Methbot: the Method by Which Russians Are Stealing Millions of Digital Advertising Dollars From Advertisers and Publishers Every Day

Here we present the last of the articles which relate to the horrors Facebook has helped unleash on the world that my company, the Joss Group, published in the now defunct Digital Marketing Report newsletter. In this article, originally published in the January 2017 issue, we present a harrowing tale of theft on a dizzying scale.

When you read the article, I want you to think about what Putin might be doing with this money and how the same approach used to steal advertising dollars could be used to attack social media networks and followers. I promise you, too, that anything you come up with is nothing compared to what is really going on. Harrowing is the watch word…

I have pasted in below a JPEG of each of the pages from the issue with this article. Please let me know if you’d like to see a PDF of the issue. In addition, please do read the full report from WhiteOps; here is the link to the background information: https://www.whiteops.com/methbot. The link for accessing the full report is in the background information.

Our article begins, “If this story had broken a few years ago, the company which broke open the story might have called it Ad Theft on Steroids or some such. Given the changes in popular culture, the reference made to methamphetamine in the WhiteOps special report on the latest, and most devastating to-date, of digital advertising theft operations is entirely current and apt. What WhiteOps first told the world about in late December 2016 is, indeed, theft on a dizzying scale.”

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Facebook Should be Worried About the FTC and Here is Why

Last week several news outlets, including the Washington Post, ran articles saying the Federal Trade Commission (FTC) is investigating Facebook, and a few days later the FTC officially confirmed the reports. Most of the articles said the FTC is looking into how Facebook has been butchering an agreement the FTC reached with the company back in 2011 regarding Facebook’s mis-use of user data back then. If the FTC concludes Facebook ignored the agreement, it could fine the company tens of thousands of dollars for each incident.

First, though, let me make my position clear. I am not a fan of Facebook and have long consider it a digital blight on the world. I do not and never have had a presence on Facebook as I realized, years and years ago, the main function of  the company and its main source of revenue is gathering and selling information about people using the social media platform. I have been telling people about my reasoned suspicions for years, too.

Mark my words: there is nothing good about Facebook.

I support, completely, the #DeleteFacebook movement.

I am convinced more and more and more information will be coming out in the next few days, weeks, and years about how Facebook has been collecting and selling information about people and also using that information on behalf of nefarious clients to help persuade and yes, even deceive, Facebook users.

We have only glimpsed, so far, the top of the tip of the iceberg on what has been going on with Facebook and Cambridge Analytica (CA), and this is only one of Facebook’s clients of this ilk.

Back to the FTC: I believe the FTC will also come to the conclusion Facebook has been involved in deceptive advertising practices, and once it does, I hope the agency takes considerable legal action against Facebook.

In January 2016 we published an article in the Digital Marketing Report newsletter about the FTC’s warning for advertisers and publishers about deceptive online advertising. Did Facebook deliberately provide advertising disguised as content to certain Facebook users on behalf of certain nefarious operators such as CA and perhaps the NRA? I am sure the FTC wants to know the answer to this question!

Here is the lead-in to our article:

The FTC Issues Deceptive Advertising Warning and Native Advertising Guide

On December 22, 2015 the United States Federal Trade Commission (FTC) issued an enforcement policy statement explaining how the consumer protection principles the FTC has established and enforced for decades apply to different advertising formats—including native ads which look like surrounding non-advertising content. While the FTC statement did not point the finger of blame only at digital advertising, the agency did make sure comments about such advertising were mentioned early and often in the statement.

The agency made it clear in the press release announcing the statement its long-standing policies apply to digital media, “The FTC’s policy applies time-tested truth-in-advertising principles to modern media,”said Jessica Rich, Director of the Bureau of Consumer Protection. “People browsing the Web, using social media, or watching videos have a right to know if they are seeing editorial content or an ad.”

The same day the FTC released the Enforcement Policy Statement, it issued a much shorter statement entitled Native Advertising: A Guide for Business. This guide, the FTC says, was written and released “to help companies understand, and comply with, the policy statement in the context of native advertising.

The business guidance gives examples of when disclosures are necessary to prevent deception and FTC staff guidance on how to make clear and prominent disclosures within the format of native ads.”

I have placed JPEGs of each page of the article below. This article is relevant and important information regarding a significant line of inquiry the FTC should undertake, if it has not already, regarding Facebook.

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Theft on Auto-Pilot: Bot Fraud in Digital Advertising or How to Waste Millions of Dollars Without Really Trying

Bots are digital robots programmed to do something online. Okay, there is a lot more to what bots are and what they do, but for now let’s just go with this quick definition.

Bots are doing a lot of bad things online. One of the most costly things they do online (costly for advertisers and marketers) is pretend to be human and to look at digital advertising. Several times we wrote in the Digital Marketing Report about such misdeeds and how bot fraud is one of the industry’ dirtiest and not-so-little secrets. Here is one such article, originally published in the March 2016 of the newsletter.

Opening text:

In mid-January 2016, the Association of National Advertisers (ANA) and White Ops released a report on the extent to which bots have infested and are sucking the life out of digital advertising efforts in the United States. Clearly, the bots are winning.

“The level of criminal, non-human traffic literally robbing marketers’ brand-building investments is a travesty,” said Bob Liodice, ANA president and CEO. “The staggering financial losses and the lack of real, tangible progress at mitigating fraud highlights the importance of the industry’s Trustworthy Accountability Group in fighting this war. It also underscores the need for the entire marketing ecosystem to manage their media investments with far greater discipline and control against a backdrop of increasingly sophisticated fraudsters.”

Forty-nine ANA member companies participated in the 2015 Bot Baseline study. Those participants deployed White Ops detection tags on their digital advertising to measure bot fraud. Data was collected from nearly 10 billion online advertising impressions across 1,300 campaigns over 61 days (from August 1 through September 30, 2015).

Here are JPEGs of the pages of the article:

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What Vizio was Doing Behind the TV Screen (Hint: It is Creepy, Very Creepy)

What Facebook has been caught out doing is bad, really, really bad. And, there is much more to this horrible story to come out in the news, much, much more.

Meanwhile, here is a story we published in the February 20, 2017 issue of the Digital Marketing Report newsletter. I have uploaded it here as two JPEG images.

Here, though, is some of the text from the article (in case you cannot enlarge the page images enough to read them):

Starting in 2014, Vizio made TVs that automatically tracked what consumers were watching and transmitted that data back to its servers. Vizio even retrofitted older models by installing its tracking software remotely. All of this, the FTC and AG allege, was done without clearly telling consumers or getting their consent. 

What did Vizio know about what was going on in the privacy of consumers’ homes? On a second-by-second basis, Vizio collected a selection of pixels on the screen it matched to a database of TV, movie, and commercial content. 

What is more, Vizio identified viewing data from cable or broadband service providers, set-top boxes, streaming devices, DVD players, and over-the-air broadcasts. Add it all up and Vizio captured as many as 100 billion data points each day from millions of TVs. 

Vizio then turned that mountain of data into cash by selling consumers’ viewing histories to advertisers and others. And, let us be clear: we are not talking about summary information about national viewing trends. According to the complaint, Vizio got personal. 

The company provided consumers’ IP addresses to data aggregators, who then matched the address with an individual consumer or household. Vizio’s contracts with third parties prohibited the re-identification of consumers and households by name, but allowed a host of other personal details, for example: gender, age, income, marital status, household size, education, and home ownership. And, Vizio permitted these companies to track and target its consumers across devices. 

This is what Vizio was up to behind the screen, but what was the company telling consumers? Not much, according to the complaint. Vizio put its tracking functionality behind a setting called Smart Interactivity. But, the FTC and New Jersey AG say the generic way the company described the feature—for example, “enables program offers and suggestions”—did not give consumers the necessary heads-up to know Vizio was tracking their TV’s every flicker. Oh, and the Smart Interactivity feature did not even provide the promised “program offers and suggestions.” 

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The Trade-off Fallacy: How Marketers are Misrepresenting American Consumers and Opening Them up to Exploitation

I have decided, in light of the shocking disclosures about Facebook which have come to light during the past few days, to share some of the content from a Digital Marketing Report, a monthly newsletter for digital marketing professionals we published for two years (May 2015 through May 2017).

For various reasons I made the decision in 2017 to stop publishing the report. One of the reasons, admittedly, was disappointing subscription numbers. But, as I suspected then and now, many (not all) digital marketing professionals are not concerned with the moral and ethical aspects of what they do. Rather, they focus unwaveringly on the money they make.

I knew then, and I know now, that most people do not understand how much information various companies are collecting–and selling to anyone who comes up with the cash–about what people do and say online. While there are benign uses for such data, there are some very sinister and even evil uses. I hope, in the coming months and years, this knowledge will spread widely, and people will demand the situation change dramatically.

Enough preaching for now…here a few of the statements from the article.

Editor’s note: in June 2015, the Annenberg School for Communication, which is part of the University of Pennsylvania, published a report entitled  The Trade-off Fallacy: How Marketers are Misrepresenting American Consumers and Opening Them up to Exploitation. The basis for the report,written by three respected and well-known professors, is survey results from discussions with more than 1,500 adult consumers in the United States.

New Annenberg survey results indicate marketers are misrepresenting a large majority of Americans by claiming Americans give out information about themselves as a trade-off for benefits they receive. To the contrary, the survey reveals most Americans do not believe “data for discounts” is a square deal.

It is evident the amount of information marketers have already collected is enormous. For example, the Forrester Research consultancy estimated in 2014 database marketing firm Acxiom has about 1,500 data points for each of over 500 million active Internet users, most of them in the United States. Another 2014 Forrester report looked to not-too-distant circumstances where marketers would routinely make decisions based on “a customer’s circle of social relationships and influencers…sensor data [from in-store technologies], streaming real-time data, acquired data [from firms such as Acxiom]…anything.”

We also found widespread suspicion: 72% of Americans reject the idea “what companies know about me from my behavior online cannot hurt me.” When we combined the people who are resigned with those who believe what firms know can hurt them, we found 41% of Americans are not only resigned, they hold a dark concern the basic dynamics of the emerging marketplace will cause them injury—and that they cannot control it.

Marketing and retailing executives have typically played down any concerns about their use of shopper data. One way has been to depict an empowered public accepting the notion it is releasing data willingly as a trade-off for benefits it receives. Our survey challenges marketers’ typical cost-benefit analysis defense by showing quite clearly most Americans do not accept the fairness of getting discounts in trade for their data.

Please read and share with others this post and the full Annenberg School for Communication report, located here: https://www.asc.upenn.edu/sites/default/files/TradeoffFallacy_1.pdf

How to Spot and React to a Twitter Troll Bot

Twitter troll bots are not new. Reports of them have been surfacing in the tech media world for years now. They are bits of computer code which comb through tweets looking for keywords, hashtags, and phrases. They can be programmed to follow certain Twitter handles, as well. When they see one they have been programmed to spot, they respond with something nasty designed to intimidate, frighten, etc. It is important to realize these are bots, and not people, when something like this happens to you.

There are real people using Twitter. You can tell, very often, because they respond as humans do when queried. For example, recently I had a nice, brief Twitter conversation with someone whose profile said he is a minister in North Carolina (profiles can be fake, but I took him at his profile, so to speak) about a post of his. I thought the title of his post (which he said an editor wrote, not him) was misleading. I suggested, via a reply tweet, that he might ask the editor to reconsider the headline. He liked my reply (clicked on the heart icon) and we both moved on.

With a bot, though, you will never get a sensible reply to your question or query. All you ever get is insults or nonsense. Now, I know that is all you ever get from some people, but you get my point.

Onward.

Yesterday and today I have been having a “conversation” with a crude example of a Twitter troll bot. Just for fun I decided to poke the troll and see what it came back with. I am sharing part of the conversation here as an example of this kind of digital interaction along with some tips on how to spot a crude bot (some of the sophisticated ones are harder to spot btw). I also want to pass along a few tips on how to respond and how to shut one down.

This interaction started when I tweeted a link to a story about what Hillary Clinton said yesterday about Putin. I think the words in bold appearing in the same tweet was enough to attract the bot’s attention.

The bot’s (its name is Mona M) response to the tweet was classical troll language:  Hillary’s own words” what difference does it make now”! Move on ~ Bernie DID when YOU pulled the rug…

Notice in the response the bot has added Donald Trump’s handle. I am not sure why, perhaps this was added as a tracking or counting mechanism.

Almost immediately after this tweet came another response tweet, one which mentions something not related to my initial tweet:  NO conflict of interest just another SMART decision to have HIS children sit in on a technology Apple/ Facebook meeting. SMART

I had not mentioned in that tweet the fact Trump had his kids sit in on his meeting with Silicon Valley execs. But maybe the troll bot just added that for good measure.

So, now we start to have fun (or at least I did) with a series of my reply tweets and Mona M’s replies. At one point I tweeted Mona is a bot, and the reply made me laugh out loud, “What is your language?” I got a couple more generic slam tweets as part of the exchange, such as  Abedin should REVIEW a few things she’s been involved with…… and  Elizabeth has always been DEEPLY troubled. Mental health is a priority for President elect Trump. Kanye knows all about it.

Some of the replies to me poking the troll bot seemed to be sentences strung together at random (see paragraph above for examples). I am also uncertain of why all caps were used on some words, perhaps an attempt to scream in Internet argot or to emphasize a word?

How to Spot a Troll Bot

In Mona M’s case, it was easy. When I got the first reply I clicked over to look at Mona’s Twitter page and saw there is no description and no owner image. There is no sign of a human anywhere. If you visit Mona’s page (@Monam7M) you will see the account started in May 2016, has tweeted 1,395 times (as I write this) and has very few followers (all of the followers look like bots to me just glancing at their headings).

Also, there are a lot of tweets in one day, another indication of a bot. But not necessarily as I tweet a lot, and I am human (at least I was the last time I checked ;-)).

The biggest tip-off this is a troll bot account is all the tweets on this account are slam tweets. Most of them are directed at Canadian tweets but recently the bot has also started slamming tweets related to Clinton and sending tweets supporting Trump.

What to Do When a Troll Bot Appears

  1. Do not panic (stole that from Douglas Adams, so sorry we lost him and his genius…
  2. Poking the troll the way I have can make for some fun times, but humans quickly lose interest.
  3. Report the account to Twitter as a spam account.
  4. You can block or mute the account if that makes you feel better.
  5. Rinse and repeat as needed. There must be thousands of these things on Twitter and since all it takes to create a Twitter account is a working e-mail address, these things will be there until Twitter stops them.