Introduction

Foursquare Statistics: Advancements in technology have revolutionised the world thanks to the invention of small portable devices that are kept in our pockets. Smartphones, tablets, and smartwatches are quickly doing away with traditional laptops and desktops. In addition to this, app developers are easing the burden of everyday tasks on people. For example, food is now being delivered to people at their doorsteps rather than going out for it. Everyone knows how efficient Google's search engine can be, and just as how one would type in ‘Chinese restaurant’ did find a lot of such recommendations in the vicinity.

In the same way, these applications avail the users of services especially helpful in tourists finding new interesting places to go, for example, Фoursquare. Foursquare is a company that specialises in location-based services, including local search, social networking, and discovery. The company was established in 2009 and has been dominating the geography of intelligence markets ever since. It offered its users a check-in system so that they could share their location and see what was nearby at the time. By 2024, Foursquare Statistics will still be able to utilize its data and provide benefits to marketers and other reproducers.

This article is designed to present the most important numerical and other business activities related to Foursquare's statistics business in 2024, including but not limited to the user statistics of the platform, its operations, and the monetary figures involved, as well as the ratios and dollar amounts that are sought to explain.

The Foursquare dataset consists of check-in data for different cities. One subset contains check-ins in NYC and Tokyo collected for about 10 month (from 12 April 2012 to 16 February 2013). It contains 227,428 check-ins in New York city and 573,703 check-ins in Tokyo. Each check-in is associated with its time stamp, its GPS coordinates and its semantic meaning (represented by fine-grained venue-categories). Another subset contains long-term (about 18 months from April 2012 to September 2013) global-scale check-in data collected from Foursquare. It contains 33,278,683 checkins by 266,909 users on 3,680,126 venues (in 415 cities in 77 countries). Those 415 cities are the most checked 415 cities by Foursquare users in the world, each of which contains at least 10K check-ins.

Foursquare data downloaded from https://sites.google.com/site/yangdingqi/home/foursquare-dataset This dataset includes long-term (about 22 months from Apr. 2012 to Jan. 2014) global-scale check-in data collected from Foursquare, and also two snapshots of user social networks before and after the check-in data collection period (see more details in our paper). The check-in dataset contains 22,809,624 checkins by 114,324 users on 3,820,891 venues. The social network data contains 363,704 (old) and 607,333 (new) friendships. Due to frequent requests, we also include the raw check-in dataset containing 90,048,627 checkins by 2,733,324 users on 11,180,160 venues.

Access FSQ OS Places

With Foursquare’s Open Source Places, you can access free data to accelerate geospatial innovation and insights. View the Places OS Data Schemas for a full list of available attributes.

  Prerequisites

In order to access Foursquare's Open Source Places data, it is recommended to use Spark. Here is how to load the Places data in Spark from Hugging Face.

For Spark 3, you can use the read_parquet helper function from the HF Spark documentation. It… See the full description on the dataset page: https://huggingface.co/datasets/foursquare/fsq-os-places.

Location-based online social network - Foursquare is a location-based online social network. The dataset contains a list of all of the user-to-user links.

This data set contains 2,153,471 users, 1,143,092 venues, 1,021,970 check-ins, 27,098,490 social connections, and 2,809,581 ratings that users assigned to venues; all extracted from the Foursquare application through the public API. All users information have been anonymized, i.e., users geolocations are also anonymized. Each user is represented by an id, and GeoSpatial location. The same for venues. The data are contained in five files, users.dat, venues.dat, checkins.dat, socialgraph.dat, and ratings.dat. More details about the contents and use of all these files follows. Content of Files * users.dat: consists of a set of users such that each user has a unique id and a geospatial location (latitude and longitude) that represents the user home town location. * venues.dat: consists of a set of venues (e.g., restaurants) such that each venue has a unique id and a geospatial location (lattude and longitude). * checkins.dat: marks the checkins (visits) of users at venues. Each check-in ha

Comprehensive dataset of 3,152 Foursquare churches in Brazil as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 11 Foursquare churches in State of Paraíba, Brazil as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 72 Foursquare churches in Colombia as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

1-Turkish comments for 128 venues in Foursquare Social Network Platform (binary and ternary classified) 2-Turkish adjectives and polarities 3-Turkish food and drink names 4- All comments without tagging 5-Venues, liked meals/foods

This dataset includes long-term (about 22 months from Apr. 2012 to Jan. 2014) global-scale check-in data collected from Foursquare, and also two snapshots of user social networks before and after the check-in data collection period (see more details in our paper). The check-in dataset contains 22,809,624 checkins by 114,324 users on 3,820,891 venues. The social network data contains 363,704 (old) and 607,333 (new) friendships. Due to frequent requests, we also include the raw check-in dataset containing 90,048,627 checkins by 2,733,324 users on 11,180,160 venues.Please cite our paper if you publish material based on this dataset:+ Dingqi Yang, Bingqing Qu, Jie Yang, Philippe Cudre-Mauroux, Revisiting User Mobility and Social Relationships in LBSNs: A Hypergraph Embedding Approach, In Proc. of The Web Conference (WWW'19). May. 2019, San Francisco, USA. + Dingqi Yang, Bingqing Qu, Jie Yang, Philippe Cudre-Mauroux, LBSN2Vec++: Heterogeneous Hypergraph Embedding for Location-Based Social Networks, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2020.

Places of Interest(POI) within the City of Detroit from Foursquare's Open Source Places dataset.With Foursquare’s Open Source Places, you can access free data to accelerate geospatial innovation and insights.https://docs.foursquare.com/data-products/docs/access-fsq-os-places02-06-2025

This dataset provides information about the number of properties, residents, and average property values for Foursquare Court cross streets in Shasta Lake, CA.

Comprehensive dataset of 6 Foursquare churches in Uttar Pradesh, India as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

This dataset provides information about the number of properties, residents, and average property values for Foursquare Drive cross streets in Conroe, TX.

This database was created and collected with the goal of observing patterns in urban mobility. To achieve this, the Twitter API was used to collect public check-ins made by users via Foursquare Swarm. Data description:

venueID: Foursquare venue identifier
userID: Swarm user identifier venueName: Name of the venue where the check-in was made
category: Category of the venue where the check-in was made
country: Country of the venue where the check-in was made city: City of the venue where the check-in was made timestamp: Time when the check-in was shared on Twitter latitude: Latitude of the venue where the check-in was made longitude: Longitude of the venue where the check-in was made

Comprehensive dataset of 171 Foursquare churches in India as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

This dataset provides information about the number of properties, residents, and average property values for Foursquare Road cross streets in Windsor, VA.

The zip file contains 3 files: - Facebook insights by place. For each place found in central Copenhagen by Facebook, we retrieved a list of the users that have “liked” the place and the ones that have mentioned the place, by country, in the past month. Facebook doesn’t allow you to search earlier than one month. - Foursquare venue statistics. For each place found in greater Copenhagen by Foursquare, we provide analytics data numbers - checkins, likes, ratings, etc. - Each user that visited each venue in Greater Copenhagen in Foursquare by their nationality.

Foursquare does rate-limiting after about 500 calls to their API, meaning that we couldn’t continue with the user visit data above 500 users - this was meant as example data, so that if they’re interested in that one they can get their own Foursquare account with more API calls available.

Datasættet er et dump fra 2017 fra Wonderful Copenhagen ifm. Open Tourism Days http://www.opentourismdays.dk/

The zip file contains 3 files: - Facebook insights by place. For each place found in central Copenhagen by Facebook, we retrieved a list of the users that have “liked” the place and the ones that have mentioned the place, by country, in the past month. Facebook doesn’t allow you to search earlier than one month. - Foursquare venue statistics. For each place found in greater Copenhagen by Foursquare, we provide analytics data numbers - checkins, likes, ratings, etc. - Each user that visited each venue in Greater Copenhagen in Foursquare by their nationality.

Foursquare does rate-limiting after about 500 calls to their API, meaning that we couldn’t continue with the user visit data above 500 users - this was meant as example data, so that if they’re interested in that one they can get their own Foursquare account with more API calls available.