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Computational Journalist? Stanford Has Your Ticket to Ride to Fame

October 6, 2015

Regular journalism going nowhere. After losing a job at a nifty PR agency, do you want to get back into the “real journalism” environment? Former newspaper person tired of writing baloney for enterprise and Big Data outfits?

Navigate to “Deep and Interesting Datasets for Computational Journalists: A Quick List.” Stanford University, birthplace of the Alphabet Google thing, has just what you need to ignite your career. Many interesting links; for example, Every thing and person paid for by Congressional office funds.

Now I did some work for a congress person, so I am not sure about the “every thing.” But, hey, it’s marketing even in academia.

Stephen E Arnold, October 6, 2015

Watson Weekly: Chasing Sales via Ads. Forget Thought Leadership

October 6, 2015

I was exploring the topics business intelligence and Big Data. I was intrigued by “Is Thought Leadership a Waste of Money?” My reaction was, “Nope, thought leadership is good.” Who wants to fool around with regular marketing methods.

What’s the write up say?

I highlighted this passage from a person who does not know about the genesis of Strategy & Business and the somewhat addled Booz, Allen executive who wanted a BAH branded Economist to generate revenue:

Once upon a time back in 1994, Joel Kurtzman, the then-editor-in-chief of Strategy & Business, coined the term “thought leader” as a means for identifying people within the business marketplace that merited our attention. Thought leaders were the individuals within their respective industries who offered fresh, creative ideas and commentary on industry problems and trends. Two decades later, much of today’s thought leadership has gone from original to repetitive. It’s not that business leaders, C-level executives, or entrepreneurs don’t have great ideas or valuable insights. The problem is a bit more complex.

But here’s the shocker. Strategy & Business was a reaction by Booz, Allen & Hamilton to publications and marketing campaigns mounted by other blue chip consulting firms.

Advertising, at least for blue chip firms, was somewhat low brow. The notion of pumping drivel into the in boxes of Fortune 1000 executives was also distasteful. Today advertising is the cat’s pajamas.

IBM is proving that nothing beats banging one’s own drum even if no one knows what the band is playing.

I opened my dead tree edition of the New York Times this morning )October 6, 2015), and what did I see? The work of Ogilvy & Mather? Sure looks like it. Big ad buy. Big images. Big assertions.

Cognitive computing via Watson. Yikes, where is the smarter planet? I did some poking around and came across “Tangled Up in Big Blue: IBM Replaces Smarter Planet With … Bob Dylan.”

IBM began to realize that the message of Smarter Planet — basically that computing is and will be integral to everything, as manifested in innovations such as smart power grids and connected cars — is no longer a differentiator for the business, explained Mr. Iwata. The emerging pattern, as harnessed and fostered by its Watson technology, is that these super computing capabilities can be built into anything digital because they live in the cloud.

IBM’s senior vice president of marketing Jon Iwata allegedly said:

“This will resonate strongly with not only our current clients but…companies and decision makers and software developers who aren’t currently IBM clients.”

The result in the dead tree newspapers I saw presented page upon page of IBM Watson marketing. Here are some of the pages from this morning’s print campaign in the New York Times and the Wall Street Journal:

ibm ad

The massive ad campaign reveals that Watson consists of 100 million lines of code. No comment about bugs counts, however.

Obviously, this snapshot is too small to read. Put down your smartphone and buy the dead tree newspapers. Here are the themes I noted:

  1. Buzzwords
  2. Components that you, gentle reader, can assemble like Potassium ferrocyanide in chem lab when the teacher is inattentive
  3. Images of youthful, diverse people who are obviously into Watson
  4. Copy, lots of copy.

The information recycles that which is available on the IBM Watson Web site. The difference is that the multi page ads are the equivalent of a Bunker Buster dropped into the somewhat indifferent world of search and content processing. How will the likes of minnows like Coveo, dtSearch, Elasticsearch (now Elastic), Recommind, Sinequa, legions of business analytics firms, the specialists pitching everything from indexing (Smartlogic) to semantics (SenseBot), and all manner of information access vendors scattered across a somewhat Martian like landscape. Sure, there may be water, but can one survive on the stuff?

IBM is skipping the thought leader thing and going right to big buck advertising. I can imagine this scenario taking place in Joe Coffee’s. The IBM marketing team is meeting with the ad agency’s equivalent of Bindy Irwin. The scene is a hip coffee shop near the Watson office in Manhattan.

IBM Watson Wizard (IWW): We need something big to get this Watson bandwagon rolling?

Mad Ave Ad Exec (MAAE): Yes, big. We need to do big.

IWW: Let’s brainstorm here? Do you want another cappuccino with the neat latte art?

MAAE: Sure, sure. But make mine a macchiato.

[IBM Watson executive returns with more cappuccino and one artisan cafe macchiato.]

IWW: Who wants the macchiato? What have you got for me?

MAAE: Okay, we have been talking while you were standing on line? By the way, do you want one of us to pay for the coffee?

IWW: Nah, we’ve got more than a billion to burn. Let’s get to it.

MAAE: Here’s the idea. Imagine putting the Watson cognitive computing message in front of every, and I mean every, New York Times and Wall Street Journal reader. We warm up with some Monday Night Football buys and then, bang, we hit the buyers with the message, “Cognitive computing.”

IWW: Well, print? What about viral videos? What about social media?

MAAE: We will do that. We can pay some mid tier consulting types to send out Watson tweets?

IWW: But that did not get any traction?

MAAE: Tweets are good. We need to provide a big bang to make the tweet thing happen.

IWW: What’s the message?

MAAE: We were thinking think. But 21st century style. We want to go with outthink thing.

IWW: Out think. I like it.

MAAE: Now picture this. You know how everyone learned about chemical symbols in high school?

IWW: Yes, but I got a D.

MAAE: No problem. Here’s the picture. [Ad person grabs napkin and sketches a hexagon with a happy face.

ibm happy face

We show the components of the Watson system as little chemical symbols with codes in them.

IWW: Symbols? Codes? It looks like a happy face with an F in it.


MAAE: Grab your mental iPhone. Snap this happy icon with the Fd. You see “face detection.” Fd. Crystal clear. Non verbal. Immediate.

IWW: I don’t understand.

MAAE: Work with me on this. We make a list of the APIs and the buzzwords and put them into a graphic. We call the page “IBM Watson is the platform for cognitive business.”

IWW: Oh, like the structures computational chemists use to visualize complex constructs?

MAAE: What’s a computational structure whatever? I know a happy face thing with a hexagon. This gets the message across. Zap. Like an Instagram, right?

IWW: I get it. I get it.

MAAE: You like it, right? Big bang. Big splash. Big message but simple, clear, easy to grasp.

IWW: How many New York Times and Wall Street Journal readers know what API means?

MAAE: We’ve grab the upside. Wait for it. We will hook the Watson cognitive thing with a superstar. We are thinking Bob Dylan.

IWW: Bob Dylan. I remember him. Butwasn’t there some talk about drugs, political activism, maybe something with Croatia in France?

MAAE: Ancient history and myth. He’s an icon. Picture this. Bob Dylan becomes the image of cognitive computing. Can’t miss. Cannot miss. Winner. We become the messaging for API. Watson APIs will be huge. The chatter about text extraction, image tagging, and concept expansion. Deafening.

IWW: Wow, that sounds almost as powerful as the Jeopardy game show promotion. I really liked that game show thing. Watson won too.

MAAE: Right. That’s the value of post production. Now. One final point. Jules here came up with a great idea while you were waiting on line. We take the rock solid facts about Watson. Jules thinks this was your idea, and it is a great one. Watson. Only 100 million lines of code, you know, more than in a Volkswagen-type fuel emission system. We sprinkle these facts under a headline like “A cognitive business is a business that thinks.” Stir in Dylan and you can write your own ticket in this cognitive computing thing.

IWW: But what about outthink thing? You said the new hook was outthink.

MAAE: Yes, yes, outthink is the glue. Cognitive API outthink. Huge. I will send a contract over to you later today.

IWW: Do you think we will make any sales?

MAAE: Sales? Sure, sure. Winner. Be sure to turn around that contract. We need to get rolling like a rolling stone. Winner.

What other boosters did Watson receive on October 6, 2015. Well, the IBM Big Blue Boss is on CNBC. Not as perky as Bindy, but pretty excited about granting CNBC an exclusive.

One question: What about revenues? You know three years of declining revenue.

Stephen E Arnold, October 6, 2015





Stephen E Arnold, October 6, 2015

Yandex TweetedTimes Is Back for Now

October 6, 2015

I noted about a week ago that Tweeted Times, now part of the Yandex operation, was dark. My magic pinger alerted me that the service is back up again as of October 5, 2015. I look forward to more tweets collected under such headings as Law Experts (aren’t all attorneys experts?) and Matt Cutts (yep, the Google “SEO is neither good nor bad specialist). Enjoy

Stephen E Arnold, October 6, 2015

Business Intelligence and Data Science: There Is a Difference

October 6, 2015

An article at the SmartDataCollective, “The Difference Between Business Intelligence and Real Data Science,” aims to help companies avoid a common pitfall. Writer Brigg Patton explains:

“To gain a competitive business advantage, companies have started combining and transforming data, which forms part of the real data science. At the same time, they are also carrying out Business Intelligence (BI) activities, such as creating charts, reports or graphs and using the data. Although there are great differences between the two sets of activities, they are equally important and complement each other well.

“For executing the BI functions and data science activities, most companies have professionally dedicated BI analysts as well as data scientists. However, it is here that companies often confuse the two without realizing that these two roles require different expertise. It is unfair to expect a BI analyst to be able to make accurate forecasts for the business. It could even spell disaster for any business. By studying the major differences between BI and real data science, you can choose the right candidate for the right tasks in your enterprise.”

So fund both, gentle reader. Patton distinguishes each position’s area of focus, the different ways they use and look at data, and  their sources, migration needs, and job processes. If need to hire someone to perform these jobs, check out this handy clarification before you write up those job descriptions.

Cynthia Murrell, October 6, 2015

Sponsored by, publisher of the CyberOSINT monograph

Full Text Search Gets Explained

October 6, 2015

Full text search is a one of the primary functions of most search platform.  If a search platform cannot get full text search right, then it is useless and should be tossed in the recycle bin.    Full text search is such a basic function these days that most people do not know how to explain what it is.  So what is full text?

According to the Xojo article, “Full Text Search With SQLite” provides a thorough definition:

“What is full text searching? It is a fast way to look for specific words in text columns of a database table. Without full text searching, you would typically search a text column using the LIKE command. For example, you might use this command to find all books that have “cat” in the description…But this select actually finds row that has the letters “cat” in it, even if it is in another word, such as “cater”. Also, using LIKE does not make use of any indexing on the table. The table has to be scanned row by row to see if it contains the value, which can be slow for large tables.”

After the definition, the article turns into advertising piece for SQLite and how it improves the quality of full text search.  It offers some more basic explanation, which are not understood by someone unless they have a coding background.   It is a very brief with some detailed information, but could explain more about what SQLite is and how it improves full text search.

Whitney Grace, October 6, 2015
Sponsored by, publisher of the CyberOSINT monograph

Video Traffic Magnitude

October 5, 2015

Short honk: I read “Facebook v. Google in Digital Video Battle: YouTube Is 11X Bigger.” The big factoid is in the headline: Facebook is a fraction of the size in terms of traffic than YouTube. A couple of thoughts: How rapidly is Facebook growing in video content compared to YouTube? What is Facebook’s monetization opportunity compared to the Alphabet Google’s opportunity? The chit chat I have heard is that Facebook’s growth in the last 18 months is more rapid that the Alphabet Google video revenue growth? I also have a suspicion that socially anchored monetization may generate a more stable stream of revenue for Facebook. My question, however, is, “When will Facebook surpass YouTube in revenue from video?”

Stephen E Arnold, October 5, 2015

Search Engine Optimization: Get Out Your Checkbook

October 5, 2015

No traffic? Low traffic? No mobile traffic? Can’t find your site on Bing or Google?

If these questions poke your marketing nerve, you may consider hiring an “expert” to help you out. Most of the traffic and “find you in Google” specialists are doing business as SEO experts. Personally I would skip the SEO baloney and just buy traffic love via Google Adwords.

Search engine optimization is a catch all to address expensive Web sites which no one visits. Yikes. Considering that most traffic on the Web flows to five percent of the billion plus Web sites, traffic to a personal or small business Web site is terrible.

What’s the fix?

The SEO crowd wants you to spend money with them, not Adwords. Google’s approach is different. The company wants to sell you traffic. The two ideas are intertwined, but you would not know this by reading “How Much Does Good SEO Cost?”

The write up summarizes a number of ball park costs; for example:

  • Hire a full time employee: Maybe $50,000 to $100,000. How’s that fit your budget, gentle reader.
  • Hire an agency: No cost given. Use your imagination.
  • Hire a dedicated SEO firm: No cost given. Use your imagination again.

But the way to go is to set aside money for an expert consultant / practitioner. At each stair step, the customer gets more SEO goodness. Exactly what the payoff is, is not clear to me. But here are the suggested price levels spelled out in the write up:

  • Put folks on a monthly retainer. Less than $500 per month. Cheaper than a daily Starbuck’s coffee
  • A retainer for $1,000 to $5,000 per month: This is SEO hog heaven for an outfit with 10 clients, the SEO wizard may generate more free cash than your business
  • $5,000 to $10,000 per month: “Ambitious goals”. You bet
  • $10,000 to $20,000 per month: The owners will retire early if their customers pay their bills.

The canny business owner in search of SEO love can sign a contract. This is interesting. Here are the price points from the article which I assume are based on thorough research in fees charged by a statistically valid sample of SEO firms. (Somehow I question the rigor of the information gathering process.) Let’s look at the benchmarked fees:

  • Link profile audits: $2,500 to $7,500
  • SEO / Web site audits: $2,500 to $7,500 or higher, gentle reader
  • Link building: $250 to $2,000 per link. Wowza
  • Per page optimization and implementation: $100 to $250. (Fascinating since some content management systems make per page operations pretty darned exciting for a skilled programmer. For dabblers, think about downtime, gentle reader.)
  • Copywriting: $0.75 to $1.00 per word.

If you are on a budget, you can hire a consultant for an hour; for example, a $100 to $300 fee seems to be normal. Keep in mind that there are roughly 2,000 billable hours per year, so this fee range is designed to compensate an expert in SEO at a minimum of  $200,000 per year. Ready to abandon your day job, gentle reader?

Now these costs spark several thoughts in this addled goose’s mind.

First, exactly what is the payoff from SEO versus spending the money for Google Adwords?

Second, what specific changes the SEO expert makes results in “more” traffic, likes, or whatever? How is an SEO action tied to a payoff?

Third, what happens to the client’s Web site if the SEO activity gets the site down checked, blackballed, or less traffic?

Dear old Google wants folks to make Web sites so it takes Google as little computing time as possible to index the site, extract data, and do all the Googley things which makes me love the company so darned much.

My experience is that making a change to a site or putting up a new site leads to a bit of Google love. After a couple of indexing cycles, the traffic declines. Desperate site owners embrace SEO. After that doesn’t work, the road leads back to buying traffic via Adwords.

Thus, the Google likes anything that does not work as well as buying traffic.

Perhaps the SEO crowd should just sell Adwords? But that may not be as lucrative or create opportunities for the client to engage in the “Why isn’t your work producing traffic meetings?” I bet those are fun and inevitable too.

Stephen E Arnold, October 5, 2015

LinkedIn: Searching for Something

October 5, 2015

LinkedIn is aimed at several different audiences. Each is interdependent just like the tree of life in my 9th grade biology text book. I want to use the word symbiotic, but I keep thinking of parasitic.

LinkedIn appeals to organizations who want to hire people to help generate revenues. The people looking for work use LinkedIn to find full time, part time, or any time labor. The companies selling products and services are looking at the companies as customers. The people looking for work are eager to demonstrate their money making potential.

The result is a maelstrom of people, posts, chat groups, and marketing.

LinkedIn, according to the write up “LinkedIn Agrees to Settle Unwanted Email Lawsuit,” reports:

LinkedIn was announcing that it had agreed to settle a class-action lawsuit over sending unwanted emails. The lawsuit revolves around LinkedIn’s Add Connections feature, which would send out connection requests to people in a user’s contact list who did not already have a LinkedIn account. Users had to agree to send out that first connection request, but LinkedIn would then follow up with up to two more “reminder emails” if there was no response. The lawsuit alleges that users did not consent to LinkedIn sending those additional emails, nor give LinkedIn permission to use their names and images in them.

We’ll see. I have received some interesting LinkedIn emails since one of the goslings set up an account, posted the titles of some of my articles, and began to fill in some of the information LinkedIn requires its “members” to provide. I think the picture of me dates from the 1990s. I am not sure because I rely on a couple of people to read messages and do the housekeeping required of a “person” who uses the service for free.

The LinkedIn mail goes directly into a junk folder. If something surfaces, one of the goslings alerts me. If I have the zip, I suggest a way to respond. I think I offered a Latin quip in response to one company’s blabbing about its superior ranking awarded by a mid tier consulting company. Okay, just not the big leagues, was it. The quip, which I dictated from memory, suggests that tooting one’s horn can be annoying.

That Latin quote from Martial who died in 101 CE, elicited emails, gossip at conferences, and a personal email enjoining me to be a much kinder and gentler goose. I told the goslings to use their judgment.

I also received an email from a person whom I did not know wanting to buy me dinner at the best restaurant in Louisville, Kentucky. Is that an oxymoron. Lyon maybe. But Louisville, not unless I know the person. I am not exactly angling for trouble. When my suggestion of a phone call did not work out, the stranger offered to hook me up with a colleague when I was in Montréal. Well, that’s pretty stupid. If I won’t meet a stranger where I live, what are the chances I will meet a stranger in a foreign country? One of the goslings pointed out to the LinkedIn member who was the motor in this meet up drifting that his résumé on LinkedIn left out some of his employment history. Technologist? Nope, sales person. The response the person sent to my “persona” was, “Never write me again.” Er, who started the email chain. Was this person stalking me? Was this person looking for a job? Is this person aberrant? I took no chances with a free meal at the Dizzy Whiz.

Then there was a person who wanted to code up her own enterprise search system. I wrote back and suggested the person use either an open source or commercial system. The likelihood of losing her job would be reduced. The offended LinkedIn member located my “real” email address and wrote me a nastygram about my failure to recognize the capabilities of females in the technical world. Well, okay.

Weekly I receive offers to get a month free of the “real” LinkedIn. I get notices of thought leaders’ musings posted to LinkedIn. I receive emails which I have never opened. Junk remember. Some of these emails are from people who want to be my friend.

I don’t know about you, but it shows pretty poor judgment to chase a person who is 71 years old, appearing on LinkedIn as part of project that ended three or four years ago, and whose participation is handled by intermediaries.

My take on the LinkedIn service is that it is probably useful for people who want to network, job hunt, locate customers, and preen their features.

Pumping out unwanted emails is obviously not something that one court thought was okay. There are some other issues with the company as well. One of the goslings told me that listing articles I have written on my bio page is really obtuse.

There you go. My hunch is that LinkedIn finds customers for the data it has harvested from the young seeds planting content in the system. Perhaps LinkedIn will buy Peeple.

And have you ever tried to search LinkedIn? One of the goslings found the information access system wanting. Why? Well, email takes priority.

Stephen E Arnold, October 5, 2015

Visual Analytics Makes Anyone a Data Expert

October 5, 2015

Humans are sight-based creatures.  When faced with a chunk of text or a series of sequential pictures, they will more likely scan the pictures for information than read.  With the big data revolution, one of the hardest problems analytics platforms have dealt with is how to best present data for users to implement.  Visual analytics is the key, but one visual analytics is not the same as another.   DCInno explains that one data visual company stands out from the rest in the article, “How The Reston Startup Makes Everyone A Big Data Expert.”

Zoomdata likes to think of itself as the one visual data companies that gives its clients a one up over others and it goes about it in layman’s terms.

“Zoomdata has been offering businesses and organizations a way to see data in ways more useful than a spreadsheet since it was founded in 2012. Its software offers real-time and historical explorations of data streams, integrating multiple sources into a cohesive whole. This makes the analytics far more accessible than they are in raw form, and allows a layperson to better understand what the numbers are saying without needing a degree in mathematics or statistics.”

Zoomdata offers a very interactive platform and is described to be the only kind on the market.  Their clients range from government agencies, such as the Library of Congress, and private companies.  Zoomdata does not want to be pigeonholed as a government analytics startup.  Their visual data platform can be used in any industry and by anyone with the goal of visual data analytics for the masses.  Zoomdata has grown tremendously, tripled its staff, and raised $22.2 million in fundraising.

Now let us sit back and see how their software is implemented in various industries.  I wonder if they could make a visual analytics graphic novel?
Whitney Grace, October 5, 2015
Sponsored by, publisher of the CyberOSINT monograph

Google Express Pales in Comparison to Amazon Prime

October 5, 2015

The article on Business Insider titled Google Should Be Very Scared of What Amazon Built, According to Investor Bill Gurley, details Gurley’s comments. Amazon Prime, according to Gurley, is challenging Google’s top dog position by offering inventory in addition to search capabilities. Shopping on Google might seem like a waste of time to many Prime members, who go directly to Amazon to search for what they are looking for. The article explains,

“Over many years, Amazon has built up this logistics framework and their one click feature and their Prime program to the point where the consumer has zero anxiety about the quality of the product, immense trust about the deliverability, down to a day and a half for most people, less than a day for some items. They trust on price. That doesn’t mean they are the absolute lowest price, but people don’t think Amazon’s trying to get ’em.”

Gurley estimates that Amazon may have as many as 90 million Prime Members loyal to their search engine for shopping, and using Google only as a last resort. Google Express, which most of us have never heard of, was Google’s “lame” answer to Amazon Prime, but without the years of planning and creating worldwide distribution centers. However, the article does not address that people use Google for quite a bit more than shopping, and Amazon Prime is limited that way.

Chelsea Kerwin, October 5, 2015

Sponsored by, publisher of the CyberOSINT monograph

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