https://brightdata.com/licensehttps://brightdata.com/license
Access detailed insights with our Instagram datasets, featuring follower counts, verified status, account types, and engagement scores. Explore post information including URLs, descriptions, hashtags, comments, likes, media, posting dates, locations, and reel URLs. Perfect for understanding user engagement and content trends to drive informed decisions and optimize your social media strategies. Over 750M records available Price starts at $250/100K records Data formats are available in JSON, NDJSON, CSV, XLSX and Parquet. 100% ethical and compliant data collection Included datapoints:
Account Fbid Id Followers Posts Count Is Business Account Is Professional Account Is Verified Avg Engagement External Url Biography Business Category Name Category Name Post Hashtags Following Posts Profile Image Link Profile URL Profile Name Highlights Count Highlights Full Name Is Private Bio Hashtags URL Is Joined Recently And much more
In 2021, there were 1.21 billion monthly active users of Meta's Instagram, making up over 28 percent of the world's internet users. By 2025, it has been forecast that there will be 1.44 billion monthly active users of the social media platform, which would account for 31.2 percent of global internet users.
How popular is Instagram?
Instagram, as of January 2022, was the fourth most popular social media platform in the world in terms of user numbers. YouTube and WhatsApp ranked in second and third place, respectively, whilst Facebook remained the most popular, with almost three billion monthly active users worldwide.
India had the largest number of Instagram users as of January 2022, with a total of over 230 million users in the country. The second-largest Instagram audience could be found in the United States, with almost 160 million people subscribing to the photo and video sharing app.
Gen Z and Instagram
As of September 2021, Gen Z users in the United States spent an average of five hours per week on Instagram. Although Instagram ranked third in terms of hours per week spent on the platform, Gen Z users spent considerably more time on TikTok, amounting to a weekly average of over 10 hours being spent on the mobile-first video app.
Most followed accounts on Instagram
As of May 2022, Instagram’s own account had 504.37 million followers. In terms of celebrities, Portuguese footballer Cristiano Ronaldo (@chistiano) had over 440.41 million followers on the social network. Moreover, the average media value of an Instagram post by Ronaldo was over 985,000 U.S. dollars.
The most liked post on Instagram as of May 2022 was Photo of an Egg, which was posted in 2019 by the account @world_record_egg. Photo of an Egg has not only exceeded 55 million likes on the platform, but it also has nearly 3.5 million comments, and the account itself has over 4.5 million Instagram followers. After mysterious posts published by the account, World Record Egg revealed itself as part of a mental health campaign aimed at the difficulties and demands of using social media.
Cristiano Ronaldo has one of the most popular Instagram accounts as of April 2024.
The Portuguese footballer is the most-followed person on the photo sharing app platform with 628 million followers. Instagram's own account was ranked first with roughly 672 million followers.
How popular is Instagram?
Instagram is a photo-sharing social networking service that enables users to take pictures and edit them with filters. The platform allows users to post and share their images online and directly with their friends and followers on the social network. The cross-platform app reached one billion monthly active users in mid-2018. In 2020, there were over 114 million Instagram users in the United States and experts project this figure to surpass 127 million users in 2023.
Who uses Instagram?
Instagram audiences are predominantly young – recent data states that almost 60 percent of U.S. Instagram users are aged 34 years or younger. Fall 2020 data reveals that Instagram is also one of the most popular social media for teens and one of the social networks with the biggest reach among teens in the United States.
Celebrity influencers on Instagram
Many celebrities and athletes are brand spokespeople and generate additional income with social media advertising and sponsored content. Unsurprisingly, Ronaldo ranked first again, as the average media value of one of his Instagram posts was 985,441 U.S. dollars.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Instagram data-download example dataset
In this repository you can find a data-set consisting of 11 personal Instagram archives, or Data-Download Packages (DDPs).
How the data was generated
These Instagram accounts were all new and generated by a group of researchers who were interested to figure out in detail the structure and variety in structure of these Instagram DDPs. The participants user the Instagram account extensively for approximately a week. The participants also intensively communicated with each other so that the data can be used as an example of a network.
The data was primarily generated to evaluate the performance of de-identification software. Therefore, the text in the DDPs particularly contain many randomly chosen (Dutch) first names, phone numbers, e-mail addresses and URLS. In addition, the images in the DDPs contain many faces and text as well. The DDPs contain faces and text (usernames) of third parties. However, only content of so-called `professional accounts' are shared, such as accounts of famous individuals or institutions who self-consciously and actively seek publicity, and these sources are easily publicly available. Furthermore, the DDPs do not contain sensitive personal data of these individuals.
Obtaining your Instagram DDP
After using the Instagram accounts intensively for approximately a week, the participants requested their personal Instagram DDPs by using the following steps. You can follow these steps yourself if you are interested in your personal Instagram DDP.
Instagram then delivered the data in a compressed zip folder with the format username_YYYYMMDD.zip (i.e., Instagram handle and date of download) to the participant, and the participants shared these DDPs with us.
Data cleaning
To comply with the Instagram user agreement, participants shared their full name, phone number and e-mail address. In addition, Instagram logged the i.p. addresses the participant used during their active period on Instagram. After colleting the DDPs, we manually replaced such information with random replacements such that the DDps shared here do not contain any personal data of the participants.
How this data-set can be used
This data-set was generated with the intention to evaluate the performance of the de-identification software. We invite other researchers to use this data-set for example to investigate what type of data can be found in Instagram DDPs or to investigate the structure of Instagram DDPs. The packages can also be used for example data-analyses, although no substantive research questions can be answered using this data as the data does not reflect how research subjects behave `in the wild'.
Authors
The data collection is executed by Laura Boeschoten, Ruben van den Goorbergh and Daniel Oberski of Utrecht University. For questions, please contact l.boeschoten@uu.nl.
Acknowledgments
The researchers would like to thank everyone who participated in this data-generation project.
https://brightdata.com/licensehttps://brightdata.com/license
Gain valuable insights with our comprehensive Social Media Dataset, designed to help businesses, marketers, and analysts track trends, monitor engagement, and optimize strategies. This dataset provides structured and reliable social media data from multiple platforms.
Dataset Features
User Profiles: Access public social media profiles, including usernames, bios, follower counts, engagement metrics, and more. Ideal for audience analysis, influencer marketing, and competitive research. Posts & Content: Extract posts, captions, hashtags, media (images/videos), timestamps, and engagement metrics such as likes, shares, and comments. Useful for trend analysis, sentiment tracking, and content strategy optimization. Comments & Interactions: Analyze user interactions, including replies, mentions, and discussions. This data helps brands understand audience sentiment and engagement patterns. Hashtag & Trend Tracking: Monitor trending hashtags, topics, and viral content across platforms to stay ahead of industry trends and consumer interests.
Customizable Subsets for Specific Needs Our Social Media Dataset is fully customizable, allowing you to filter data based on platform, region, keywords, engagement levels, or specific user profiles. Whether you need a broad dataset for market research or a focused subset for brand monitoring, we tailor the dataset to your needs.
Popular Use Cases
Brand Monitoring & Reputation Management: Track brand mentions, customer feedback, and sentiment analysis to manage online reputation effectively. Influencer Marketing & Audience Analysis: Identify key influencers, analyze engagement metrics, and optimize influencer partnerships. Competitive Intelligence: Monitor competitor activity, content performance, and audience engagement to refine marketing strategies. Market Research & Consumer Insights: Analyze social media trends, customer preferences, and emerging topics to inform business decisions. AI & Predictive Analytics: Leverage structured social media data for AI-driven trend forecasting, sentiment analysis, and automated content recommendations.
Whether you're tracking brand sentiment, analyzing audience engagement, or monitoring industry trends, our Social Media Dataset provides the structured data you need. Get started today and customize your dataset to fit your business objectives.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Kindly refer to my paper for more information. Please cite my work if you use my dataset in any work : K. R. Purba, D. Asirvatham and R. K. Murugesan, "Classification of instagram fake users using supervised machine learning algorithms," International Journal of Electrical and Computer Engineering (IJECE), vol. 10, no. 3, pp. 2763-2772, 2020.
The dataset was collected using web scraping from third-party Instagram websites, to capture their metadata and up to 12 latest media posts from each user. The collection process was executed from September 1st, 2019, until September 20th, 2019. The dataset contains authentic users and fake users, which were filtered using human annotators. The authentic users were taken from followers of 24 private university pages (8 Indonesian, 8 Malaysian, 8 Australian) on Instagram. To reduce the number of users, they are picked using proportional random sampling based on their source university. All private users were removed, which is a total of 31,335 out of 63,795 users (49.11%). The final number of public users used in this research was 32,460 users.
Var name | Feature name | Description pos | Num posts | Number of total posts that the user has ever posted. flg | Num following | Number of following flr | Num followers | Number of followers bl | Biography length | Length (number of characters) of the user's biography pic | Picture availability | Value 0 if the user has no profile picture, or 1 if has lin | Link availability | Value 0 if the user has no external URL, or 1 if has cl | Average caption length | The average number of character of captions in media cz | Caption zero | Percentage (0.0 to 1.0) of captions that has almost zero (<=3) length ni | Non image percentage | Percentage (0.0 to 1.0) of non-image media. There are three types of media on an Instagram post, i.e. image, video, carousel erl | Engagement rate (Like) | Engagement rate (ER) is commonly defined as (num likes) divide by (num media) divide by (num followers) erc | Engagement rate (Comm.) | Similar to ER like, but it is for comments lt | Location tag percentage | Percentage (0.0 to 1.0) of posts tagged with location hc | Average hashtag count | Average number of hashtags used in a post pr | Promotional keywords | Average use of promotional keywords in hashtag, i.e. {regrann, contest, repost, giveaway, mention, share, give away, quiz} fo | Followers keywords | Average use of followers hunter keywords in hashtag, i.e. {follow, like, folback, follback, f4f} cs | Cosine similarity | Average cosine similarity of between all pair of two posts a user has pi | Post interval | Average interval between posts (in hours)
Output : 2-class User classes : r (real/authentic user), f (fake user / bought followers) 4-class User classes : r (authentic/real user), a (active fake user), i (inactive fake user), s (spammer fake user) Note that the 3 fake user classes (a, i, s) were judged by human annotators.
As of April 2025, almost 32 percent of global Instagram audiences were aged between 25 and 34 years, and 29.5 percent of users were aged between 25 and 34 years. Overall, 16.3 percent of users belonged to the 35 to 44 year age group. Instagram users With roughly one billion monthly active users, Instagram belongs to the most popular social networks worldwide. The social photo sharing app is especially popular in India and in the United States, which have respectively 413.85 million and 171.7 million Instagram users each. Instagram features One of the most popular features of Instagram is Stories. Users can post photos and videos to their Stories stream and the content is live for others to view for 24 hours before it disappears. In January 2019, the company reported that there were 500 million daily active Instagram Stories users. Instagram Stories directly competes with Snapchat, another photo sharing app that initially became famous due to it’s “vanishing photos” feature. As of the first quarter of 2025, Snapchat had 460 million daily active users.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
These four datasets are gathered from Instagram users who were chosen randomly.
The MainDataset encompasses data for 818 users. The TestDataset encompasses data for 78 users.
Data gathered for each user includes :
1- number of posts
2- number of followers
3- number of followings
4- number of likes for the tenth previous post
5- number of likes for the eleventh previous post
6- number of likes for the twelfth previous post
7- number of self-presenting posts from nine previous posts
8- gender
The MainDataset_after_150_days and TestDataset_after_150_days encompass data of the users of the Main data set and the Test data set, respectively, for after 150 days. For example, User_1 in the MainDataset has 486 posts and in the MainDataset_after_150_days has 562 posts, which means over the course of 150 days he had published 76 posts.
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License information was derived automatically
Analysis of ‘📸 Most Followed on Instagram’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/most-followed-on-instagrame on 13 February 2022.
--- Dataset description provided by original source is as follows ---
Data from Iconsquare.com. The company delivers Instagram analytics to tens of thousands of businesses, agencies and individuals.
- BRAND
- CATEGORIES 1
- CATEGORIES 2
- FOLLOWERS
- ER - Average engagement rate of all media. Engagement rate is based on the likes and comments received divided by the number of followers at the time of the post.
- POSTS ON HASHTAG
- MEDIA POSTED
Source: ICONSQUARE
This dataset was created by Social Media Data and contains around 100 samples along with Categories 1, Categories 2, technical information and other features such as: - Followers - Categories 1 - and more.
- Analyze Categories 2 in relation to Followers
- Study the influence of Categories 1 on Categories 2
- More datasets
If you use this dataset in your research, please credit Social Media Data
--- Original source retains full ownership of the source dataset ---
https://brightdata.com/licensehttps://brightdata.com/license
Use our Instagram Hashtags dataset (public data) to extract insights by filtering hashtags, follower counts, account type, or engagement metrics. Depending on your needs, you can purchase the full dataset or a customized subset. Popular use cases include trend analysis, brand monitoring, hashtag optimization, and influencer marketing. The dataset includes key data points such as hashtags, engagement scores, associated posts, locations, account types (business/non-business), and much more.
https://cdla.io/sharing-1-0/https://cdla.io/sharing-1-0/
Context: This dataset offers insights into the usage patterns of social media apps for 1,000 users across seven popular platforms: Facebook, Instagram, Twitter, Snapchat, TikTok, LinkedIn, and Pinterest. It tracks various metrics such as daily time spent on the app, number of posts made, likes received, and new followers gained.
Dataset Features:
User_ID: Unique identifier for each user. App: The social media platform being used. Daily_Minutes_Spent: Total time a user spends on the app each day, ranging from 5 to 500 minutes. Posts_Per_Day: Number of posts a user creates per day, ranging from 0 to 20. Likes_Per_Day: Total number of likes a user receives on their posts each day, ranging from 0 to 200. Follows_Per_Day: The number of new followers a user gains daily, ranging from 0 to 50. Context & Use Cases: This dataset could be particularly useful for social media analysts, digital marketers, or researchers interested in understanding user engagement trends across different platforms. It provides insights into how much time users spend, how actively they post, and the level of engagement they receive (in terms of likes and followers).
Conclusion & Outcome: Analyzing this dataset could yield several outcomes:
Engagement Patterns: Identifying which platforms have higher engagement in terms of time spent or likes received. Active Users: Determining which users are the most active across various platforms based on the number of posts and followers gained. User Retention: Studying the correlation between time spent and follower growth, providing insight into user retention strategies for different platforms. Overall, the dataset allows for exploration of social media usage trends and helps drive decision-making for marketing strategies, content creation, and platform engagement.
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License information was derived automatically
This dataset supports research on how engagement with social media (Instagram and TikTok) was related to problematic social media use (PSMU) and mental well-being. There are three different files. The SPSS and Excel spreadsheet files include the same dataset but in a different format. The SPSS output presents the data analysis in regard to the difference between Instagram and TikTok users.
As of April 2024, around 16.5 percent of global active Instagram users were men between the ages of 18 and 24 years. More than half of the global Instagram population worldwide was aged 34 years or younger.
Teens and social media
As one of the biggest social networks worldwide, Instagram is especially popular with teenagers. As of fall 2020, the photo-sharing app ranked third in terms of preferred social network among teenagers in the United States, second to Snapchat and TikTok. Instagram was one of the most influential advertising channels among female Gen Z users when making purchasing decisions. Teens report feeling more confident, popular, and better about themselves when using social media, and less lonely, depressed and anxious.
Social media can have negative effects on teens, which is also much more pronounced on those with low emotional well-being. It was found that 35 percent of teenagers with low social-emotional well-being reported to have experienced cyber bullying when using social media, while in comparison only five percent of teenagers with high social-emotional well-being stated the same. As such, social media can have a big impact on already fragile states of mind.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
These two data sets are gathered from Instagram users who were chosen randomly.
The Main data set encompasses data for 1K users including 500 men and 500 women. The Test data set encompasses data for 100 users including 50 men and 50 women.
Data gathered for each user includes :
1- number of posts
2- number of followers
3- number of followings
4- number of likes for the tenth previous post
5- number of likes for the eleventh previous post
6- number of likes for the twelfth previous post
7- number of self-presenting posts from nine previous posts
8- gender
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Analysis of ‘Instagram fake spammer genuine accounts’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/free4ever1/instagram-fake-spammer-genuine-accounts on 28 January 2022.
--- Dataset description provided by original source is as follows ---
[comment]: <> (There's a story behind every dataset and here's your opportunity to share yours.) Fakes and spammers are a major problem on all social media platforms, including Instagram. This is the subject of my final-year project in which I set out to find ways of detecting them using machine learning. In this dataset fake and spammer are interchangeable terms.
[comment]: <> (What's inside is more than just rows and columns. Make it easy for others to get started by describing how you acquired the data and what time period it represents, too.) I have personally identified the spammer/fake accounts included in this dataset after carefully examining each instance and as such the dataset has high level of accuracy though there might be a couple of misidentified accounts in the spammers list as well. The dataset has been collected using a crawler from 15-19, March 2019.
[comment]: <> (### Acknowledgements)
[comment]: <> (We wouldn't be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research.)
[comment]: <> (Your data will be in front of the world's largest data science community. What questions do you want to see answered?) This dataset could be further improved in quantity and quality measures, but how much accuracy can it achieve? Possible ways of using the models to tackle the problem?
--- Original source retains full ownership of the source dataset ---
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset investigates the Instagram engagement metrics (likes and comments) of the U.S. and British Armies to understand their strengths and weaknesses in their marketing. For the quantitative data collection, a random number generator was used to compile a 20% data sample (73 posts) from a total of 365 posts from each account. For instance, a number 1 in the random generator corresponded to the most recent post from the start date of data collection (May 23rd, 2024). By picking from 365 posts, the data collection was meant to represent roughly a year of Instagram content, assuming their Instagram accounts posted every day. This method ensured an unbiased representation of which content was included in the 20% data sample.However, the U.S Army posted almost once a day while the British Army posted only a few days a week. In the end, data was collected across 365 U.S. Army posts from May 23rd, 2024, to October 28th, 2023. For the British Army’s Instagram, the data collection span from May 23rd, 2024, to November 25th, 2021. By engaging with recent posts, the purpose was to understand how effectively these Armies responded to their recruitment crisis (which started in 2022).For the data collection, variables for each post included the following:Date of postNumber of likesPercentage of likes by follower populationNumber of commentsPercentage of comments by follower populationTo understand which Instagram posts were successful, the content with the highest number of likes and comments were defined as the most engaged. But, to accurately compare the British Army’s Instagram engagement to the U.S., the number of likes/comments was divided by the number of their followers. As of May 23, 2024, the U.S. Army had 2.9 million followers on Instagram whereas the British Army had 594,000 followers. While social media users outside of the Armies’ followers engaged with the posts, these ratios provided a basis to fairly compare their engagement metrics.
Instagram’s most popular post
As of April 2024, the most popular post on Instagram was Lionel Messi and his teammates after winning the 2022 FIFA World Cup with Argentina, posted by the account @leomessi. Messi's post, which racked up over 61 million likes within a day, knocked off the reigning post, which was 'Photo of an Egg'. Originally posted in January 2021, 'Photo of an Egg' surpassed the world’s most popular Instagram post at that time, which was a photo by Kylie Jenner’s daughter totaling 18 million likes.
After several cryptic posts published by the account, World Record Egg revealed itself to be a part of a mental health campaign aimed at the pressures of social media use.
Instagram’s most popular accounts
As of April 2024, the official Instagram account @instagram had the most followers of any account on the platform, with 672 million followers. Portuguese footballer Cristiano Ronaldo (@cristiano) was the most followed individual with 628 million followers, while Selena Gomez (@selenagomez) was the most followed woman on the platform with 429 million. Additionally, Inter Miami CF striker Lionel Messi (@leomessi) had a total of 502 million. Celebrities such as The Rock, Kylie Jenner, and Ariana Grande all had over 380 million followers each.
Instagram influencers
In the United States, the leading content category of Instagram influencers was lifestyle, with 15.25 percent of influencers creating lifestyle content in 2021. Music ranked in second place with 10.96 percent, followed by family with 8.24 percent. Having a large audience can be very lucrative: Instagram influencers in the United States, Canada and the United Kingdom with over 90,000 followers made around 1,221 US dollars per post.
Instagram around the globe
Instagram’s worldwide popularity continues to grow, and India is the leading country in terms of number of users, with over 362.9 million users as of January 2024. The United States had 169.65 million Instagram users and Brazil had 134.6 million users. The social media platform was also very popular in Indonesia and Turkey, with 100.9 and 57.1, respectively. As of January 2024, Instagram was the fourth most popular social network in the world, behind Facebook, YouTube and WhatsApp.
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License information was derived automatically
There were 392 465 000 Instagram users in India in June 2024, which accounted for 26.7% of its entire population. The majority of them were men - 66.9%. People aged 18 to 24 were the largest user group (172 600 000). The highest difference between men and women occurs within people aged 25 to 34, where men lead by 99 300 000.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset includes Instagram user characteristics of those Olympic athletes who won gold medals in the individual events of Rio2016. The name of all these gold medalists of individual events are in the dataset (226 athletes), however only 144 athletes (83 men and 61 women) had a publicly available Instagram account in all of the observations during the 4 months period of data gathering. The first round of data gathering (first observation, i.e. OlympicAthletesData_1) took place 9-Aug-2019 to 12-Aug-2019, the second round of data gathering (second observation, i.e. OlympicAthletesData_2) took place 9-Sep-2019 to 12-Sep-2019, the third round of data gathering (third observation, i.e. OlympicAthletesData_3) took place 9-Oct-2019 to 12-Oct-2019, the fourth round of data gathering (fourth observation, i.e. OlympicAthletesData_4) took place 9-Nov-2019 to 12-Nov-2019. The data gathered for each user (in each observation) consists of:
1- Name of the individual event
2- Country
3- Name
4- Gender
5- Instagram ID
6- Number of Posts
7- Number of followers
8- Number of followings
9- Maximum Number of likes (in the last 10 photo posts)
10- Number of comments for the post with Maximum Number of likes (in the last 10 photo posts)
11- Number of self-presenting posts in the last 10 photo posts (those posts in which the athlete is present)
12- Number of pure self-presenting posts in the last 10 photo posts (those posts in which the athlete is the only person who is present)
13- Age
14- Date of data crawling
As of January 2024, Instagram was slightly more popular with men than women, with men accounting for 50.6 percent of the platform’s global users. Additionally, the social media app was most popular amongst younger audiences, with almost 32 percent of users aged between 18 and 24 years.
Instagram’s Global Audience
As of January 2024, Instagram was the fourth most popular social media platform globally, reaching two billion monthly active users (MAU). This number is projected to keep growing with no signs of slowing down, which is not a surprise as the global online social penetration rate across all regions is constantly increasing.
As of January 2024, the country with the largest Instagram audience was India with 362.9 million users, followed by the United States with 169.7 million users.
Who is winning over the generations?
Even though Instagram’s audience is almost twice the size of TikTok’s on a global scale, TikTok has shown itself to be a fierce competitor, particularly amongst younger audiences. TikTok was the most downloaded mobile app globally in 2022, generating 672 million downloads. As of 2022, Generation Z in the United States spent more time on TikTok than on Instagram monthly.
https://brightdata.com/licensehttps://brightdata.com/license
Access detailed insights with our Instagram datasets, featuring follower counts, verified status, account types, and engagement scores. Explore post information including URLs, descriptions, hashtags, comments, likes, media, posting dates, locations, and reel URLs. Perfect for understanding user engagement and content trends to drive informed decisions and optimize your social media strategies. Over 750M records available Price starts at $250/100K records Data formats are available in JSON, NDJSON, CSV, XLSX and Parquet. 100% ethical and compliant data collection Included datapoints:
Account Fbid Id Followers Posts Count Is Business Account Is Professional Account Is Verified Avg Engagement External Url Biography Business Category Name Category Name Post Hashtags Following Posts Profile Image Link Profile URL Profile Name Highlights Count Highlights Full Name Is Private Bio Hashtags URL Is Joined Recently And much more