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I recently saw a poll in a private Facebook Group where many people voted that nofollow links can help rank a site because of the anchor text. Can nofollow anchor text help rankings?


Take note that in September 2023, a few months after this article was published, Google made a substantial change to how nofollowed links are handled. Beginning in September 2023, Google is treating the nofollow link attribute as a hint. What that means is that Google may or may not obey the nofollow attribute.

Previously Google treated nofollows as a directive, meaning that Google would obey the nofollow and drop the link from the link graph and not count it for link purposes.

Read more about Google nofollow hints:

How Google Treats Nofollow Links.

How Google Nofollow Hints Affect SEO

Why Google Changed Nofollow to Hints

Anchor Text Without Links

There are two theories floating around about how nofollow links help a site rank.

The first theory states that a nofollow link will get republished by a spammer and that the spammer might make it a dofollow link.

That’s correct. But that argument assumes that a few spam links will make a meaningful impact on rankings.

For ranking keywords that matter, keywords that make money, no, absolutely no. A few spam links will not help a site rank.

The second theory suggests that search engines will pick up the anchor text and use that for ranking. There are many problems with that guess about what Google does.

And let’s make it clear, that theory is purely just a guess. There is nothing to support that idea.

There is no research.

There are no patents.

There are no statements from Google that anchor text from nofollow links are used.

There is nothing, zero, to substantiate the idea of nofollow anchors being a ranking factor. ZERO.

Links and the Link Graph

Nofollow links are dropped from the link graph. The Link Graph is the map of the Internet.

The nofollow removes the link from existence. It does not exist for Google.

This has always been the case. John Mueller is on record stating this as far back as 2012:

“We take these links out of our PageRank calculations, and out of our algorithms when they use links.”

Nofollow Anchor Text are Just Words

Google takes it out of the PageRank calculation. And that includes the anchor text and this is why:

Because the link that the anchor points to does not exist for Google, the anchor text becomes words, just words.

Words are Not Links

So how could Google use words as anchor text when there is no link associated with them?

Setting aside the fact that there are no patents and no research papers about using nofollow anchor text for ranking, the whole idea of using words (without links) as anchor text does not make logical sense.

Those words are disconnected from the link (because there is no link) and because of that they are disconnected to the website that the link points to… because there are no links.

Google has even made a video dedicated to explaining that nofollow links do not help rank a site in any way.

The idea that nofollow anchor text can influence rankings makes zero sense in at least three different ways. It’s on the same level as a belief in fairy tales.

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Why Mobile And Desktop Rankings Are Different

Google’s John Mueller answered an interesting question about why mobile and desktop search rankings can differ. Mueller offered several factors related to personalization to explain why the two kinds of searches sometimes are different.

Why Do Desktop and Mobile Search Rankings Differ?

The person asking the question was interested in learning how to diagnose the reason why a site might not perform as well in mobile search as it does in desktop search.

Here’s the question:

“Why… How are desktop and mobile ranking different when we’ve already been switched to mobile first indexing?”

Google’s John Mueller pointed out that indexing and ranking are two different things.

Just because we’re in a mobile-first indexing environment doesn’t mean that the mobile and desktop versions will be ranked equally because they were indexed as mobile.


“So, mobile first indexing is specifically about that technical aspect of indexing the content.

And we use a mobile Googlebot to index the content.

But once the content is indexed, the ranking side is still (kind of) completely separate.”

Mobile and Desktop Rankings Are Contextually Personalized

Mueller next explained that for some situations the context of the searcher and the device that is used can alter rankings.

He explained that for some searches the needs of the users are different depending on the device and that can influence rankings.

John Mueller Explaining Why Mobile and Desktop Searches are Different

“And it’s normal that desktop and mobile rankings are different.

Sometimes that’s with regards to things like speed.

Sometimes that’s with regards to things like mobile friendliness.

Sometimes that’s also with regards to the different elements that are shown in the search results page.

For example if you’re searching on your phone then maybe you want more local information because you’re on the go.

So we tend to show …a different mix of different search results types.

And because of that it can happen that the ranking or the visibility of individual pages differs between mobile and desktop.

And that’s essentially normal. That’s a part of how we do ranking.

It’s not something where I would say it would be tied to the technical aspect of indexing the content.”

Page Speed and Mobile Factors for Ranking Differences

The person asking the question next asked a follow up question about diagnosing these ranking differences.

He asked if lower mobile rankings are an indication that mobile page speed factors are the cause.

Google’s Mueller answered:

“…Mobile friendliness is definitely a factor.

There might also be other factors that play in there, specifically with regards to mobile and desktop.

These are kind of the differences that are always a bit around with regards to mobile and desktop search results.

Sometimes it’s also just because it’s a different device or a different connection to the Internet so we use different settings essentially for personalization.”

Difference in Rankings is Due to Personalization

Google’s John Mueller confirmed that mobile indexing is just indexing and separate from the ranking part of the algorithm.

He also revealed that personalization plays a role in the occasional differences in search rankings between the mobile and desktop searches.

Mueller explained that the needs of someone on a mobile device may be different from the needs of someone on a desktop device.

So if one is trying to diagnose why there are differences in ranking between devices then maybe it may be useful to see why the top ranked sites mobile versions might be preferable over the lower ranked pages within the context of a mobile device and personalization.

It’s possible there may be clues there to help diagnose the issues.


Watch John Mueller answer the question at the 49:10 minute mark

How To Send Text Messages (Sms) From Google Chat

Sending text messages from the web has been fraught with inconveniences such as saving conversations in one location, being able to receive messages easily and sending updates without paying outrageous fees. There are a few workarounds but one of the easier yet more unknown feature lies in Google’s Chat function.

Enable SMS in Labs

Sending text messages from Google Chat is easy to enable but hidden in Google’s experimental feature base called Labs. To add text messaging capability to your account, log in and select the gear icon located in the top right of the window. From the drop down choose “Labs” and you’ll be taken to Beta and other experimental features available for Gmail.

The selections you need to enable are listed as “SMS (text messaging) in Chat” and “SMS in Chat gadget.” Both of these features must be enabled to send, receive and display text messages when logged in to Gmail through the web interface.

Sending Text Messages In Gchat

To send a text start typing the name or number of a contact and a menu bar should pop up with their number and an option to send a SMS. A normal chat window will appear but will send text messages (or an IM if they sign on with Google Chat) to their phone. Incoming messages will show up in this same window and act as a typical chat conversation.

However, there are some downsides to using Gmail for sending text messages. While the service itself is free, you are initially limited to 50 messages but gain 5 more when you receive a new message. If you manage to finish your quota of available text messages, your count will be increased to one in 24 hours.

A quick and dirty trick to get additional messages

If you feel that 50 messages are insufficient for your usage, a quick and dirty way is to send an SMS to your own phone, and then reply to that message multiple times. Since each time you receive a SMS in Gchat, your quote increases by 5, by replying the message from your mobile time (say 10 times), you are effectively doubling your message count. This will work for those who have free SMS usage on their mobile phone.

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Text Mining Hack: Subject Extraction Made Easy Using Google Api

Let’s do a simple exercise. You need to identify the subject and the sentiment in following sentences:

Google is the best resource for any kind of information.

I came across a fabulous knowledge portal – Analytics Vidhya

Messi played well but Argentina still lost the match

Opera is not the best browser

Yes, like UAE will win the Cricket World Cup.

Was this exercise simple? Even if this looks like a simple exercise, now imagine creating an algorithm to do this? How does that sound?

The  first example is probably the  easiest, where you know “Google” is the subject. Also we see a positive sentiment about the subject. Automating the two components namely subject mining and sentiment mining are both difficult tasks, given the complex structure of English language.

Basic sentiment analysis is easy to implement because positive / negative word dictionary is abundantly available on internet. However, subject mining dictionaries are very niche and hence user needs to create his own dictionary to find the subject. In this article, we will talk about subject extraction and ways to automate it using Google API.

Also See: Basics of creating a niche dictionary

Why is subject extraction not a common analysis?

The most common projects using text mining are those with sentiment analysis. We rarely hear about subject mining analysis. Why is it so?

Hash tags could also help to find sarcasm to some extent.  Consider the following tweet :

Indian batting line was just fine without Sachin. #Sarcasm #CWC2024 #Sachin #Indian-Cricket-Team

Think of this sentence without hash-tags. It would be incomplete and would give a different meaning. Mining for hash tag(#sarcasm) will indicate that the sentence is most probably a negative sentence. Also, multiple subjects can be extracted from the hash tags and added to this sentence.

Hopefully, you can now realize the importance of these hash tags in data management and data mining of social networks. They enable the social media companies to understand our emotions, preferences, behavior etc.

Why do we even need subject extraction?

However, social media do a good job with subject tagging, we still have a number of other sources of unstructured informations. For instance, consider the following example :

You run a grocery stores chain. Recently you have launched a co-branded card which can help you understand the buying patterns of your customers. Additionally this card can be used at other retail chains. Given, that you now will have transaction information of your customers at other retail chains, you will be in a better position to increase the wallet share of the customer at your store. For instance, if a customer buys all vegetables at your store but fruits at other, you might consider giving the customer a combo of fruits & vegetables.

In this scenario, you need to mine the name of retail store and some description around the type of purchase from the transaction description. No hash-tags or other clues, hence you need to do the hard work!

What are the challenges in subject extraction?

There are multiple other scenarios where you will need to do subject mining. Why do we call it a “hard work”?  Here are the major challenges you might face while subject mining :

Rarely do we find a ready-made dictionary to mine subjects.

Creating a subject based dictionary is extremely manual task. You need to pull a representative sample then pull those keywords and find a mapping subject.

Standardization of subjects is another challenge. For instance, take following transaction description :

“Pizza Hut paid $50”

“Pizzahut order for $30”

Now even if we build a system which can populate the first/first 2 words as the subject, we can’t find a common subject for the above two. Hence, we need to build a dictionary which can identify a common subject i.e. “Pizza Hut” for both these sentences.

Possible Framework to build a Subject Extraction Dictionary

There are two critical steps in building a subject mining dictionary:

Find the keywords occurring frequently in the text. This has been covered in detail in this article.

Create a mapping dictionary from these keywords to a standardized subject list.

For second part, here are the sub-steps you need to follow :

Find the most associated word with these frequently occurring word. (You again need to assume a minimum association threshold)

Combine the frequently occurring words with associated words to find searchable pairs.

Now all we need to do is to match subjects for each of these pairs.  We search pairs and not single words because we need enough context to search for the phrase. For example “Express” might mean “American Express” or “Coffee Express”, two words can give enough context whereas more than two words will make the dictionary too big.

Here are some examples of this process :

“Wall Mart has the best offers” 

“Tesco stores are not good with discounts”

“New Wall Mart stores are supposed to open this year”

“Tesco Stores have the coolest loyalty programs and discounts”

Most Frequent words: After removing stop-words : 1. Wall  2. Mart  3.Tesco  4. Stores

Most Associated words: 1. Wall  & Mart , 2. Mart & Wall , 3. Tesco & Stores  , 4. Stores & Tesco

Now we’ll use these words to search for the right subject.

How to automate the process of Subject Extraction Dictionary Creation?

Second step of subject mining is creating keyword to subject pairs. This step is generally done manually, but let’s take a shot at automating this process. Here is what we intend to do :

Pick up the keyword pairs found significant in the context (coming from last step).

Google Search on this pair

Pick the first 4 links which Google would give.

If two of the first 4 links are same, we return back to the URL. In case the search is not unanimous, we return “No Match Found”.

Let’s first create a function which can retrieve the first four links from Google on a search and then find if we have a common link. Here is code to do the same :

Now, let’s create a list of keywords which our code can search. (Notice that each of these keywords are quite different but Google will help us standardize them)

Its now time to test our function :

And Bingo! You see that our code was given different inputs but our code has done fairly well to spot the right set of subjects. Also notice that this dictionary is not limited by any scope of the subject. Two of its searches are Fast Food chains. Third one is an analytics website. Hence, we are creating a more generalized dictionary in this case. Now all we need to do is build rules using these keywords and map them to the matched links.

Here is the entire code :

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import urllib import json import numpy as np from urlparse import urlparse from bs4 import BeautifulSoup def searchengine(examplesearch):       encoded = urllib.quote(examplesearch)       searchResults = jsonData['responseData']['results']       links = np.empty([4, 1], dtype="S25")       i = 0      for er in searchResults:            link = er['url']            link1 = urlparse(link).netloc            links[i,0]=link1            i = i + 1       target = "No Match found"       if links[0,0] == links[1,0] or links[0,0] == links[2,0] or links[0,0] == links[3,0]:          target = links[0,0]       if links[1,0] == links[2,0] or links[1,0] == links[3,0]:          target = links[1,0]       if links[2,0] == links[3,0] :          target = links[2,0]       return [target] import numpy as np import pandas as pd import pylab as pl import os os.chdir(r"C:UsersTavishDesktop") Transaction_details = pd.read_csv("Descriptions.csv") Transaction_details["match"] = "blank" Transaction_details for i in range(0,11):        descr = Transaction_details['Descriptions'][i]      Transaction_details["match"][i] = searchengine(descr) Transaction_details


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End Notes

The approach mentioned in this article can be used to create a generalized dictionary which is not restricted to any subject. Frequently, we use the super powers of Google to auto correct the input keywords to get the most appropriate results. If this result is unanimous, it tells us Google has found a decent match from the entire web world. This approach minimizes the human effort of creating such tedious subject extraction dictionaries.

Thinkpot: Can you think of more cases where Google API’s are used? Share with us useful links of related video or article to leverage Google API

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Should You Use Nofollow, Sponsored, Or Ugc Links?

Today’s question comes from Aishwarya in Queensland, who asks:

“Is it necessary to use Nofollow, Sponsored or UGC links (rel=”sponsored”, rel=”follow” or rel=”nofollow sponsored”) in the coupons/vouchers/offers websites where there are lot of outbound links? If yes, which of the links above is better to use.”

Great question, Aishwarya!

Yes, it’s absolutely necessary to use these attributes on your outbound links.

Aside from the U.S., UK, and the EU each having its own unique laws and rules about needing to disclose, Google has its own version and mentions it in their guidelines, too. Here is an example of that.

Google also applied a penalty a few years back specifically for sites that aren’t disclosing.

I talked about how Google can tell if you are or are not disclosing in this post.

Because you asked about coupons, in particular, I’ll assume you’re a vouchers website and answer for your likely situation.

Here is how I recommend doing the attribute.


You are likely earning commissions or getting paid.

This would mean you’ll want to use sponsored because you’re not placing the link there to be nice.

This includes affiliate links, media buys, products for review, and when you have custom coupon codes that are being used to track from the page.


If you aren’t making money and just sourcing coupon codes with no monetary gain, then leave it as a follow link, and don’t worry.

That means the store is trustworthy and should have followed links.


There are multiple situations here.

1. If the website you are linking to is not something you trust, then you shouldn’t be building a page for coupons for that store.

Ask yourself, “Why would you refer website visitors to a store that isn’t trustworthy?”

It doesn’t make sense to link to them, so simply delete that page instead of using no-follow.

If you insist on having the page, then nofollow is correct but not recommended.

2. If the links are not affiliate, PR, or paid media and you added them because the store’s deal is worth mentioning, then follow is the right way to go.

This is because there is no monetary incentive and you feel the website is a good resource for your webpage visitors.

UGC & User-Submitted Coupons

Just like nofollow above, this is situational:

If the page is non-branded (ie.: “Valentine’s Coupons”) and coupons are user-submitted, use UGC.

If it is user-submitted and there is no affiliate relationship, make it UGC.

Affiliate Links

These should be sponsored because you are posting them with the goal of earning a commission.

Hopefully this helps answer your question about coupon websites and which link attributes to use.

If it doesn’t, please feel free to reach out to me so I can look at your website and understand the specific situation.

Thank you for the question!

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Major Google Adwords Changes Announced: Expanded Text Ads, New Local Search Ads & More

The updates were revealed by  Sridhar Ramaswamy, Senior Vice President of Ads & Commerce and Jerry Dischler, Vice President of Product Management, AdWords. Here’s what they had to say about exciting changes coming to AdWords:

Crazy New AdWords Stats

Google AdWords is more effective than ever and driving massive economic activity, according to Google. Among the statistics they shared in their presentation:

There are now trillions of searches on chúng tôi and over half of those searches happen on smartphones.

Nearly one third of all mobile searches on Google are related to location. In fact, location-related searches are growing 50% faster than other mobile queries.

AdWords Redesign & New Features

In the announcement, Ramaswamy writes: “To help marketers succeed in this mobile-first world, we have redesigned AdWords — from the ground-up — and re-thought everything from creatives and bidding, to workflow and measurement.”

He added that Google has realized that accounting for mobile and actually designing for mobile-first are two very different things, which had resulted in their completely changing how they think about and build AdWords.

Expanded Text Ads

Responsive Ads for Display

Individual Bid Adjustments for Device Types

Local Search Ads for chúng tôi & Google Maps

Now, you’ll have more room to sell your wares on the SERPs, with two 30-character headlines, 80 characters for description, and an auto-extracted URL with customizable domain path.

This is AMAZING and is going to make Quality Score even more important, as those top spots are going to take up more prime real estate. This is going to make anything below #2 or #3 even more useless.

Responsive Ads for Display

Advertisers just need to provide a headline, description, image and URL.  Google will do the rest.

Individual Bid Adjustments for Device Types

Bid adjustments are a super important tool for controlling how much you pay and where you appear according to different parameters. You can adjust your mobile bids, for example, by setting a percentage you’re willing to pay (more or less) against desktop.

Now, Google is also letting you set individual bid adjustments by device type, so you can choose to bid more or less for mobile, desktop or tablets. They widened the adjustment range, too, allowing up to 900% variation.

Local Search Ads for chúng tôi & Google Maps

Searchers will be able to see special offers or browse available inventory right from the Google Maps ad.

Check out the full announcement on the Inside AdWords blog!

Screenshots and photos taken by author May 2024. 

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