Trending March 2024 # Google Announces Spam Update Part 2 # Suggested April 2024 # Top 4 Popular

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Google SearchLiaison announced on Twitter that the second part of Google’s spam update is under way. Similarly to the first spam update this update will conclude on the same day that is announced.

According to the announcement:

“The second part of our spam update has has begun today, and it will also conclude later today, unless we share otherwise.”

Google’s Danny Sullivan tweeted that it is directly related to previous update and similar in nature.

“It’s all part of the same thing, just a second part.”

Yes. It’s all part of the same thing, just a second part.

— Danny Sullivan (@dannysullivan) June 28, 2023

Spam Fighting and AI

Google SearchLiaison linked to their announcement from April 2023 (How we fought Search Spam on Google in 2023) where it was revealed that Google used AI to fight spam and has been doing so since 2023.

According to the announcement of the Spam AI:

“By combining our deep knowledge of spam with AI, last year we were able to build our very own spam-fighting AI that is incredibly effective at catching both known and new spam trends.

For example, we have reduced sites with auto-generated and scraped content by more than 80% compared to a couple of years ago.”

Among the spam types addressed in that announcement is spam generated by hacked websites.

Google said it’s not a problem they can solve by themselves and appealed to publishers to take measures to keep their site software up to date to prevent hacking events from happening.

Google linked to their webmaster guidelines which lists the following types of spam that publishers should avoid.

Spam to Avoid Becoming Involved With

This is a partial list of the kind of spam that concerns Google:

Autogenerated content

Link schemes

Unoriginal content

Cloaking

Hidden text or links

Doorway pages

Scraped content

Abusing structured data

Link Schemes a Lucrative and Popular

Link schemes are a highly popular form of manipulating Google’s search results. There’s a huge business in developing ways to trick websites into linking to websites.

It’s debatable if Google’s AI can identify these kinds of link schemes, some of which were developed by so-called white hats…

Fake Alumni Trick

For example, I know that some link builders send outreach emails to universities and pretend to be alumni asking for a link to their latest venture.

Informational Site Trick

This is another “white hat” link building scheme designed to trick universities and non-profit sites by creating an informational site on a .org domain in order to represent it as being a non-commercial website providing information related to a topic of interest.

Once all the links are attained the link builder places a cross-domain rel canonical on the pages that collected links to tell Google to send all the link equity to the commercial site.

All the links that were given to the fake non-commercial site are now going to a commercial website.

Broken PDF Link Scheme

I know about this link scheme because a popular white hat link builder sent me an outreach email attempting to get me to link to their page.

The way it works is that first the link builders identify popular United States government or non-profit PDF files or web pages that have been moved to a different URL.

Next the link builder will create a fake non-commercial website on a dot org domain and represent it as the new home of whatever information was formerly hosted on the government or non-profit web page.

They then contact all the websites that are linking to the old URL (that is now a broken link) and ask them to update the link to the “new home” of those documents and information.

Once the sites are linking to the new URLs on their fake dot org site they then redirect all the links to the client site.

Niche Edit

Some link builders do something called a niche edit where they will add a link to an existing web page.

But niche edits earned a bad reputation in 2023 because some of the links were associated with hacked sites.

Several years ago in 2023 Buzzfeed reported on a link scheme involving “niche edit” links where Russian hackers were selling links from sites they had compromised.

It turned out that the web pages being edited to add a link were actually hacked sites that were being used to sell links from.

Content spammers are using AI tools to rewrite popular content.

There are many link and content schemes. It’s not surprising that Google would turn to sophisticated AI to try to get on top of it.

Why Two Google Spam Updates?

Google did not say why there are two spam updates and provided no more information other than to say that these two updates, released one week apart and lasting a single day, were related.

They didn’t indicate if the updates were AI related or involved a new technology.

Citations

You're reading Google Announces Spam Update Part 2

How To Read Smartphone Specs – Part 2

Smartphones began as slow and weak pieces of hardware, but they have since evolved into very powerful machines. As a result, there are so many aspects to consider when reading up on a new phone. What do all of those numbers mean? Last week, in Part 1 , I broke down screen displays, processors, storage space, and battery life. Now it’s time to tackle much of what’s left.

Just like last time, we’ll start by pulling up the HTC One’s specs.

Let’s take a look at the camera first.

Camera

Much of the information here is more than you need to know. First, the most useful bit of information is what’s left off – megapixels (MP). The HTC One has a 4MP camera. Many of its competitors these days ship with 8 or 13MP. The Nokia Lumia 1020 has surprised people by shipping with a staggering 41MP. This spec determines how large the pictures you take are and how far you can digitally zoom before the picture looks fuzzy.

The rest of these specs are aimed towards people who have a strong understanding of cameras in general, and that’s an area that could take up an entire post on its own. Just know that a smartphone with optical image stabilization should have a more stable picture when you’re taking shots or recording videos. With the latter, 1080p means the videos you capture should look fine on a modern computer or TV.

Network

The first thing you want to know is whether your device is GSM or CDMA. This will determine which networks you can run your phone on. In the US, AT&T and T-Mobile use GSM, while Verizon and Sprint rely on CDMA. If you pick up a phone that only works with GSM carriers, it won’t work with the latter two. If your phone is GSM, though, you have the freedom to pop out the SIM card and switch around between various providers. CDMA carriers are typically more restrictive, requiring you to get a new phone entirely when you’re looking to switch. Keep that in mind before picking up a device.

After that, it helps to see which frequency bands your phone supports. If you’re buying it straight from a carrier, you’re already covered, as you know they’re giving you a device that will work on their network. But if you’re buying a phone online, be sure to check if your phone’s supported frequency bands match those that your wireless provider relies on.

Then there are network speeds. Most smartphones will connect to a 3G network just fine, but some budget devices won’t connect to one that’s 4G. This means that such a device won’t be able to access the faster data speeds that a 4G LTE network provides. This could be a problem if you plan on streaming music and video or downloading apps using your mobile network.

Other Essentials

GPS: You need GPS in order to use in-car navigation or most apps that want to pinpoint your precise location. This information is often used to suggest local stores, restaurants, events, and the like. It can also be used to provide accurate weather forecasts. Chances are your phone comes with this as well.

Accelerometer/Gyro sensor: These determine how fast your device is moving and how you’re holding it. Many games require these, such as racing games that simulate a steering wheel using the phone. Many devices also come with a digital compass, which can detect which cardinal direction it’s pointing in, just like a physical compass.

Conclusion

This isn’t a list of everything you could possibly want to know about smartphones, but hopefully it’s enough information to hold your hand through your next purchase. These things can be intimidating, especially if you’re dealing with a contract that will lock you in for two years. It’s worth taking your time and doing some research before making a commitment. After all, this device will go with you practically everywhere.

Bertel King, Jr.

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How To Filter Out Referral Spam In Google Analytics

Referral spammers have been making their way into our Google Analytics (GA) data without ever actually visiting our websites since around 2013.

Referral spam may show up to administrators as either a fake traffic referral, a search term, or a direct visit.

Referral spambots hijack the referrer that displays in your GA referral traffic, indicating a page visit from their preferred site even though a user has not viewed the page.

The problem is that marketers have to manually decipher and filter this type of traffic out of their GA data to make proper sense of it.

Since we rely on GA to make major ongoing marketing decisions, clean data means everything to us.

Without knowing about referral spam and how to filter it, marketers could be making weighted conclusions based on bogus bot traffic.

In this column, marketers will learn how to clean their Google Analytics data by filtering referral spam.

If you’ve recently migrated to Google Analytics 4, we’ve got a section in here for you too.

For the Love of Filters, What Is Referral Spam?

Referral spam, also known as referrer spam or ghost spam, is created by spam bots that are made to visit websites and artificially trigger a page view.

It sounds sketchy, but bots are just pieces of programmed script that are designed to complete a task automatically online.

It’s estimated that 37% of website activity is created by bots, and less than half of this bot activity is legit.

Desirable bots include:

Search crawlers creating search engine results pages.

Checkers monitoring the health of your website.

Feed fetchers converting content to a mobile format.

The other half of bots aren’t so noble.

Some are designed specifically to spam our referral reports by sending false HTTP requests to our websites with the ability to create non-human traffic otherwise known as bot traffic.

You Cannot Weigh Your Gold with Garbage on the Scale

Referral spam artificially inflates your Google Analytics data.

The level of artificial inflation depends on the amount of referral spam your website is getting, which can vary depending on your industry.

Similarly, the threat this traffic poses to the integrity of your data is directly proportional to the amount of legitimate traffic your website receives on a normal day.

For example, if you receive thousands or even tens of thousands of visits every month, your data won’t be significantly skewed by a couple of hundred spam referral sessions.

However, if you only receive 50-100 visits every month, a couple of hundred spam referrals would throw off your GA data completely, effectively suffocating legitimate traffic.

If you aren’t aware of this problem, it can be very dangerous to your marketing strategy.

How to Filter Referral Spam in Universal Analytics

It’s a nuisance to have bots spamming our websites.

The good news is that it has historically been pretty straightforward to filter this type of traffic.

However, the plot thickened in October 2023, when Google launched Google Analytics 4.

We’ll discuss referral spam in this new version of GA in the next section.

For now, let’s see how to achieve this important task inside your Universal Analytics account.

Make sure that you have the necessary permissions to make changes in your Google Analytics account at the Admin level and then navigate there.

To get started, first create a new view.

It’s a best practice in GA to test new configurations like filters in a new view, instead of in your default raw data view since changes can be permanent and mistakes can be made along the way.

Select the type of view you are creating, either Website or Mobile app.

Then give it a name, and select the same regions and time zone as your main view to make sure you’re comparing apples to apples:

Google will do the bulk of the referral spam filtering work for you automatically.

Navigate to your test view View Settings and ensure that the option to Exclude all hits from known bots and spiders is selected:

By checking this off, you’ll automatically and easily be able to filter out about 75-80% of bot traffic.

Another best practice is to add an annotation to mark the date you started filtering bot traffic.

Annotations act as a helpful reference to remember significant changes over time and can help teams keep a record of these types of changes.

Next, you’ll have to do a bit of manual work to weed out any remaining spam making it through Google’s filter.

But before you can do that, you need to know which spam sites are getting in.

How Do You Identify Spam Referral Traffic in GA?

If you want to see if the websites that you suspect to be spam in your Referrals report actually are, first check if they’re on this list or this list of known spam websites.

Other indicators are a bounce rate of either 0 or 100%, a session time of 0 seconds (it’s easy to see how data could become skewed with outliers like these), and a hostname referral that’s not set.

With the list of “bad referrers,” you can block them manually.

Head over to your Referrals report, and filter by descending bounce rate.

That number can vary according to your traffic volume.

In the example below 50 was used.

To identify suspected spam referral sites, use the pointers above.

It is important to roll out filtering in your test view account first.

Once these sites are filtered, they’re gone for good (so you better be damn sure that it truly is spam!).

Once you’re sure, create your list in Notepad or Text Editor so you can paste it back into GA.

Cut down all the URLs to their top-level domain (TLD).

For example, chúng tôi is an affiliate of chúng tôi so it’s better to just add chúng tôi to your potential referral exclusion list.

Now create a regular expression with your list of URLs, so it looks like the example below from Moz:

Be careful to separate websites with a pipe bar, and to add a backslash in front of the domain extension.

This will allow for other subdomains belonging to that TLD to be excluded, as well.

Now, you’re finally ready to create your filter!

Give your new filter a descriptive name like Referral Spam for easy identification later on.

Change your Filter Type to Custom, and change the Exclude Filter Field to Campaign Source (not the Referral field).

Finally, paste your pre-made list of referral spam URLs:

Once you start filtering referral spam, you can start to see how much it was and is affecting your traffic.

It could account for a fair portion of your website traffic if left unchecked, so it’s easy to see why search marketers get annoyed by it.

Blocking Referral Spam Using Data Filters in Google Analytics 4

If you’ve recently started using Google Analytics, or actively migrated your Universal Analytics account, you should have a Google Analytics 4 (GA 4) property (which is now the default).

While digital marketers are going to love the new engagement tab, setting up filters for spam referrers looks different now.

Most prominently is the fact that in the new Google Analytics 4 Admin interface, the View column is no longer present.

Instead, GA 4 uses Data Streams, which does not have its own column.

With the new GA 4, marketers can create up to 10 data filters per property.

Internal traffic filters are suggested and somewhat pre-configured.

However, currently, there are only two types of filters available:

Developer Traffic

Internal Traffic

Neither of these seems appropriate for filtering external referral spam.

What’s more, if you turn to Google support for help, you find yourself in an endless loop between Google’s top-drawer banner that tells you to navigate to Google Analytics 4 support and the search bar on that page that takes you back to the Universal Analytics results for filtering referral domains.

We’ve reached out to Google to clarify exactly how to do this in GA 4, and they confirmed that it isn’t yet possible (current at time of publication).

Google said:

“…since GA4 is a new upgraded product in Analytics, thus the feature i.e “Referral Exclusions” are yet to be launched in GA. Different resources have different timelines, so we cannot assure a specific date for the launch. However, I would like to inform you that the feature is being worked upon…”

While we wait for the ability to exclude referral spam in GA4, I recommend creating an old and new version of Google Analytics:

One in your legacy Universal Analytics mode.

And a new one in Google Analytics 4 mode.

Follow the instructions from the previous section in Universal Analytics to filter referral spam from your GA reports for now.

The good news is that this new iteration of Google Analytics has testing built-in, so it won’t be necessary to create new views for implementing new configurations:

The Benefits of Weeding Out Referrer Spam

Clean data is everything when it comes to making meaningful and actionable conclusions based on it.

With these powerful tactics behind you, you’ll be able to filter referral spam so you can make decisions based on facts.

Since referral spam can hit lower-traffic websites even harder than larger sites, it’s important that marketing teams of all sizes stay on top of it.

That means checking for new referral spam websites regularly and adding them to your exclusion list.

Remember to keep your Universal Analytics view alive for now, until we know more about how to exclude referral spam in Google Analytics 4.

More Resources:

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Asus Rog Phone 2 Update: Android 10 Update Starts Rolling Out!

With the launch of the ROG Phone, Asus broke new ground in the world of smartphone gaming. Not everyone is a fan of Asus’ beefy gaming machine, but that hasn’t stopped the company from bringing a second iteration.

The ROG Phone 2 has been launched in China for 5,999 yuan (~$873), which is the same as the ROG 1’s launch price. The device will be made available, globally, in September.

In this section, we’ll talk security updates, bug fixes, Android OS upgrades and everything in between. So, without further ado, let’s dig in.

Latest News

March 9, 2023: Android 10 finally makes its way to the ROG Phone II. Asus has started rolling out the latest version of Android to its gaming smartphone. Here’s the complete changelog:

November 21, 2023: Asus has started rolling out a sizeable software update for the ROG Phone II. The update, which carries software version 16.0631.1910.44, fixes a bunch of issues regarding phone navigation, Air Triggers, Wi-Fi Hotspot, car Bluetooth, and more.

Check out the complete changelog to see all the fixes and improvements.

Fixed the abnormal vibration sound issue when certain notifications arrived

Fixed the issue where occasionally the Back gesture did not work

Fixed the issue where occasionally in-screen fingerprint icon would not disappear

Fixed the issue where hotspot icon still appeared in the status bar after WiFi hotspot had been turned off

Fixed the issue where the phone occasionally could not connect to car’s Bluetooth

Fixed the issue where user could not set up AirTriggers buttons when the system language was in Hebrew

Fixed the issue where in some regions there was no Google Assistant option in AirTriggers squeeze gesture settings

Fixed the issue where occasionally Kunai GamePad did not work

Fixed the issue where making a phone call accidentally triggered AirTriggers squeeze function

November 08, 2023: As anticipated, Asus is bringing Android 10 to ROG Phone II and has opened the beta registration portal to the smartphone’s enthusiasts. There aren’t many requirements, per se, to test Android 10 beta, but users are required to be active on ZenTalk and provide valuable feedback. To get yourself registered for the ROG Phone II Android 10 beta program, follow this link and fill out the application form.

November 07, 2023: Asus has started rolling out a software update for its ROG Phone II. The OTA, which carries software version WW1910.35, brings all new AirTrigger gestures, adds game cover customization, fixes navigation bar problem, updates the security patch to October 2023, and more.

As it’s Asus’ greatest smartphone on the market, the ROG Phone 2 is expected to get the Android 10 update. Asus has been pretty sloppy with its updates lately, so, we are expecting the OEM to release the update by the end of Q3 2023.

Last year, when Asus released the first ROG device, most users expected the company to provide lightning-quick updates due to the phone’s unchallenged, flagship status. The phone shipped with Android 8.1 Oreo, just around the time when Android Pie popped up around the block. Months went by, but the Taiwanese giant never got around to publishing the update. The original ROG users are still waiting for the update, which, according to Asus will go live by end of September 2023.

The Asus ROG Phone 2 will be the first device to pack the Snapdragon 855 Plus chipset, so, its performance should arguably be the best on the market. However, if you are in for a device that’s guaranteed to get lightning-fast updates, you’d be better off looking for alternatives.

The OnePlus 7 Pro and Samsung Galaxy S10 are a couple of great alternatives. Both come with top-of-the-line specs and are guaranteed to get a couple of major OS upgrades. In terms of speed, OnePlus beats Samsung by a margin, as there are no highly-modified skins involved. However, judging by the quality of the two devices, you can’t go wrong with either.

RELATED → Asus ROG Phone 1 update

Release Date Software Version — Changelog

Mar 09, 2023 Installs Android 10

Aug 15, 2023 NA — Always On Display setting is back

You have already seen how sloppy Asus has been with updates lately, and that isn’t expected to change much with the introduction of ROG Phone 2. Asus implements a heavy skin on top of the vanilla Android build that Google releases, which itself is quite time-consuming.

Also, the Taiwanese giant is usually more concerned with updating its Zenfone lineup ahead of ROG, which could prevail with the ROG Phone 2, as well.

In contrast, devices like OnePlus 7 Pro, Galaxy S10, Huawei P30 Pro, etc. shall be getting stable (beta could arrive early) Android 10 update by November 2023, January 2023, and December 2023 respectively. If you talk about dedicated gaming phones though, we won’t be surprised if Razer is able to update the Razer Phone 2 to Android 10 before Asus rolls out the 10 update for ROG Phone 2.

Google Ranking & Results Update Underway

Google set blogs and webmasters ablaze in coverage last week with their changes in Toolbar PageRank, which was cast aside by some and taken quite seriously by others. It looks like this week, there may be an update of much more importance going on at Google, in their search result rankings.

Google has just cranked up the dial for domain name relevance, it seems.

I have a fairly new website (about a year old) in a very competitive area with millions of search results. The site has only about 100 pages. PR2. Hardly any backlinks. No link campaigns. No optimization. But it’s a single-word dn in .net, e.g., chúng tôi (I bought it in the aftermarket hoping search engines would dig it.)

Once again there has been an update and as usual I lost another 30% of my traffic from Google. Soon it’ll be down to nothing and that is without me doing anything except adding more pages, fixing some typo’s and a few layout fixes.

Yes, there definitely has been an update or algo movement yesterday. My first guess is that there has been some movement on dup content filtering measures.

Strong domains and duplicate content filtering being tweaked in the Google algorithm? Possibly.

One fear last week would be that since Google lowered the PageRank of some sites that it suspected as passing paid link juice, the target sites which were linked to from those sites would lose some kind of ranking.

Hopefully this will not be the case, but if it does happen the full effect of a PageRank (yeah, I know it’s only the toolbar) ‘penalty’ would be heard from the top on down to the bottom. Google does have a knack for keeping things exciting, don’t they?

Google Search Patent Update – February 18, 2023

What can I say? It’s been damned slow as far as search-related patent awards over the last while – which is actually quite odd.

I was joking with fellow patent hound, Bill Slawski, recently that Google figures we’re on to them… and stopped filing stuff.

Just kidding!

But here’s a few from the past few weeks.

Latest Google Patents of Interest

Filed: December 20, 2023

Awarded: February 18, 2023

Abstract

“Systems and methods of providing content for display on a computing device via a computer network using a location feature index are provided. A data processing system can receive a request for content from the computing device, and can determine a geographic location of the computing device associated with the request for content. The data processing system can identify a keyword indicating a non-geographic semantic feature of the determined geographic location. The identification can be based on the determined geographic location and from a location feature index that maps geographic areas to keywords that indicate non-geographic semantic features of the geographic areas. The data processing system can select, based on the keyword, a candidate content item for display on the computing device.”

Notable

“The data processing system can determine a geographic location of the computing device associated with a request for content. The data processing system can to identify a keyword indicating a non-geographic semantic feature of the determined geographic location. The data processing system can make the identification based on the determined geographic location and using a location feature index that maps geographic areas to keywords that indicate non-geographic semantic features of the geographic areas.”

“For example, the data processing system can determine that a geographic location has high end retail clothing stores. From a semantic analysis of this information, the data processing systems can identify keywords “diamonds” “luxury car” or “tropical beach vacation” and associate or map these keywords to the geographic area. The data processing system can receive a request for content to display on a computing device in the geographic area, e.g., the computing device is in the vicinity of the high end retail clothing stores. Responsive to the request, the data processing system can use the “tropical beach vacation” keyword to select a content item for a luxury tropical resort as a candidate for display on the computing device responsive to the request. In this example, the geographic area having high end clothing stores can be unrelated to any tropical location, although a user of a computing device (e.g., a smartphone) walking down a street having high end clothing stores may also be interested in high end luxury vacations. Thus, the data processing system can identify a group of keywords for one or more geographic areas based on semantic features or characteristics of those areas, and content providers can select content for a type of geographic area (e.g., high end retail areas) in general rather than focusing on a single area such as one set of latitude and longitude coordinates near a particular clothing store.”

Filed: December 16, 2024

Awarded: February 4, 2023

Abstract

“An assistant executing at, at least one processor, is described that determines content for a conversation with a user of a computing device and selects, based on the content and information associated with the user, a modality to signal initiating the conversation with the user. The assistant is further described that causes, in the modality, a signaling of the conversation with the user.”

Notable

“… a user interface from which a user can chat, speak, or otherwise communicate with a virtual, computational assistant (e.g., also referred to as “an intelligent personal assistant” or simply as an “assistant”) to cause the assistant to output useful information, respond to a user’s needs, or otherwise perform certain operations to help the user complete a variety of real-world or virtual tasks.”

“The assistant may proactively guide the user to interesting information, even in instances where there was no explicit user request for the information. For instance, in response to the assistant determining that a flight reservation for the user indicates that the flight is delayed, the assistant may notify the user without the user requesting that the assistant provide information about the flight status.”

“The assistant may generate a single notification representing multiple notifications and multiple types of user experiences, based on an importance of the notifications. For instance, the assistant may collapse multiple notifications into a single notification (e.g., Jon, you have four alerts. Your package is on time, your flight is still on time, and your credit card was paid.”) for trivial notifications.”

Filed: March 20, 2023

Awarded: February 18, 2023

Abstract

“Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for contextually disambiguating queries are disclosed. In an aspect, a method includes receiving an image being presented on a display of a computing device and a transcription of an utterance spoken by a user of the computing device, identifying a particular sub-image that is included in the image, and based on performing image recognition on the particular sub-image, determining one or more first labels that indicate a context of the particular sub-image. The method also includes, based on performing text recognition on a portion of the image other than the particular sub-image, determining one or more second labels that indicate the context of the particular sub-image, based on the transcription, the first labels, and the second labels, generating a search query, and providing, for output, the search query.”

Notable

“(…) a graphical interface being presented on a display of a computing device and a transcription of an utterance spoken by a user of the computing device; identifying two or more images that are included in the graphical interface; for each of the two or more images, determining a number of entities that are included in the image; based on the number of entities that are included in each of the two or more images and for each of the two or more images, determining an image confidence score that reflects a likelihood that the image is of primary interest to the user;”

“For example, a user may ask a question about a photograph that the user is viewing on the computing device, such as “What is this?” The computing device may detect the user’s utterance and capture a respective image of the computing device that the user is viewing.”

Filed: July 26, 2023

Awarded: February 18, 2023

NOTE: This seems to be targeted at Google Plus, as such may have no bearing in current approaches with Google.

Abstract

“Systems and methods for determining a user engagement level for a content item are provided. In some aspects, indicia of one or more user interactions with a content item are received. Each user interaction in the one or more user interactions has an associated time and an interaction type. A user engagement level for the content item is determined based on the one or more user interactions, the associated times, and the interaction types. The user engagement level for the content item is stored in association with the content item.”

Notable

“The subject technology generally relates to social networking services and, in particular, relates to determining a quality score for a content item in a social networking service.”

“A recentness score of the content item is determined based on the time stamp. An affinity score representing an affinity of the first user to the second user in the web-based application is also determined. A popularity score of the content item is determined based on user interactions with the content item. A quality score of the content item is generated based on the recentness score of the content item and a combination of the affinity score and the popularity score of the content item.”

And there we have it for another week.

Drop back next week for more (unless Google decides to rain on our parade again).

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In-Post Images: USPTO

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