User_ID | IP_Address | Latitude | Longitude | Country | City | Last_Time_Logged_In |
---|---|---|---|---|---|---|
xxxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxxxx | xxx | xxxxxxxxxxxxx | xxxxxxxxxxxxxxxxxxx |
xxxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxx | xx | xxxxxx | xxxxxxxxxxxxxxxxxxx |
xxxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxx | xxxxx | xxxxx | xxxxxxxxxxxxxxxxxxx |
xxxxxx | xxxxxxxxxx | xxxxx | xxxxxx | xxxxxxx | xxxxxx | xxxxxxxxxxxxxxxxxxx |
xxxxxx | xxxxxxxxxx | xxxxxxxx | xxxxxxxx | xxxxxx | xxxxxxxxx | xxxxxxxxxxxxxxxxxxx |
xxxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxx | xxx | xxxxxxxx | xxxxxxxxxxxxxxxxxxx |
xxxxxx | xxxxxxxxxx | xxxxxx | xxxxxxx | xxxxx | xxxxxx | xxxxxxxxxxxxxxxxxxx |
xxxxxx | xxxxxxxxxx | xxxxxxx | xxxxxx | xxxxxx | xxxxx | xxxxxxxxxxxxxxxxxxx |
xxxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxx | xxxxxx | xxxxxx | xxxxxxxxxxxxxxxxxxx |
xxxxxx | xxxxxxxxxx | xxxxxxxx | xxxxxxxx | xxxxxxxxx | xxxxxxxxxxxx | xxxxxxxxxxxxxxxxxxx |
Description
This dataset offers a comprehensive collection of Telegram users' geolocation data, including IP addresses, with full user consent, covering 50,000 records. This data is specifically tailored for use in AI, ML, DL, and LLM models, as well as applications requiring Geographic Data and Social Media Data. The dataset provides critical geospatial information, making it a valuable resource for developing location-based services, targeted marketing strategies, and more. What Makes This Data Unique? This dataset is unique due to its focus on geolocation data tied to Telegram users, a platform with a global user base. It includes IP to Geolocation Data, offering precise geospatial insights that are essential for accurate geographic analysis. The inclusion of user consent ensures that the data is ethically sourced and legally compliant. The dataset's broad coverage across various regions makes it particularly valuable for AI and machine learning models that require diverse, real-world data inputs. Data Sourcing: The data is collected through a network of in-app tasks across different mini-apps within Telegram. Users participate in these tasks voluntarily, providing explicit consent to share their geolocation and IP information. The data is collected in real-time, capturing accurate geospatial details as users interact with various Telegram mini-apps. This method of data collection ensures that the information is both relevant and up-to-date, making it highly valuable for applications that require current location data. Primary Use-Cases: This dataset is highly versatile and can be applied across multiple categories, including: IP to Geolocation Data: The dataset provides precise mapping of IP addresses to geographical locations, making it ideal for applications that require accurate geolocation services. Geographic Data: The geospatial information contained in the dataset supports a wide range of geographic analysis, including regional behavior studies and location-based service optimization. Social Media Data: The dataset's integration with Telegram users' activities provides insights into social media behaviors across different regions, enhancing social media analytics and targeted marketing. Large Language Model (LLM) Data: The geolocation data can be used to train LLMs to better understand and generate content that is contextually relevant to specific regions. Deep Learning (DL) Data: The dataset is ideal for training deep learning models that require accurate and diverse geospatial inputs, such as those used in autonomous systems and advanced geographic analytics. Integration with Broader Data Offering: This geolocation dataset is a valuable addition to the broader data offerings from FileMarket. It can be combined with other datasets, such as web browsing behavior or social media activity data, to create comprehensive AI models that provide deep insights into user behaviors across different contexts. Whether used independently or as part of a larger data strategy, this dataset offers unique value for developers and data scientists focused on enhancing their models with precise, consented geospatial data.
Country Coverage
(249 countries)Data Categories
- Social Media Data
- Geographic Data
- IP To Geolocation Data
- Deep Learning (DL) Data
- Large Language Model (LLM) Data
Pricing
Volumes
- records
- 50K
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