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.

Use our Instagram dataset (public data) to extract business and non-business information from complete public profiles and filter by hashtags, followers, account type, or engagement score. Depending on your needs, you may purchase the entire dataset or a customized subset. Popular use cases include sentiment analysis, brand monitoring, influencer marketing, and more. The dataset includes all major data points: # of followers, verified status, account type (business / non-business), links, posts, comments, location, engagement score, hashtags, and much more.

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.

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.

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.

Automatically describing images using natural sentences is an essential task to visually impaired people's inclusion on the Internet. Although there are many datasets in the literature, most of them contain only English captions, whereas datasets with captions described in other languages are scarce.

PraCegoVer arose on the Internet, stimulating users from social media to publish images, tag #PraCegoVer and add a short description of their content. Inspired by this movement, we have proposed the #PraCegoVer, a multi-modal dataset with Portuguese captions based on posts from Instagram. It is the first large dataset for image captioning in Portuguese with freely annotated images.

PraCegoVer has 533,523 pairs with images and captions described in Portuguese collected from more than 14 thousand different profiles. Also, the average caption length in #PraCegoVer is 39.3 words and the standard deviation is 29.7.

Dataset Structure

PraCegoVer dataset is composed of the main file dataset.json and a collection of compressed files named images.tar.gz.partX

containing the images. The file dataset.json comprehends a list of json objects with the attributes:

user: anonymized user that made the post;

filename: image file name;

raw_caption: raw caption;

caption: clean caption;

date: post date.

Each instance in dataset.json is associated with exactly one image in the images directory whose filename is pointed by the attribute filename. Also, we provide a sample with five instances, so the users can download the sample to get an overview of the dataset before downloading it completely.

Download Instructions

If you just want to have an overview of the dataset structure, you can download sample.tar.gz. But, if you want to use the dataset, or any of its subsets (63k and 173k), you must download all the files and run the following commands to uncompress and join the files:

cat images.tar.gz.part* > images.tar.gz tar -xzvf images.tar.gz

Alternatively, you can download the entire dataset from the terminal using the python script download_dataset.py available in PraCegoVer repository. In this case, first, you have to download the script and create an access token here. Then, you can run the following command to download and uncompress the image files:

python download_dataset.py --access_token=

This statistic shows a ranking of the estimated number of Instagram users in 2020 in Africa, differentiated by country. The user numbers have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period and count multiple accounts by persons only once.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in more than 150 countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).

How much time do people spend on social media? As of 2024, the average daily social media usage of internet users worldwide amounted to 143 minutes per day, down from 151 minutes in the previous year. Currently, the country with the most time spent on social media per day is Brazil, with online users spending an average of three hours and 49 minutes on social media each day. In comparison, the daily time spent with social media in the U.S. was just two hours and 16 minutes. Global social media usageCurrently, the global social network penetration rate is 62.3 percent. Northern Europe had an 81.7 percent social media penetration rate, topping the ranking of global social media usage by region. Eastern and Middle Africa closed the ranking with 10.1 and 9.6 percent usage reach, respectively. People access social media for a variety of reasons. Users like to find funny or entertaining content and enjoy sharing photos and videos with friends, but mainly use social media to stay in touch with current events friends. Global impact of social mediaSocial media has a wide-reaching and significant impact on not only online activities but also offline behavior and life in general. During a global online user survey in February 2019, a significant share of respondents stated that social media had increased their access to information, ease of communication, and freedom of expression. On the flip side, respondents also felt that social media had worsened their personal privacy, increased a polarization in politics and heightened everyday distractions.