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Comprehensive database of Instagram creators with detailed analytics, engagement metrics, and content promotion tracking

IMGT/GENE-DB is the comprehensive IMGT genome database for immunoglobulin (IG) and T cell receptor (TR) genes from human and mouse, and, in development, from other vertebrates. IMGT/GENE-DB is the international reference for the IG and TR gene nomenclature and works in close collaboration with the HUGO Nomenclature Committee, Mouse Genome Database and genome committees for other species. IMGT/GENE-DB allows a search of IG and TR genes by locus, group and subgroup, which are CLASSIFICATION concepts of IMGT-ONTOLOGY. Short cuts allow the retrieval gene information by gene name or clone name. Direct links with configurable URL give access to information usable by humans or programs. An IMGT/GENE-DB entry displays accurate gene data related to genome (gene localization), allelic polymorphisms (number of alleles, IMGT reference sequences, functionality, etc.) gene expression (known cDNAs), proteins and structures (Protein displays, IMGT Colliers de Perles). It provides internal links to the IMGT sequence databases and to the IMGT Repertoire Web resources, and external links to genome and generalist sequence databases. IMGT/GENE-DB manages the IMGT reference directory used by the IMGT tools for IG and TR gene and allele comparison and assignment, and by the IMGT databases for gene data annotation.

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.

IMGT/LIGM-DB is a comprehensive database of immunoglobulin (IG) and T cell receptor (TR) nucleotide sequences from human and other vertebrate species (270). IMGT/LIGM-DB includes all germline (non-rearranged) and rearranged IG and TR genomic DNA (gDNA) and complementary DNA (cDNA) sequences published in generalist databases. IMGT/LIGM-DB allows searches from the Web interface according to biological and immunogenetic criteria through five distinct modules depending on the user interest. Users can search the catalogue by accession number, mnemonic, definition, creation date, length, or annotation level. They also have the option to search through taxonomic classification, keywords, and annotated labels. For a given entry, nine types of display are available including the IMGT flat file, the translation of the coding regions and the analysis by the IMGT/V-QUEST tool (see parent org. below). IMGT/LIGM-DB distributes expertly annotated sequences. The annotations hugely enhance the quality and the accuracy of the distributed detailed information. They include the sequence identification, the gene and allele classification, the constitutive and specific motif description, the codon and amino acid numbering, and the sequence obtaining information, according to the main concepts of IMGT-ONTOLOGY. They represent the main source of IG and TR gene and allele knowledge stored in IMGT/GENE-DB and in the IMGT reference directory.

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.

Next generation sequencing (NGS) of immunoglobulin (Ig) repertoires (Rep-seq) enables examination of the adaptive immune system at an unprecedented level. Applications include studies of expressed repertoires, gene usage, somatic hypermutation levels, Ig lineage tracing and identification of genetic variation within the Ig loci through inference methods. All these applications require starting libraries that allow the generation of sequence data with low error rate and optimal representation of the expressed repertoire. Here, we provide detailed protocols for the production of libraries suitable for human Ig germline gene inference and Ig repertoire studies. Various parameters used in the process were tested in order to demonstrate factors that are critical to obtain high quality libraries. We demonstrate an improved 5′RACE technique that reduces the length constraints of Illumina MiSeq based Rep-seq analysis but allows for the acquisition of sequences upstream of Ig V genes, useful for primer design. We then describe a 5′ multiplex method for library preparation, which yields full length V(D)J sequences suitable for genotype identification and novel gene inference. We provide comprehensive sets of primers targeting IGHV, IGKV, and IGLV genes. Using the optimized protocol, we produced IgM, IgG, IgK, and IgL libraries and analyzed them using the germline inference tool IgDiscover to identify expressed germline V alleles. This process additionally uncovered three IGHV, one IGKV, and six IGLV novel alleles in a single individual, which are absent from the IMGT reference database, highlighting the need for further study of Ig genetic variation. The library generation protocols presented here enable a robust means of analyzing expressed Ig repertoires, identifying novel alleles and producing individualized germline gene databases from humans.

United States Agri Productivity: Input: IG: Energy data was reported at 0.719 2005=1 in 2015. This records an increase from the previous number of 0.632 2005=1 for 2014. United States Agri Productivity: Input: IG: Energy data is updated yearly, averaging 1.020 2005=1 from Dec 1948 (Median) to 2015, with 68 observations. The data reached an all-time high of 1.421 2005=1 in 1978 and a record low of 0.575 2005=1 in 2012. United States Agri Productivity: Input: IG: Energy data remains active status in CEIC and is reported by Economic Research Service. The data is categorized under Global Database’s United States – Table US.B067: Agriculture Productivity.

The RDA Data Discovery Paradigms IG (https://www.rd-alliance.org/groups/data-discovery-paradigms-ig) aims to provide a forum where representatives from across the spectrum of stakeholders and roles pertaining to data search can discuss issues related to improving data discovery. The goal is to identify concrete deliverables such as a registry of data search engines, common test datasets, usage metrics, and a collection of data search use cases and competency questions.

In order to identify the key requirements evident across data discovery use-cases from various scientific fields and domains, the Use Cases Task Force (https://www.rd-alliance.org/group/data-discovery-paradigms-ig/wiki/use-cases-prototyping-tools-and-test-collections-task-force) was initiated. Direct outcome of this task force is this collection of use cases outlining what users might wish to search for data and what supports they would expect a data repository should provide.

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.

InSTA: Towards Internet-Scale Training For Agents

Brandon Trabucco (1) Gunnar Sigurdsson (2) Robinson Piramuthu (2) Ruslan Salakhutdinov (1) (1) Carnegie Mellon University, Machine Learning Department (2) Amazon This is a revised dataset, from the authors of the paper Towards Internet-Scale Training For Agents, contains 150k web navigation tasks generated to facilitate Internet-scale training of agents without relying heavily on human annotations. The dataset is split… See the full description on the dataset page: https://huggingface.co/datasets/data-for-agents/insta-150k-v2.

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.

1. Go to www.instagram.com and log in
2. Click on your profile picture, go to Settings and Privacy and Security
3. Scroll to Data download and click Request download
4. Enter your email adress and click Next
5. Enter your password and click Request download

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.

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.

3282 Global import shipment records of Normal Human Immunoglobulin with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

The Top Instagram Accounts Dataset is a collection of 200 rows of data that provides valuable insights into the most popular Instagram accounts across different categories. The dataset contains several columns that provide comprehensive information on each account's performance, engagement rate, and audience size.

1. The "rank": column lists the accounts in order of their popularity on Instagram, starting from the most followed account.

2. The "name": column displays the Instagram handle of the account, which can be used to locate and follow the account on Instagram.

3. The "channel_info": column provides a brief description of the account, such as the type of content it features or the products and services it offers.

4. The "Category": column categorizes the account based on its primary theme or subject matter, such as fashion, sports, entertainment, or food.

5. The "posts": column displays the total number of posts on the account. This column helps to understand the account's level of activity and the amount of content it has produced over time.

6. The "followers": column indicates the number of people who follow the account on Instagram.

7. The "avg likes": column displays the average number of likes that the account's posts receive per post.

8. The "eng rate": column calculates the account's engagement rate by dividing the total number of likes and comments received by the total number of followers, expressed as a percentage.

How you can use this Dataset?

The Top Instagram Accounts Dataset can be used in a variety of ways to gain insights into the performance and engagement levels of popular Instagram accounts. Here are a few examples of what you can do with this dataset:

1. Conduct category analysis: The dataset provides information on the category of each Instagram account. You can use this information to conduct a category analysis and identify the most popular categories on Instagram.

2. Identify top influencers: The dataset ranks Instagram accounts based on their follower count. You can use this information to identify the top influencers in different categories and use them for influencer marketing campaigns.

3. Analyze engagement levels: The dataset includes columns such as "avg likes" and "eng rate" that provide insights into the engagement levels of Instagram accounts. You can use this information to understand what type of content resonates with Instagram users and create more engaging content for your own account.

This is a dataset of 1968 instagram photo posts totalling to 5,426 images.

There are 1968 folder each containing one or more image corresponding to the image, the post's metadata in a comprossed json file and the post's caption in a txt file.

Panama Imports: CIF: Intermediate Goods (IG) data was reported at 3,210,690.626 PAB th in 2017. This records an increase from the previous number of 2,964,312.732 PAB th for 2016. Panama Imports: CIF: Intermediate Goods (IG) data is updated yearly, averaging 2,360,055.439 PAB th from Dec 2000 (Median) to 2017, with 18 observations. The data reached an all-time high of 3,533,896.534 PAB th in 2014 and a record low of 1,044,237.000 PAB th in 2003. Panama Imports: CIF: Intermediate Goods (IG) data remains active status in CEIC and is reported by National Institute of Statistics and Census. The data is categorized under Global Database’s Panama – Table PA.JA002: Imports: By Stage of Processing: Annual.

The accurate germline gene assignment and assessment of somatic hypermutation in antibodies induced by immunization or infection are important in immunological studies. Here, we illustrate issues specific to the construction of comprehensive immunoglobulin (IG) germline gene reference databases for outbred animal species using rhesus macaques, a frequently used non-human primate model, as a model test case. We demonstrate that the genotypic variation found in macaque germline inference studies is reflected in similar levels of gene diversity in genomic assemblies. We show that the high frequency of IG heavy chain V (IGHV) region structural and gene copy number variation between subjects means that individual animals lack genes that are present in other animals. Therefore, gene databases compiled from a single or too few animals will inevitably result in inaccurate gene assignment and erroneous SHM level assessment for those genes it lacks. We demonstrate this by assigning a test macaque IgG library to the KIMDB, a database compiled of germline IGHV sequences from 27 rhesus macaques, and, alternatively, to the IMGT rhesus macaque database, based on IGHV genes inferred primarily from the genomic sequence of the rheMac10 reference assembly, supplemented with 10 genes from the Mmul_051212 assembly. We found that the use of a gene-restricted database led to overestimations of SHM by up to 5% due to misassignments. The principles described in the current study provide a model for the creation of comprehensive immunoglobulin reference databases from outbred species to ensure accurate gene assignment, lineage tracing and SHM calculations.

Explore the short-form video landscape on Instagram with this specialized dataset featuring Reels content. This collection includes millions of Reels posts from global creators, influencers, and brands, providing a focused view into one of Instagram’s fastest-growing content formats.

Key Features:

Reel-Specific Posts: Every entry in the dataset is confirmed to be an Instagram Reel, with associated metadata.

Content & Engagement Metrics: Includes video captions, hashtags, view counts, like counts, comment counts, share counts, and timestamp data.

Creator Information: Features public account data such as usernames, follower counts, bio snippets, and account category where available.

Trend Discovery & Analysis: Perfect for analyzing video content performance, audio trends, visual themes, and influencer strategies on Reels.

Ready for Analysis: Delivered in clean CSV format, API, or custom formats, optimized for direct use in analytics, dashboards, machine learning models, or campaign planning.

This dataset is ideal for marketers, social strategists, and researchers looking to understand what drives engagement in short-form video content across the Instagram ecosystem.

The dataset contains several shapefiles with information about Universidad glacier, which were derived from datasets not available to IG PAS. Said datasets were made available without charge to the PI of the "Changes of surface hydrology of a mountain glacier studied with very high resolution aerial and satellite images and machine learning " project for the purpose of realizing the goals of the project.