media is brain candy for those who use it. The study comes as the deadline nears for nominations to participate in the Social Madness competition which will honor companies doing outstanding work in social networking. Staff Silicon Valley Business Journal A new study from Harvard says the reason that Facebook, Twitter and other social media are so popular and addictive is that they pleasantly stimulate the same part of the brain as when people eat food, get money or have sex. The researchers found that people simply like to talk about themselves and social media outlets provide a very effective way to do that. The researchers at Harvard asked test subjects hooked up to an MRI machine questions about their own opinions and some about other people's opinions. They found the brain was strongly engaged when the test subjects talked about themselves, and less engaged when talking about someone else.
HP “All in on Big Data.” More Acquisitions Ahead? HP has watched Big Data develop over several years and believes that it will cause major disruption in the storage and systems market, says Manoj Goyal, Senior Director of Data Management Solutions in HP’s Enterprise Group. As a result, “HP is all in on Big Data,” he said in an interview in The SiliconAngle Cube at HP Discover 2012 (full video below). It is working to develop a complete ecosystem around Hadoop that includes hardware, middleware, software, and services to “make Big Data more accessible to customers.” And, he said, “While HP does not make its M&A plans public, we are always looking for partners and ways to fill in gaps. Over time big things will happen.” HP, he said, is solving the “Big Data consumption problem. Meanwhile, Goyal’s group is working with Autonomy and Vertica internally to create a software layer to support Big Data analysis. “Clearly Vertica is the best place to take the Big Data once it is structured,” he said.
Understanding Big Data « opencollaborarchy The more we know the less we understand. Nowhere is this more true than on the Social Network, where volume, velocity, volatility and variability are increasing on a daily basis. Those 4 V’s are part of a definition of big data, which includes both structured and unstructured data. We may have a reasonable chance of obtaining valuable information from the structured data population. In general there are no data models, no data definitions, no rules and no discipline of housekeeping for unstructured data in Social Media. We do however have some rudimentary tools at our disposal, but like early man our technical bows and arrows are a poor match against the stampeding herd of beasts that is the social network stream. Knowing how to perform the three C’s is therefor one of the keys to success. Taking these observations a little further I believe the following 5 components are necessary in order to navigate, participate and collaborate in world of social information. 1. 2. 3. 4. 5.
10 Ways to Discover Social Media Content When brainstorming about what kinds of content to create and share in social media, you need not look any further for inspiration than social media channels themselves. Colleagues who communicate with customers every day can also provide excellent insight. Let’s take a closer look at how to uncover the important issues your community is ready and willing to discuss with you. 1. Your customers are your best source of intelligence. 2. Your sales team spends their time talking to customers and prospects. 3. Customer service and technical support reps know what the weak points are in your products and marketing materials. 4. While asking your customers direct questions is one way to get information from them, following them on Twitter and other social media platforms is a way to find out what’s really on their minds. 5. LinkedIn Groups can be a great source of content ideas. 6. 7. Search still drives significant traffic to many websites, and yours is not likely to be the exception. 8. 9.
Google's Knowledge Graph Has An Error 20% Of The Time Google’s knowledge graph which launched a little over a month ago is reportedly often wrong. Conductor ran a study showing that for trending terms, the knowledge Google is providing via their knowledge graph is wrong about 20% of the time. By trending, Conductor looked at the top 50 ‘people’ in Google Trends and Google Insights and 1 out of 5 of them had outdated or wrong information. For those in the Top 50 on Forbes’ Celebrity 100 list, Google is more often right, with only a 4% chance of the information being outdated. So combined, 12% of the answers in the knowledge graph are inaccurate according to Conductor. Brian Ussery this morning wrote how even Matt Cutts, Google’s head of search spam, entry has wrong information. Brian looked at how other Knowledge Graph entries are also wrong and then Conductor published their study showing the accuracy rate of the data in these knowledge graphs. Related Topics: Channel: SEO | Google: Knowledge Graph
The 7 steps in Big Data delivery Network World - This vendor-written tech primer has been edited by Network World to eliminate product promotion, but readers should note that it will likely favor the submitter's approach. The Big Data trend represents the evolving need to process large amounts of data with a new crop of technology solutions that aren't necessarily your father's database. So, what does a company need to consider when contemplating getting started with Big Data? First, they need to know what Big Data is. "The emerging technologies and practices that enable the collection, processing, discovery and storage of large volumes of structured and unstructured data quickly and cost-effectively." Big Data -- from financial trades to human genomes to telemetry sensors in cars to social media interactions to Web logs and beyond -- is expensive to process and store in traditional databases. MORE: Open source: Leading the way for big data applications ROUNDUP: 9 open source big data technologies to watch
5 QUESTIONS with Gnip Inc. CEO Jud Valeski Boulder-based Gnip Inc. specializes in gathering data from public social networks such as Twitter, Facebook and YouTube and providing real-time content to a variety of firms in industries such as social media monitoring, business intelligence, government and finance. CEO Jud Valeski spoke with the Camera recently about the company's current state, competition and direction. The following has been edited for clarity and space. 1. All of these different providers, all of these different consumers of the content use all of their own protocols and formats to communicate outward and inward to consumers. There's also a volume of content challenge, which is actually a bigger one. 2. There's this social cocktail and there are obviously a variety of different sources and a variety of different providers. ... 3. It's both a blessing and a curse. ... 4. We're 35 people now. 5. There's also a "what's old is new again" (shift). A big part of all of this is execution and people. -- Alicia Wallace
Jasper Soft eBook Five Levels of Embedded Bi PDF 16098 State Street’s Chief Scientist on How to Tame Big Data Using Semantics Semantic databases are the next frontier in managing big data, says State Street's David Saul. Financial institutions are accumulating data at a rapid pace. Between massive amounts of internal information and an ever-growing pool of unstructured data to deal with, banks' data management and storage capabilities are being stretched thin. But relief may come in the form of semantic databases, which could be the next evolution in how banks manage big data, says David Saul, Chief Scientist for Boston-based State Street Corp. The semantic data model associates a meaning to each piece of data to allow for better evaluation and analysis, Saul notes, adding that given their ability to analyze relationships, semantic databases are particularly well-suited for the financial services industry. "Our most important asset is the data we own and the data we act as a custodian for," he says. Using a semantic database, each piece of data has a meaning associated with it, says Saul. More Insights
Decomposing Twitter (Database Perspective) Twitter - one of the latest and hottest Web 2.0 trends used by millions of users around the world every day. How does it manage the enormous data produced by its users? This article reviews the technical aspects of the Twitter service, how it handles such a tremendous amount of tweets and other data, and looks at what we can learn from the findings. Twitter As we all know, Twitter, which launched its service in 2006, is expanding at an amazing pace. Simply put, the scale of service is amazing, but what is even more amazing is its growth rate. Understanding Twitter For those of us who are satisfied with sitting in the passenger seat, here is a brief outline of the services provided by Twitter. Twitter is a micro blogging service. Here are two core services of Twitter: One is to allow you to read (follow) the tweets of others in whom you are interested. Replied tweets can only be seen by users who follow both you and the owner of the original tweet. Real-Time Data in Twitter Tweets Timelines