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Twitter is incredible for so many reasons. For some, Twitter is a platform for promotion. For others, it’s a market research tool. The great thing about Twitter is you can use it however you want.

However, what many businesses don’t address is the impact Twitter can have on search results.  Learning how to share and format your content on Twitter can directly impact your organic search results.

In this article I’ll review how Twitter works to impact search results.

Twitter and Search’s Unexpected Marriage

According to a study on social media growth, the goal of social media is to identify and attract new customers. Many marketers don’t plan on using social channels like Twitter to influence their search rankings, it just happens to be an added benefit.

Many simply plan to get a bit more traffic, but if we learn how things like anchor text and URL shortened links play in to search results, we may be able to optimize our ability to draw users from both social and search.

According to study done by SEOMoz, social is shockingly well correlated to search engine results. More than 80% of people surveyed believe that in the future social signals will influence rankings at both a domain level and page level.

It only makes sense for search engines to incorporate a human element in their results. Traditional SEO tactics garnered spammy and low quality search results. From a search perspective ranking domains and pages, based on what people are talking about, makes results much more relevant and timely.

Your Authority Matters

The chart below illustrates the same study done by SEOMoz. The study surveyed 132 SEO experts, as they ranked their most important to least important social media factors 1-10. According to the survey “Authority of Tweets” and “# of Tweets,” were the most influential social media factors that played in these SEO expert’s search results.

Caption: SEO Expert survey: On a scale from 1-10, how important are social media factors in search rankings? 1 being most important and 10 being least.

“We do look at the social authority of a user. We look at how many people you follow, how many follow you, and this can add a little weight to a listing in regular search results. It carries much more weight in Bing Social Search, where tweets from more authoritative people will flow to the top when best match relevancy is used.” –Bing via Search Engine Land.

Building Links On Twitter

A topic that many SEO experts are “up in the air” on is Twitter’s power to replicate consistently replicate link building’s benefits. Although Twitter links are “nofollowed,” the importance of the link depends strictly on the number of tweets and retweets that are aggregated on websites. A good deal of websites put their Twitter feeds on to their webpage, which means that every time your content is retweeted by them it builds links. If this conclusion is valid, one could assume that link authority can be transferred to retweeted links. For example; The Retweetist is just one of many sites that aggregate Retweets and follow links.

Caption:  Blue highlight illustrates a DoFollowed link

Real Results

There have been numerous case studies where a tweeted link that goes “viral” gets redirected around Twitter, and the host site ends up ranking for anchor text keywords within the article.

He received 110 Facebook Likes and 1 Tweet – He began ranking for the term “yoga mat compare.”

After 117 Facebook Likes and 4 retweets- He began ranking on the first page for the term “yoga mat compare.”

After 118 Facebook Likes, 4 retweets and 1 link shared on Yoga related sites- he began ranking for “luxury yoga mats.”

Marcus Taylor concluded after his study that, “you can see a progressive increase in not only rankings but the variety of keywords ranking…if I were to carry on acquiring more and more likes and tweets I could potentially attain competitive rankings for these keywords.”

So it seems that collective tweets that are retweeted, pass on link juice by being disseminated across the web on website Twitter feeds. Marcus Taylor questions, “How does this affect SEO? Right this moment I think it’s safe to assume that acquiring likes, tweets and other social signals is a fairly good strategy for not only improving indexation but also rankings.”

Ultimately, establishing Twitter authority improves long term organic search relevance for your site when you share content. Make sure your content’s keywords text is optimized because it seems this is taken to consideration when ranking on search, giving your website traditional SEO benefit from social behaviors.

Caption: Perfect Market’s tweet, recapping the Search Marketing Expo

What This Means For You

Establishing thought leadership on Twitter is important. Easier said than done right? We know that Twitter users are portals for blog promotions; a tweeted link gets power from author authority and retweets. Think of your Twitter account as a pyramid. The higher you are able to drop a link from, the more of the pyramid you will be able to capture; and ultimately the more retweets from authoritative twitter-ers.

To find author authority, chúng tôi gives a list of “experts” when they index search. The goal is to find a niche within Twitter that gets your content to fall majestically through Twitter streams. As Google modifies it’s algorithm to incorporate end user relevance, through a hybrid crowd sourced social indexing model; the SEO waters will become cloudier. Social media, especially Twitter, is a powerful tool for marketers to rank for search terms without spending years on link building campaigns. SEO is no longer a systematic labor intensive process of seeking out partnerships. It seems to be a marriage of engagement in social sharing as well as SEO best practices.

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Semantic Search: How It Works & Who It’s For

For simple user queries, a search engine can reliably find the correct content using keyword matching alone.

A “red toaster” query pulls up all of the products with “toaster” in the title or description, and red in the color attribute.

Add synonyms like maroon for red, and you can match even more toasters.

But things start to become more difficult quickly: You have to add these synonyms yourself, and your search will also bring up toaster ovens.

This is where semantic search comes in.

Semantic search attempts to apply user intent and the meaning (or semantics) of words and phrases to find the right content.

It goes beyond keyword matching by using information that might not be present immediately in the text (the keywords themselves) but is closely tied to what the searcher wants.

For example, finding a sweater with the query “sweater” or even “sweeter” is no problem for keyword search, while the queries “warm clothing” or “how can I keep my body warm in the winter?” are better served by semantic search.

As you can imagine, attempting to go beyond the surface-level information embedded in the text is a complex endeavor.

It has been attempted by many and incorporates a lot of different components.

Additionally, as with anything that shows great promise, semantic search is a term that is sometimes used for search that doesn’t truly live up to the name.

What Are The Elements Of Semantic Search?

Semantic search applies user intent, context, and conceptual meanings to match a user query to the corresponding content.

These components work together to retrieve and rank results based on meaning.

One of the most fundamental pieces is that of context.


The context in which a search happens is important for understanding what a searcher is trying to find.

Context can be as simple as the locale (an American searching for “football” wants something different compared to a Brit searching the same thing) or much more complex.

An intelligent search engine will use the context on both a personal level and a group level.

The personal level influencing of results is called, appropriately enough, personalization.

Personalization will use that individual searcher’s affinities, previous searches, and previous interactions to return the content that is best suited to the current query.

It is applicable to all kinds of searching, but semantic search can go even further.

Again, this displays how semantic search can bring in intelligence to search, in this case, intelligence via user behavior.

Semantic search can also leverage the context within the text.

We’ve already discussed that synonyms are useful in all kinds of search, and can improve keyword search by expanding the matches for queries to related content.

But we know as well that synonyms are not universal – sometimes two words are equivalent in one context, and not in another.

When someone searches for “football players”, what are the right results?

The answer will be different in Kent, Ohio than in Kent, United Kingdom.

A query like “tampa bay football players”, however, probably doesn’t need to know where the searcher is located.

Adding a blanket synonym that made football and soccer equivalent would have led to a poor experience when that searcher saw the Tampa Bay Rowdies soccer club next to Ron Gronkowski.

(Of course, if we know that the searcher would have preferred to see the Tampa Bay Rowdies, the search engine can take that into account!)

This is an example of query understanding via semantic search.

User Intent

The ultimate goal of any search engine is to help the user be successful in completing a task.

That task might be to read news articles, buy clothing, or find a document.

The search engine needs to figure out what the user wants to do, or what the user intent is.

We can see this when searching on an ecommerce website.

As the user types the query “jordans”, the search automatically filters on the category, “Shoes.”

This anticipates that the user intent is to find shoes, and not jordan almonds (which would be in the “Food & Snacks” category).

By getting ahead of the user intent, the search engine can return the most relevant results, and not distract the user with items that match textually, but not relevantly.

This can be all the more relevant when applying a sort on top of the search, like price from lowest to highest.

This is an example of query categorization.

Categorizing the query and limiting the results set will ensure that only relevant results appear.

Difference Between Keyword And Semantic Search

We have already seen ways in which semantic search is intelligent, but it’s worth looking more at how it is different from keyword search.

While keyword search engines also bring in natural language processing to improve this word-to-word matching – through methods such as using synonyms, removing stop words, ignoring plurals – that processing still relies on matching words to words.

But semantic search can return results where there is no matching text, but anyone with knowledge of the domain can see that there are plainly good matches.

This ties into the big difference between keyword search and semantic search, which is how matching between query and records occurs.

To simplify things some, keyword search occurs by matching on text.

“Soap” will always match “soap” or “soapy ”, because of the overlap in textual quality.

More specifically, there are enough matching letters (or characters) to tell the engine that a user searching for one will want the other.

That same matching will also tell the engine that the query soap is a more likely match for the word “soup” than the word “detergent.”

That is unless the owner of the search engine has told the engine ahead of time that soap and detergent are equivalents, in which case the search engine will “pretend” that detergent is actually soap when it is determining similarity.

Keyword-based search engines can also use tools like synonyms, alternatives, or query word removal – all types of query expansion and relaxation – to help with this information retrieval task.

NLP and NLU tools like typo tolerance, tokenization, and normalization also work to improve retrieval.

While these all help to provide improved results, they can fall short with more intelligent matching, and matching on concepts.

Semantic Search Matches On Concepts

Because semantic search is matching on concepts, the search engine can no longer determine whether records are relevant based on how many characters two words share.

Again, think about “soap” versus “soup” versus “detergent.”

Or more complex queries, like “laundry cleaner”, “remove stains clothing”, or “how do I get grass stains out of denim?”

You can even include things like image searching!

A real-world analogy of this would be a customer asking an employee where a “toilet unclogged” is located.

An employee with only a pure keyword-esque understanding of the request would fail it unless the store explicitly refers to their plungers, drain cleaners, and toilet augers as “toilet uncloggers.”

But, we would hope, the employee is wise enough to make the connection between the various terms and direct the customer to the right aisle.

(Perhaps the employee knows the different terms, or synonyms, a customer can use for any given product).

A succinct way of summarizing what semantic search does is to say that semantic search brings increased intelligence to match on concepts more than words, through the use of vector search.

With this intelligence, semantic search can perform in a more human-like manner, like a searcher finding dresses and suits when searching fancy, with not a jean in sight.

What Is Semantic Search Not?

By now, semantic search should be clear as a powerful method for improving search quality.

As such, you should not be surprised to learn that the meaning of semantic search has been applied more and more broadly.

Often, these search experiences don’t always warrant the name.

And while there is no official definition of semantic search, we can say that it is search that goes beyond traditional keyword-based search.

It does this by incorporating real-world knowledge to derive user intent based on the meaning of queries and content.

It’s true, tokenization does require some real-world knowledge about language construction, and synonyms apply understanding of conceptual matches.

However, they lack, in most cases, an artificial intelligence that is required for search to rise to the level of semantic.

Powered By Vector Search

It is this last bit that makes semantic search both powerful and difficult.

Generally, with the term semantic search, there is an implicit understanding that there is some level of machine learning involved.

Almost as often, this also involves vector search.

Vector search works by encoding details about an item into vectors and then comparing vectors to determine which are most similar.

Again, even a simple example can help.

Take two phrases: “Toyota Prius” and “steak.”

And now let’s compare those to “hybrid.”

Which of the first two are more similar?

Neither would match textually, but you probably would say that “Toyota Prius” is the more similar of the two.

You can say this because you know that a “Prius” is a type of hybrid vehicle because you have seen “Toyota Prius” in a similar context as the word hybrid, such as “Toyota Prius is a hybrid worth considering,” or “hybrid vehicles like the Toyota Prius.”

You’re pretty sure, however, you’ve never seen “steak” and ”hybrid” in such close quarters.

Plotting Vectors To Find Similarity

This is generally how vector search works as well.

A machine learning model takes thousands or millions of examples from the web, books, or other sources and uses this information to then make predictions.

Of course, it is not feasible for the model to go through comparisons one-by-one ( “Are Toyota Prius and hybrid seen together often? How about hybrid and steak?”) and so what happens instead is that the models will encode patterns that it notices about the different phrases.

It’s similar to how you might look at a phrase and say, “this one is positive” or “that one includes a color.”

Except in machine learning the language model doesn’t work so transparently (which is also why language models can be difficult to debug).

These encodings are stored in a vector or a long list of numeric values.

Then, vector search uses math to calculate how similar different vectors are.

Another way to think about the similarity measurements that vector search does is to imagine the vectors plotted out.

This is mind-blowingly difficult if you try to think of a vector plotted into hundreds of dimensions.

If you instead imagine a vector plotted into three dimensions, the principle is the same.

These vectors form a line when plotted, and the question is: which of these lines are closest to each other?

The lines for “steak” and “beef” will be closer than the lines for “steak” and “car” , and so are more similar.

This principle is called a vector, or cosine, similarity.

Vector similarity has a lot of applications.

It can make recommendations based on the previously purchased products, find the most similar image, and can determine which items best match semantically when compared to a user’s query.


Semantic search is a powerful tool for search applications that have come to the forefront with the rise of powerful deep learning models and the hardware to support them.

While we’ve touched on a number of different common applications here, there are even more that use vector search and AI.

Even image search or extracting metadata from images can fall under semantic search.

We’re in exciting times!

And, yet, its application is still early and its known powerfulness can lend itself to a misappropriation of the term.

There are many components in a semantic search pipeline, and getting each one correct is important.

When done correctly, semantic search will use real-world knowledge, especially through machine learning and vector similarity, to match a user query to the corresponding content.

More resources:

Featured Image: magic pictures/Shutterstock

How To Write A Results Section

A results section is where you report the main findings of the data collection and analysis you conducted for your thesis or dissertation. You should report all relevant results concisely and objectively, in a logical order. Don’t include subjective interpretations of why you found these results or what they mean—any evaluation should be saved for the discussion section.

How to write a results section

When conducting research, it’s important to report the results of your study prior to discussing your interpretations of it. This gives your reader a clear idea of exactly what you found and keeps the data itself separate from your subjective analysis.

Here are a few best practices:

Your results should always be written in the past tense.

While the length of this section depends on how much data you collected and analyzed, it should be written as concisely as possible.

Only include results that are directly relevant to answering your research questions. Avoid speculative or interpretative words like “appears” or “implies.”

If you have other results you’d like to include, consider adding them to an appendix or footnotes.

Always start out with your broadest results first, and then flow into your more granular (but still relevant) ones. Think of it like a shoe store: first discuss the shoes as a whole, then the sneakers, boots, sandals, etc.

NoteIn a few fields, including a separate results section is not common practice. In some types of qualitative research, such as ethnographies, the results are often woven together with the discussion. Be sure to check your departmental guidelines for any formatting questions.

Reporting quantitative research results

If you conducted quantitative research, you’ll likely be working with the results of some sort of statistical analysis.

Your results section should report the results of any statistical tests you used to compare groups or assess relationships between variables. It should also state whether or not each hypothesis was supported.

The most logical way to structure quantitative results is to frame them around your research questions or hypotheses. For each question or hypothesis, share:

A reminder of the type of analysis you used (e.g., a two-sample t test or simple linear regression). A more detailed description of your analysis should go in your methodology section.

A concise summary of each relevant result, both positive and negative. This can include any relevant descriptive statistics (e.g., means and standard deviations) as well as inferential statistics (e.g., t scores, degrees of freedom, and p values). Remember, these numbers are often placed in parentheses.

A brief statement of how each result relates to the question, or whether the hypothesis was supported. You can briefly mention any results that didn’t fit with your expectations and assumptions, but save any speculation on their meaning or consequences for your discussion and conclusion.

TipThe statistics you report (and the conventions for presenting them) depend both on the type of analysis you conducted and the style guide you are following. For example, there are specific rules for writing a results section in APA Style.

If you’re unsure, read the results sections of other papers in your field. This can help you get a clear sense of what information to include.

A note on tables and figures

In quantitative research, it’s often helpful to include visual elements such as graphs, charts, and tables, but only if they are directly relevant to your results. Give these elements clear, descriptive titles and labels so that your reader can easily understand what is being shown. If you want to include any other visual elements that are more tangential in nature, consider adding a figure and table list.

As a rule of thumb:

Tables are used to communicate exact values, giving a concise overview of various results

Graphs and charts are used to visualize trends and relationships, giving an at-a-glance illustration of key findings

Don’t forget to also mention any tables and figures you used within the text of your results section. Summarize or elaborate on specific aspects you think your reader should know about rather than merely restating the same numbers already shown.

Example: Reporting survey results

A two-sample t test was used to test the hypothesis that higher social distance from environmental problems would reduce the intent to donate to environmental organizations, with donation intention (recorded as a score from 1 to 10) as the outcome variable and social distance (categorized as either a low or high level of social distance) as the predictor variable.Social distance was found to be positively correlated with donation intention, t(98) = 12.19, p

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Reporting qualitative research results

In qualitative research, your results might not all be directly related to specific hypotheses. In this case, you can structure your results section around key themes or topics that emerged from your analysis of the data.

For each theme, start with general observations about what the data showed. You can mention:

Recurring points of agreement or disagreement

Patterns and trends

Particularly significant snippets from individual responses

Next, clarify and support these points with direct quotations. Be sure to report any relevant demographic information about participants. Further information (such as full transcripts, if appropriate) can be included in an appendix.

Example: Reporting interview results

When asked about video games as a form of art, the respondents tended to believe that video games themselves are not an art form, but agreed that creativity is involved in their production. The criteria used to identify artistic video games included design, story, music, and creative chúng tôi respondent (male, 24) noted a difference in creativity between popular video game genres:

“I think that in role-playing games, there’s more attention to character design, to world design, because the whole story is important and more attention is paid to certain game elements […] so that perhaps you do need bigger teams of creative experts than in an average shooter or something.”

Responses suggest that video game consumers consider some types of games to have more artistic potential than others.

Results vs. discussion vs. conclusion

Your results section should objectively report your findings, presenting only brief observations in relation to each question, hypothesis, or theme.

It should not speculate about the meaning of the results or attempt to answer your main research question. Detailed interpretation of your results is more suitable for your discussion section, while synthesis of your results into an overall answer to your main research question is best left for your conclusion.

Checklist: Research results Checklist: Research results




Well done!

You’ve finished writing up your results! Use the other checklists to further improve your thesis.

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Google’s Url Parameter Tool Does Not Remove Urls From Search Results

Google’s John Mueller cleared up a misconception about the URL parameter tool in Search Console, saying it doesn’t actually remove URLs.

This topic came up in a recent Google Webmaster Central hangout on YouTube when a question was asked about whether the URL parameter tool still works.

Google has not yet ported the URL parameter tool from the classic version of Search Console to the new version.

Despite not being available in the new Search Console, the URL parameter tool is still effective. You just have to revert back and forth from the old Search Console in order to use it.

However, a follow-up question would indicate the webmaster had the wrong expectations when it comes to what the tool is meant to do.

URL Parameter Tool Does Not Remove URLs

In their question to Mueller, the site owner mentioned they added a parameter to be dropped but the change was not immediately visible in search results.

That’s not what the tool is intended to do, Mueller says, it’s designed to refine the crawling of URLs.

You can use the tool to add a parameter you no longer want to be crawled, and over time those URLs would eventually drop out of search results because Google stopped crawling them.

It’s not a case where you add a parameter to the tool and all of a sudden a bunch of URLs with that parameter are removed from Google’s index.

So the URL parameter tool still works, as long as it’s being used as intended.

Hear the full question and answer below, starting at the 46:44 mark.

“The URL parameter handling tool would not remove URLs from the search results. It’s really only to refine the crawling of URLs.

So it’s not something where we would say you add this parameter to that tool and then suddenly all those pages disappear from search results.

It’s more that, over time, we would crawl those URLs less and over time they would drop out from the search results but it wouldn’t be any immediate change there.”

How To Delete Your Genshin Impact Account

If you no longer play Genshin Impact, you can delete it.

In early 2023, there isn’t an option to delete your Genshin Impact account.

As a result, you need to contact Genshin Impact support.

However, in late 2023, Genshin Impact introduced the “Delete account” feature.

Hence, you’ll be able to delete your account in your profile settings.

In this guide, you’ll learn how to delete your Genshin Impact account, if you can delete it, and how to reset it.

How to delete your Genshin Impact account

To delete your Genshin Impact account, you need to go to your profile settings.

Lastly, follow the on-screen instructions to delete your Genshin Impact account.

After you’ve requested the deletion of your account, it’ll be permanently deleted after 30 days.

During the 30 days, you can reactivate it on the miHoYo website.

If you didn’t reactivate it after 30 days, your account will be permanently deleted and you won’t be able to retrieve it.

Here are 9 steps to delete your Genshin Impact account:

The first step is to go to the official Genshin Impact website.

Once you’re on the website, you’ll see a “Log In” icon on the header of it.

2. Log in to your Genshin Impact account

Now, you need to log in to your Genshin Impact account.

The pop-up contains a couple of fields.

This includes “Username/Email” and “Password”.

Enter your Genshin Impact username/email and password.

3. Go to your account settings

After you’ve logged into your Genshin Impact account, you’ll see your email address on the header of the site.

This will open a chat box containing a couple of links.

This includes “Account” and “Log Out”.

4. Log in to your Genshin Impact account

Once you’re on the site, you need to log in to your Genshin Impact account again.

Firstly, enter your Genshin Impact username or email address in the “Username/Email” field.

Next, enter your password in the “Password” field.

After you’ve logged into your Genshin Impact account, you’ll land on your account settings.

On the left sidebar, you’ll see 3 options.

This includes “Account Information”, “Account Security Settings”, and “Login Devices”.

At the bottom of your account security settings, you’ll see a link to delete your Genshin Impact account.

The pop-up message states that your account will be deleted once the process is complete.

It also states that your miHoYo account including your personal information and data will be deleted permanently.

7. Complete the security verification

It’s recommended that you use the “Email Verification” method.

Next, check your email for the verification code and copy it.

8. Confirm the deletion of your account

After you’ve completed the security verification, another pop-up message will appear.

The message says that you have completed the security verification process.

It also states that it takes 30 days for your account to be deleted.

Before 30 days, you can still reactive your account by logging in to it.

However, if you did not reactivate your account, it will be automatically deleted and you won’t be able to recover it.

9. Log out of your account

The message states that you’ve successfully submitted an account deletion request.

It also states that unless you reactivate your account, you won’t be able to use it.

Now, you need to wait for 30 days for your Genshin Impact account to be automatically deleted!

Can you delete your Genshin Impact account?

Yes, you can delete your Genshin Impact account.

Then, follow the on-screen instructions to delete your account.

As of late 2023, you don’t have to contact Genshin Impact support to request the deletion of your account.

Instead, you can delete your account in your account security settings.

How can I reset my Genshin Impact account?

You can reset your Genshin Impact account by creating a new account or switching to a new server.

Firstly, if you create a new Genshin Impact account, your progress will be reset.

Similarly, if you switch to a new server, your progress will be reset as well.

This is because data cannot be transferred across servers.


Before late 2023, users were required to contact Genshin Impact support to request the deletion of their accounts.

However, in late 2023, Genshin Impact introduced the “Delete Account” feature.

As a result, users are able to delete their accounts in their account security settings.

Further reading

175+ Funny Genshin Impact Signatures

How to Find Your Genshin Impact Username

How to Change Genshin Impact Language

How To Add Friends In Genshin Impact

On Genshin Impact, you can add friends to your Friends List.

Adding friends allow you to check their player profile easily and join them for a co-op session.

For easier recognition, you can also assign a nickname for your friends.

In addition, you can send your friends an in-game private message.

You can have a party of up to 4 players in co-op mode.

You can also cross-play the co-op mode between PC, mobile, and PSN as long as you and your friends are on the same server.

In this guide, you’ll learn how to add friends in Genshin Impact so that you can play co-op mode with them.

You’ll also learn if you can add friends from different servers in Genshin Impact and why can’t you join your friends in Genshin Impact.

How to add friends in Genshin Impact

To add friends in Genshin Impact, you need to ask your friend to send you their UID.

Then, you’ll be able to add them by opening the Paimon menu, navigating to “Friends”, and pasting their UID.

In the “Add Friend” menu, you can search for players and send friend requests using the player’s UID.

A UID stands for a unique identifier, which can be found in the bottom right of your screen.

Your friend does not need to be online to receive a friend request.

Once your friend is online, they need to accept your friend request.

After you’ve added a friend on Genshin Impact, you can play co-op with them at rank 16.

However, you need to be on the same server as them.

For example, if you’re playing in the “Asia” server, your friend needs to be in the “Asia” server as well.

Here are 3 steps to add friends in Genshin Impact:

1. Ask your friend to send you their UID

The first step is to ask your friend to send your their UID (unique identifier).

To add someone on Genshin Impact, you need their UID.

You cannot add someone using their username.

The UID can be found in a couple of places.

Firstly, it is located at the bottom right corner of the screen.

Secondly, you can find it on the Paimon menu.

To do so, press “Esc” on your keyboard if you’re playing Genshin Impact on a PC.

After you’ve pressed “Esc” on your keyboard, the Paimon menu will open.

On the menu, you’ll see your UID under your profile picture.

You need to ask your friend to follow the above steps to send you their UID.

2. Navigate to “Friends”

Once you’ve received your friend’s UID, you can now add them in Genshin Impact.

Firstly, open the Paimon menu by pressing “Esc” on your keyboard if you’re playing Genshin Impact on a PC.

After you’ve pressed “Esc”, the Paimon menu will open.

On the menu, you’ll see several options.

This includes “Party Setup”, “Friends”, “Achievements”, and more.

3. Add your friend by their UID

On the top navigation bar, you’ll see 3 icons.

This includes a name card icon, an add friends icon, and a timer icon.

On the “Add Friends” menu, you’ll see a “Search and add friends by UID” search bar.

After you’ve searched for your friend using their UID, you’ll be able to add them as a friend on Genshin Impact!

Keep in mind that a total of 45 friends can be added in Genshin Impact.

Can you add friends from different servers in Genshin impact?

No, you cannot add friends from different servers in Genshin Impact.

To add someone on Genshin Impact, you need to be on the same server as them.

Similarly, you need to be on the same server as your friend to play co-op with them.

Once you’re on the same server with your friend, you’ll be able to play co-op with them even if you’re on a different platform.

Why can’t I join my friends in Genshin Impact?

You and your friend need to be rank 16 before you can play co-op with them.

Another reason why you can’t join your friends is that you’re on a different server than them.

To play co-op mode with your friend, you need to be on the same server as them.


Once you and your friend have reached rank 16, you’ll be able to play co-op mode with them.

However, you need to add them as a friend in Genshin Impact first so that they’ll appear in your friends list.

If you’ve activated the cross-save feature on Playstation, the list will be split into two.

This includes “Genshin Impact Friends” and “Genshin Impact Friends on PlayStation Network”.

In co-op mode, cross-play is available between PC, mobile, and PSN platforms.

However, you need to be on the same server as your friend.

For example, if your friend is playing in the “Asia” server, you need to be in the “Asia” server as well.

If you haven’t played in the “Asia” server before, your progress will be restarted on it.

However, your progress will be saved on the old server when you switch back to it.

Further reading

300+ Good, Aesthetic, and Cool Usernames for Genshin Impact

How to Change Your Genshin Impact Username or Name

How to Change Servers in Genshin Impact

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