Beset

AI spam is winning the battle against search engine quality

'Not all AI content is spam, but I think right now all spam is AI content'

Google Search Overwhelmed By Massive Spam Attack

Google is apparently struggling to contain a spam attack that's been ongoing for days

Browsing your website does not mean I want your spam

I recently fell down a deep dark hole on the internet.

My Journey to the Center of America’s Political Spam Text Hell

I’ve gotten nearly 2,000 campaign fundraising texts that were meant for someone else. I tried to find out why—and uncovered a labyrinth of politicians, data brokers, and shady tactics.

The Brazilianization of the Internet

Spam filters don't help you when you're the spam

Google Search Really Has Gotten Worse, Researchers Find

"The majority of high-ranking product reviews in the result pages of commercial search engines use affiliate marketing, and significant amounts are outright SEO product review spam."

Bluesky follower sales websites

As Bluesky grows, so does the spam industry orbiting it

Email isn’t decentralized, and that’s fine

Email is open, but deliverability depends on a few big inbox providers. Why we traded some of email's decentralization to fight spam, and why that's fine.

The spreading of misinformation online

Significance The wide availability of user-provided content in online social media facilitates the aggregation of people around common interests, worldviews, and narratives. However, the World Wide Web is a fruitful environment for the massive diffusion of unverified rumors. In this work, using a massive quantitative analysis of Facebook, we show that information related to distinct narratives––conspiracy theories and scientific news––generates homogeneous and polarized communities (i.e., echo chambers) having similar information consumption patterns. Then, we derive a data-driven percolation model of rumor spreading that demonstrates that homogeneity and polarization are the main determinants for predicting cascades’ size. , The wide availability of user-provided content in online social media facilitates the aggregation of people around common interests, worldviews, and narratives. However, the World Wide Web (WWW) also allows for the rapid dissemination of unsubstantiated rumors and conspiracy theories that often elicit rapid, large, but naive social responses such as the recent case of Jade Helm 15––where a simple military exercise turned out to be perceived as the beginning of a new civil war in the United States. In this work, we address the determinants governing misinformation spreading through a thorough quantitative analysis. In particular, we focus on how Facebook users consume information related to two distinct narratives: scientific and conspiracy news. We find that, although consumers of scientific and conspiracy stories present similar consumption patterns with respect to content, cascade dynamics differ. Selective exposure to content is the primary driver of content diffusion and generates the formation of homogeneous clusters, i.e., “echo chambers.” Indeed, homogeneity appears to be the primary driver for the diffusion of contents and each echo chamber has its own cascade dynamics. Finally, we introduce a data-driven percolation model mimicking rumor spreading and we show that homogeneity and polarization are the main determinants for predicting cascades’ size.

Is Google Getting Worse? A Longitudinal Investigation of SEO Spam in Search Engines

Many users of web search engines have been complaining in recent years about the supposedly decreasing quality of search results. This is often attributed to an increasing amount of search-engine-optimized but low-quality content. Evidence for this has always been anecdotal, yet it’s not unreasonable to think that popular online marketing strategies such as affiliate marketing incentivize the mass production of such content to maximize clicks. Since neither this complaint nor affiliate marketing as such have received much attention from the IR community, we hereby lay the groundwork by conducting an in-depth exploratory study of how affiliate content affects today’s search engines. We monitored Google, Bing and DuckDuckGo for a year on 7,392 product review queries. Our findings suggest that all search engines have significant problems with highly optimized (affiliate) content—more than is representative for the entire web according to a baseline retrieval system on the ClueWeb22. Focussing on the product review genre, we find that only a small portion of product reviews on the web uses affiliate marketing, but the majority of all search results do. Of all affiliate networks, Amazon Associates is by far the most popular. We further observe an inverse relationship between affiliate marketing use and content complexity, and that all search engines fall victim to large-scale affiliate link spam campaigns. However, we also notice that the line between benign content and spam in the form of content and link farms becomes increasingly blurry—a situation that will surely worsen in the wake of generative AI. We conclude that dynamic adversarial spam in the form of low-quality, mass-produced commercial content deserves more attention. (Code and data: https://github.com/webis-de/ECIR-24).

Is Google Getting Worse? A Longitudinal Investigation of SEO Spam in Search Engines

Many users of web search engines have been complaining in recent years about the supposedly decreasing quality of search results. This is often attributed to an increasing amount of search-engine-optimized but low-quality content. Evidence for this has always been anecdotal, yet it’s not unreasonable to think that popular online marketing strategies such as affiliate marketing incentivize the mass production of such content to maximize clicks. Since neither this complaint nor affiliate marketing as such have received much attention from the IR community, we hereby lay the groundwork by conducting an in-depth exploratory study of how affiliate content affects today’s search engines. We monitored Google, Bing and DuckDuckGo for a year on 7,392 product review queries. Our findings suggest that all search engines have significant problems with highly optimized (affiliate) content—more than is representative for the entire web according to a baseline retrieval system on the ClueWeb22. Focussing on the product review genre, we find that only a small portion of product reviews on the web uses affiliate marketing, but the majority of all search results do. Of all affiliate networks, Amazon Associates is by far the most popular. We further observe an inverse relationship between affiliate marketing use and content complexity, and that all search engines fall victim to large-scale affiliate link spam campaigns. However, we also notice that the line between benign content and spam in the form of content and link farms becomes increasingly blurry—a situation that will surely worsen in the wake of generative AI. We conclude that dynamic adversarial spam in the form of low-quality, mass-produced commercial content deserves more attention. (Code and data: https://github.com/webis-de/ECIR-24).

The Worst Spam Emails: Inside iLands' AI Agent Hustle

iLands, a new AI agent-centric startup, is spamming creatives like me numerous times a day. What do its agents want? My job. Why? They need to buy more tokens.

Facebook’s AI Spam Isn’t the ‘Dead Internet’: It’s the Zombie Internet

Facebook is the zombie internet, where a mix of bots, humans, and accounts that were once humans but aren’t anymore interact to form a disastrous website where there is little social connection at all.

Facebook’s AI Spam Isn’t the ‘Dead Internet’: It’s the Zombie Internet

Facebook is the zombie internet, where a mix of bots, humans, and accounts that were once humans but aren’t anymore interact to form a disastrous website where there is little social connection at all.