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jerryking : social_data   20

Sandy Pentland on the Social Data That Business Should Use - WSJ
Feb. 10, 2014 | Journal Report - CIO Netowrk| WSJ's Steve Rosenbush speaking with MIT's Sandy Pentland.

MR. ROSENBUSH: For most of us, social data is Twitter, it's Facebook. What do you mean by it?

MR. PENTLAND: Those sorts of things are people's public face. On the other hand, for instance, there's badge data. Every corporation has name badges. Many of these record where people come and go, door swipes and things like that. That's a different type of social media. Or if I look at cellphone data, I can tell when people get together, what they search for, who they talk to. You can look at connections between people in ways you never could before. The way most people approach this is incorrect, because they're asking questions about individuals. A better way to approach is asking questions about interactions between people.
social_data  interpretation  Twitter  interactivity  Facebook  social_physics  Communicating_&_Connecting  informed_consent  location_based_services  data  massive_data_sets  contextual  LBMA 
february 2015 by jerryking
Let me see
Posted by Seth Godin on July 08, 2008.

Passive contributions of public behaviour information to traditionally-sorted data
data  ideas  information  inspiration  Seth_Godin  social_data  datasets  open_data  social_physics  massive_data_sets  wisdom_of_crowds  thick_data  public_behavior  sorting  value_creation 
january 2015 by jerryking
The Data Companies Wish They Had About Customers - WSJ
March 23, 2014 | WSJ | by Max Taves.

We asked companies what data they wish they had—and how they would use it. Here's what they said....
(A) Dining----Graze.com has a huge appetite for data. Every hour, the mail-order snack business digests 15,000 user ratings about its foods, which it uses to better understand what its customers like or dislike and to predict what else they might like to try...more data could help him understand customers' tastes even better. Among the information he wants most is data about customers' dietary habits, such as what they buy at grocery stores, as well as better information about what they look at on Graze's own site. And because the dietary needs of children change rapidly, he'd like to know if his customers have children and, if so, their ages.
(B) Energy-----Energy consumption is among its customers' main concerns, says CEO William Lynch. For instance, the company offers a product giving homeowners the real-time ability to see things like how many kilowatts it takes to heat the hot tub in Jan. Because of privacy concerns, Savant doesn't collect homeowners' energy data. But if the company knew more about customers' energy use, it could help create customized plans to conserve energy. "We could make recommendations on how to set up your thermostat to save a lot of money,
(C) Banking-----the Bank of the West would like "predictive life-event data" about its customers—like graduation, vacation or retirement plans—to create products more relevant to their financial needs...At this point, collecting that breadth of data is a logistical and regulatory challenge, requiring very different sources both inside and outside the bank.
(D) Appliances-----Whirlpool Corp.has a vast reach in American households—but wants to know more about its customers and how they actually use its products. Real-time use data could not only help shape the future designs of Whirlpool products, but also help the company predict when they're likely to fail.
(E) Healthcare----Explorys creates software for health-care companies to store, access and make sense of their data. It holds a huge trove of clinical, financial and operational information—but would like access to data about patients at home, such as their current blood-sugar and oxygen levels, weight, heart rates and respiratory health. Having access to that information could help providers predict things like hospitalizations, missed appointments and readmissions and proactively reach out to patients,
(F) Healthcare----By analyzing patient data, Carolinas HealthCare System of Charlotte, N.C., can predict readmission rates with 80% accuracy,
(G) Law----law firms that specialize in defense work are typically reactive, however some are working towards becoming more proactive, coveting an ability to predict lawsuits—and prevent them.How? By analyzing reams of contracts and looking for common traits and language that often lead to problems.
(H) Defense---BAE Systems PLC invests heavily in protecting itself from cyberattacks. But it says better data from its suppliers could help improve its defenses...if its suppliers get cyberattacked, its own h/w and s/w could be compromised. But "those suppliers are smaller businesses with lesser investments in their security," ...A lack of trust among suppliers, even those that aren't direct competitors, means only a small percentage of them disclose the data showing the cyberattacks on their systems. Sharing that data, he says, would strengthen the security of every product BAE makes. [BAE is expressing recognition of its vulnerability to network risk].
data  data_driven  massive_data_sets  Graze  banking  cyber_security  BAE  law_firms  Whirlpool  genomics  social_data  appliances  sense-making  predictive_analytics  dark_data  insights  customer_insights  real-time  design  failure  cyberattacks  hiring-a-product-to-do-a-specific-job  network_risk  shifting_tastes  self-protection  distrust  supply_chains 
november 2014 by jerryking
M.I.T.'s Alex Pentland: Measuring Idea Flows to Accelerate Innovation - NYTimes.com - NYTimes.com
April 15, 2014 | NYT | By STEVE LOHR.

Alex Pentland --“Social Physics: How Good Ideas Spread — The Lesson From a New Science.”

Mr. Pentland has been identified with concepts — and terms he has coined — related to the collection and interpretation of all that data, like “honest signals” and “reality mining.” His descriptive phrases are intended to make his point that not all data in the big data world is equal....Reality mining, for example, examines the data about what people are actually doing rather than what they are looking for or saying. Tracking a person’s movements during the day via smartphone GPS signals and credit-card transactions, he argues, are far more significant than a person’s web-browsing habits or social media comments....Central to the concept of social physics is the ability to measure communication and transactions as never before. Then, that knowledge about the flow of ideas can be used to accelerate the pace of innovation.

The best decision-making environment, Mr. Pentland says, is one with high levels of both “engagement” and “exploration.” Engagement is a measure of how often people in a group communicate with each other, sharing social knowledge. Exploration is a measure of seeking out new ideas and new people.

A golden mean is the ideal....[traders] with a balance of diversity of ideas in their trading network — engagement and exploration — had returns that were 30 percent ahead of isolated traders and well ahead of the echo chamber traders, too....The new data and measurement tools, he writes, allow for a “God’s eye view” of human activity. And with that knowledge, he adds, comes the potential to engineer better decisions in a “data-driven society.”
Alex_Pentland  books  cross-pollination  curiosity  data_scientists  data_driven  decision_making  massive_data_sets  MIT  Mydata  sensors  social_physics  Steve_Lohr  idea_generation  heterogeneity  ideas  intellectual_diversity  traders  social_data  signals  echo_chambers 
april 2014 by jerryking
Twitter Acquires Gnip, Bringing a Valuable Data Service In-House - NYTimes.com - NYTimes.com
April 15, 2014 | NYT | By ASHWIN SESHAGIRI.

In 2010, Gnip was the first company to work with Twitter to gain access to the social network’s so-called fire hose, which contains all publicly available tweets since 2006. Brands, advertisers and, recently, academics could use that stream of data to analyze and parse activity on the social network....Last year, Apple acquired Topsy Labs, a similar provider of data of Twitter activity. The terms of that deal were also not disclosed, though The Wall Street Journal, citing people familiar with the matter, estimated the deal to be worth more than $200 million.

“We believe Gnip has only begun to scratch the surface,” Jana Messerschmidt, Twitter’s vice president of global business development and platform, wrote in a blog post announcing the deal. “Together we plan to offer more sophisticated data sets and better data enrichments, so that even more developers and businesses big and small around the world can drive innovation using the unique content that is shared on Twitter.”
Twitter  Gnip  massive_data_sets  mergers_&_acquisitions  data  data_mining  sentiment_analysis  social_media  social_data 
april 2014 by jerryking
The Power of 'Thick' Data - WSJ.com
By
Christian Madsbjerg and
Mikkel B. Rasmussen
March 21, 2014

companies that rely too much on the numbers, graphs and factoids of Big Data risk insulating themselves from the rich, qualitative reality of their customers' everyday lives. They can lose the ability to imagine and intuit how the world—and their own businesses—might be evolving. By outsourcing our thinking to Big Data, our ability to make sense of the world by careful observation begins to wither, just as you miss the feel and texture of a new city by navigating it only with the help of a GPS.

Successful companies and executives work to understand the emotional, even visceral context in which people encounter their product or service, and they are able to adapt when circumstances change. They are able to use what we like to call Thick Data.
thick_data  massive_data_sets  Lego  ethnography  visceral  storytelling  social_data  observations  Samsung  consumer_research  imagination  skepticism  challenges  problems  sense-making  emotions  contextual 
march 2014 by jerryking
Kabbage s Fresh Idea for Small Business Finance - American Banker Magazine Article
Glen Fest
JUN 1, 2013

For the past three years, Atlanta-based Kabbage has used social media analytics in part to quantify a borrower's propensity to repay. The underlying logic, says chairman and co-founder Marc Gorlin, is that a small business actively promoting itself or receiving customer attention through these channels is a better risk candidate than a less socially savvy merchant even with a similar credit score and product line....Whereas a bank would require extensive and audited financial data, says Scott Thompson, the former PayPal president and Yahoo! ex-CEO who was recently appointed to Kabbage's board, Kabbage "offers up this very simple signup flow," where the application and approval process can take less than seven minutes.

"What they've done is they've assembled a richer set of data, they have better technology, better science, better attributes, and are looking at better signals to try to attempt to get a current understanding of what your small business is," Thompson says.
massive_data_sets  data  data_driven  Kabbage  unstructured_data  social_media  social_data  online_banking  small_business  Facebook  Twitter 
february 2014 by jerryking
How should we analyse our lives? - FT.com
January 17, 2014 | FT |Gillian Tett.

“Social physics helps us understand how ideas flow from person to person . . . and ends up shaping the norms, productivity and creative output of our companies, cities and societies,” writes Pentland. “Just as the goal of traditional physics is to understand how the flow of energy translates into change in motion, social physics seems to understand how the flow of ideas and information translates into changes in behaviour.”...The only question now is whether these powerful new tools will be mostly used for good (to predict traffic queues or flu epidemics) or for more malevolent ends (to enable companies to flog needless goods, say, or for government control). Sadly, “social physics” and data crunching don’t offer any prediction on this issue, even though it is one of the dominant questions of our age......data are always organised, collected and interpreted by people. Thus if you want to analyse what our interactions mean – let alone make decisions based on this – you will invariably be grappling with cultural and power relations.
massive_data_sets  social_physics  data_scientists  quantified_self  call_centres  books  data  social_data  flu_outbreaks  Gillian_Tett  queuing 
january 2014 by jerryking
Twitter's Lucrative Data Mining Business - WSJ.com
October 6, 2013 | WSJ | By ELIZABETH DWOSKIN.

Twitter's Data Business Proves Lucrative
Twitter Disclosed It Earned $47.5 Million From Selling Off Information It Gathers

Twitter's data business has rippled across the economy. The site's constant stream of experiences, opinions and sentiments has spawned a vast commercial ecosystem, serving up putative insights to product developers, Hollywood studios, major retailers and—potentially most profitably—hedge funds and other investors....Social-data firms spot trends that it would take a long time for humans to see on their own. The United Nations is using algorithms derived from Twitter to pinpoint hot spots of social unrest. DirecTV DTV +0.99% uses Twitter data as an early-warning system to spot power outages based on customer complaints. Human-resources departments analyze the data to evaluate job candidates....While estimates of the market value of the social-data industry are hard to come by, one research firm, IDC, estimates that the entire "big data" market has grown seven times as quickly as the information technology sector as a whole. It may be valued at $16.9 billion in two years....Each social-data firm boasts proprietary dating-mining tools that go beyond basic keyword searches. Some can zoom in on a subset of people—say, women in a certain ZIP Code—and monitor phrases that show emotion. Then they can create a heat map or a sentiment score that measures how that subset feels about a topic. They have trained natural language processing algorithms to look at slang and broken grammar and to highlight tweets that indicate urgency because of words like "BREAKING."

"We don't just count the volume of these trends. That's naïve," says Nova Spivak, CEO of the Los Angeles-based firm Bottlenose. Rather, his firm looks at the momentum of trends....Many smaller analytics startups are now turning to four companies that Twitter has dubbed "certified data resellers." These brokers, Gnip, Data Sift, Topsy and the Japanese firm NTT Data, 9613.TO -2.04% account for the bulk of Twitter's data revenue. Last year, they paid Twitter monthly fees of about $35.6 million.

Twitter's exponential growth has meant its influence extends well beyond marketing and crisis PR. Nonprofits, human-resource managers and politicians have found Twitter data useful, too.
data  data_mining  Twitter  massive_data_sets  sentiment_analysis  product_development  social_media  social_data  Gnip  Data_Sift  Topsy  NTT_Data  Bottlenose  NLP  hotspots  UN  human_resources  insights  Hollywood  hedge_funds  momentum 
october 2013 by jerryking
New takes on data spawn new businesses - FT.com
January 15, 2013 | FT | By Brian McKenna.

DataSift, based in San Francisco in the US and Reading in the UK. It aims to help organisations improve their understanding and use of social media.

Kabbage, is an online lender to small businesses;

Big data does not just mean a lot of information. It also refers to so-called unstructured data – sensor data, social media outpourings, video and images – that does not fit neatly into the rows and columns of most databases.....

“What if one of the large online marketplaces bought a credit company? What would they do with it? They’d give cash to the businesses that were generating their online revenue. That was the germ of Kabbage,” he says.

From application to cash in the bank for small, mostly online, companies takes seven minutes. Kabbage monitors its borrowers by linking to and watching their private data sources: bank accounts, Twitter feeds, eBay and Facebook accounts, among others. Interest rates are between 2-18 per cent. The company’s 90,000 accounts are mostly in the US, but it is planning a UK launch in February.
massive_data_sets  data  data_driven  new_businesses  Kabbage  unstructured_data  DataSift  online_banking  product_launches  social_data  alternative_lenders  alternative_lending 
april 2013 by jerryking
How Big Data Is Changing the Whole Equation for Business - WSJ.com
March 8, 2013 | WSJ | By STEVEN ROSENBUSH AND MICHAEL TOTTY.

Big data often gets linked to companies that already deal in information, like Google, GOOG -0.13% Facebook FB -2.16% and Amazon. But businesses in a slew of industries are putting it front and center in more and more parts of their operations. They're gathering huge amounts of information, often meshing traditional measures like sales with things like comments on social-media sites and location information from mobile devices. And they're scrutinizing it to figure out how to improve their products, cut costs and keep customers coming back.
massive_data_sets  social_data  social_media  social_physics 
march 2013 by jerryking
Data Is the World
Aug 1, 2005 | Inc.com | Michael S. Hopkins.

Use your data. "Companies aren't taking advantage of the data they generate, Levitt says. "Often, data generated for one purpose is useful for another. Freakonomics describes the case of an entrepreneur selling bagels in corporate offices who kept meticulous records to track profits and loss—data that eventually yielded insights about white-collar crime and the effects of office size on honesty.
Ask different questions. The abortion-crime link revealed itself when Levitt thought to stop asking what made crime fall and try asking why it had risen so much in the first place. That led him to justice system practices in the 1960s, which led him to a statistical understanding of which individuals were likeliest to commit crimes, and ultimately to the question of why a large segment of that population seemed to have vanished.
Don't mistake correlation for causality. Innovative policing and a drop in crime happened simultaneously, but data proved the one didn't cause the other. (Be mindful of the feudal king who, having learned disease was greatest in regions with the most doctors, figured that reducing doctors would reduce disease.)
Question conventional wisdom. An idea that is both easy to understand and a source of comfort (such as the credit quickly given to innovative policing for cutting crime) should be especially suspect.
Respect the complexity of incentives. "You can't imagine, says Levitt, "all the ways humans will connive to beat a system.
Employ data against cheating. Just as companies don't sufficiently capitalize on the data they have access to, they aren't exploiting what Levitt calls "opportunities to think about fraud or theft in their businesses.
'60s  bank_shots  causality  cheating  conventional_wisdom  correlations  data  data_driven  exhaust_data  Freakonomics  gaming_the_system  incentives  insights  justice_system  massive_data_sets  metadata  oversimplification  questions  skepticism  social_data  Steven_Levitt  theft  think_differently  white-collar_crime 
january 2013 by jerryking
McKinsey's data whiz mines the social media motherlode
May. 25, 2012 | ROB Magazine - The Globe and Mail | Simon Houpt.

What is "Big Data"?...Let me give it a try. It’s the use of massive sets of data—typically transaction data, motivation data, environmental data, social data—to make better business decisions.
McKinsey  massive_data_sets  Simon_Houpt  Amazon  privacy  social_data  social_media 
may 2012 by jerryking
Twitter sells your feed to Big Data - The Globe and Mail
Mar. 01, 2012 |Reuters| by Mitch Lipka.

Boulder, Colorado-based Gnip Inc. and DataSift Inc., based in the U.K. and San Francisco, are licensed by Twitter to analyze archived tweets and basic information about users, like geographic location. DataSift announced this week that it will release Twitter data in packages that will encompass the last two years of activity for its customers to mine, while Gnip can go back only 30 days.
Twitter  Gnip  massive_data_sets  data_scientists  commercialization  DataSift  social_data 
march 2012 by jerryking
Data markets aren't coming. They're already here
26 January 2011 | O'Reilly Radar| by Julie Steele.

Jud Valeski is cofounder and CEO of Gnip, a social media data provider
that aggregates feeds from sites like Twitter, Facebook, Flickr,
delicious, and others into one API.

Jud will be speaking at Strata next week on a panel titled "What's Mine
is Yours: the Ethics of Big Data Ownership."
Find out more about growing business of data marketplaces at a "Data
Marketplaces" panel with Ian White of Urban Mapping, Peter Marney of
Thomson Reuters and Dennis Yang of Infochimps.

What do you wish more people understood about data markets and/or the
way large datasets can be used?

Jud Valeski: First, data is not free, and there's always someone out
there that wants to buy it. As an end-user, educate yourself with how
the content you create using someone else's service could ultimately be
used by the service-provider. Second, black markets are a real problem,
and just because "everyone else is doing it" doesn't mean it's okay.
markets  data  analytics  massive_data_sets  digital_economy  content_creators  black_markets  Infochimps  Gnip  Thomson_Reuters  commercialization  data_scientists  data_marketplaces  social_data  financial_data 
may 2011 by jerryking
The Social Data Revolution(s) - Now, New, Next -
4:58 PM Wednesday May 20, 2009 | HarvardBusiness.org | blog post by Andreas Weigend
data  social_data  customers  marketing  online_marketing 
june 2009 by jerryking

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