Why ‘bad’ ads appear on ‘good’ sites – explains a computer scientist

Why ‘bad’ ads appear on ‘good’ sites – explains a computer scientist

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Ive here. Since readers sometimes get ads that are inconsistent with our content and get confused, this explainer seems to be helpful. However, at least a few years ago, when we were critical of the big banks’ business practices and frequently called for the prosecution of senior executives, it was interesting to me that we often received campaigns from the big banks. We’ll assure our readers that it’s an accidental confession that financial companies are paying us to run content against their interests.

By Eric Zeng, PhD student in computer science and engineering at the University of Washington.Originally Posted in dialogue

Sketchy ads, like ads for miracle diet pills and dubious software, sometimes appear on legitimate, well-regarded sites. It turns out that most websites don’t actually decide who can show ads to their audience. Instead, most sites outsource this task to a complex network of ad tech companies that determine which ads to show to each specific person.

The online advertising ecosystem revolves primarily around “programmatic advertising,” a system used to place ads from millions of advertisers on millions of websites. The system uses computers to automatically let advertisers bid on available ad space, often with deals happening faster than manually possible .

Programmatic advertising is a powerful tool that allows advertisers to target and reach people on a large number of websites.as a PhD student in computer science, I study how malicious online advertisers exploit the system and use online advertising to spread scams or malware to millions of people. This means that online advertising companies have a big responsibility to prevent harmful ads from reaching users, but they sometimes fail to do so.

Programmatic Advertising, Explained

The modern online advertising market is designed to solve one problem: matching lots of ads with lots of ad space. Sites want to keep their ad space full at the best price, and advertisers want to target their ads to relevant sites and users.

Rather than pairing up with each website and advertiser to serve ads, advertisers work with demand-side platforms, the tech companies that let advertisers buy ads. Websites partner with supply-side platforms, and tech companies pay websites to place ads on their pages. These companies handle the details of determining which websites and users should be matched with specific ads.

Most of the time, ad tech companies use real-time bidding auctions to decide which ads to show. Whenever a person loads a website, and the website has an ad space, the supply-side platform for that website will request an ad bid from the demand-side platform through an auction system called an ad exchange.Demand-side platforms will decide which ad in their inventory is best for a particular user based on any information they collect about user interests and web history Track user browsing, then submit the bid. The winner of this auction can put their ad in front of users. It all happens in an instant.

When you see an ad on a webpage, behind the scenes the ad network automatically conducts an auction to decide which advertiser wins the right to show you the ad. Eric Zeng, CC BY-ND

Big players in this market include Google, which runs a supply-side platform, demand-side platform, and an exchange. These three components make up an ad network. Various smaller companies such as Criteo, Pubmatic, Rubicon, and AppNexus also operate in the online advertising market.

The system allows advertisers to place ads on millions of websites to potentially millions of users without knowing the specifics. It allows sites to solicit ads from countless potential advertisers without having to contact or make an agreement with any of them.

Screening Bad Ads: An Incomplete System

Like any other advertiser, malicious advertisers can take advantage of the scale and reach of programmatic advertising to send scam and malware links to potentially millions of users on any website.

There are checks for bad ads on multiple levels. Ad networks, supply-side platforms, and demand-side platforms often have content policies that limit harmful advertising.For example, Google Ads has an extensive content policy that prohibits illegal and dangerous products, inappropriate and objectionable content, and a long list of deception techniquessuch as phishing, clickbait, false advertising, and doctored images.

However, other ad networks have less stringent policies.For example, MGID, a native ads Network I checked with my colleagues a study and found many lower quality ads served, with shorter Content Policy Illegal, offensive and malicious advertising, and one-liners regarding “misleading, inaccurate or deceptive information” are prohibited. Native ads are designed to mimic the look and feel of the website they appear on, and are often responsible for sketchy ads at the bottom of news articles. Another native ad network, content.ad, has no content policy at all on its site.

These political ads from the 2020 election are examples of potentially misleading techniques to get you to click on them. The ad on the left uses Trump’s name and a click-bait headline that promises money. The center’s ad purported to be a thank you card to Dr. Fauci, but was actually meant to collect email addresses for political mailing lists. The ad on the right is in the form of a poll, but links to a page that sells a product. Screenshot by Eric Zeng

Sites can block specific advertisers and ad categories. For example, a website can block specific advertisers that serve fraudulent ads on its pages, or certain ad networks that serve low-quality ads.

However, these policies are only as good as enforcement. Ad networks often use a combination of manual content reviewers and automated tools to check each ad campaign for compliance with their policies.How these effects are unclear, but Report from advertising quality firm Confiant Indicates that between 0.14% and 1.29% of ads served on various supply-side platforms in Q3 2020 were low quality.

Malicious advertisers take countermeasures and find ways to evade automatic or manual review of their ads, or exploit gray areas in content policies.For example, in a study My colleagues and I investigated deceptive political ads during the 2020 US election, and we found numerous examples of fake political polls that claimed to be polls but asked for an email address to vote. Polls in polls get users to sign up for political email lists. Despite this deceptive behavior, such ads may not violate Google’s content policies for political content, data collection, or misrepresentation, or may have simply been missed during the review process.

Bad Ads by Design: Native Ads on News Sites

Finally, some examples of “bad” ads are intentionally designed by websites and ad networks to be misleading and deceptive. Native ads are a good example.They obviously work because native advertising companies claim Websites have higher CTR and revenue. study Have show This may be because it is difficult for users to distinguish native ads from website content.

These are examples of native ads found on news sites. They mimic the look and feel of links to news articles and often contain clickbait, scams, and questionable products. Screenshot by Eric Zeng

You’ve probably seen native ads on many news and media sites, including major sites like CNN, USA Today, and Vox. If you scroll to the bottom of a news article, there may be a section called “Sponsored Content” or “Around the Web” with content that looks like a news article. However, all of this is paid content.I had one with my colleague study Native ads on news and misinformation sites were found to disproportionately contain potentially deceptive and misleading content, such as unregulated health supplement ads, deceptive written ads, investment promotions and sources from content farm.

This highlights an unfortunate situation. Even reputable news and media sites are struggling to make money and are turning to deceptive and misleading advertisements on their sites to make more money, even though this poses risks to users and damages their reputations.

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