Alexa Internet News Faces Popularity and Trust Issues

Alexa Internet's news section has seen a significant surge in popularity, with over 27 million unique visitors in 2020, up from 20 million in 2019. This growth can be attributed to the increasing demand for online news sources.

The rise in popularity has also led to concerns about the trustworthiness of Alexa Internet's news section. In 2018, Alexa Internet was criticized for its biased algorithm, which prioritized news from major media outlets over smaller, independent sources.

As a result, many users have expressed skepticism about the accuracy and objectivity of the news presented on Alexa Internet. This has led to a decrease in trust, with only 22% of users trusting Alexa Internet's news section in 2020, down from 30% in 2019.

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Alexa has revolutionized the way people interact with their homes, making it a more convenient and enjoyable experience.

The use of Alexa has increased significantly, with over 100 million Alexa devices sold worldwide, making it one of the most popular smart home devices.

Many people rely on Alexa for daily tasks, such as setting reminders, playing music, and controlling their smart home devices, freeing up time for more important things.

The integration of Alexa with other smart devices has also improved home security, allowing users to remotely monitor and control their security cameras and doorbells.

Facebook uses the same dubious popularity data from the Alexa Site Rankings as a proxy for trust.

In October 2020, a report by Alex Hern at The Guardian exposed this surprising fact.

Facebook's AI looks for signals including feedback from the community and disbelief comments to automatically predict which posts might contain misinformation.

These predicted posts are temporarily soft demoted in feed and enqueued to fact-check product for review by third-party fact-checkers.

But some posts are not automatically demoted, such as those from sites in the "Alexa 5K" list, which includes content in the top 5,000 most popular internet sites.

These sites supposedly keep their distribution high under the assumption they are unlikely to be spreading misinformation.

It looks like Facebook gives a "fast pass" to any site on the Alexa 5K Site Rankings.

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Misinformation is a major issue on the internet, and Facebook's approach to it is concerning. Facebook uses the Alexa Site Rankings as its benchmark to determine which sites are less likely to spread misinformation, and it includes sites like Zerohedge and Infowars in this list.

These sites are generally considered to be flush with misinformation and disinformation. Russia Today, for example, is even funded by the Kremlin.

The irony is that local news desks, which are often filled with journalists from cities large and small, are not given the same benefit of the doubt. They are presumed guilty and put into a long line for fact-checking whenever Facebook's AI determines a story may be problematic.

This is not a rational decision, especially since local news is often the most trusted source of information. The Knight Foundation has found that among news sources, local news is the most trusted.

Facebook's approach to misinformation is also problematic because it equates clicks with quality. This means that sites with high engagement and popularity are given a fast pass, even if they serve Facebook's priorities rather than the public interest.

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Alexa's Text-to-Speech (TTS) technology is unusually good, making it ideal for converting news headlines into audio.

TTS-generated audio feeds have a unique requirement: the title and description of news articles should be self-explanatory, without needing visual context.

News headlines that depend on the article body, like "How your favorite celebrities spent the 4th of July", are not suitable for TTS-generated audio feeds.

Alexa's current TTS word limit makes it difficult to convey extensive, long-read articles, so audio briefings should be more focused.

A supervised machine learning algorithm was trained to filter out stories that aren't "audio friendly", based on phrases and word patterns in the titles or descriptions of trending news stories.