BotsArchive API

Overview

BotsArchive offers an API designed for the systematic study and detection of social media bots. Launched in 2024, the platform provides access to a comprehensive dataset of bot activity, enabling users to analyze patterns, identify coordinated behavior, and track the dissemination of content by automated accounts. The API is particularly suited for academic research, journalistic investigations into online influence, social media analysis, and efforts to monitor and combat misinformation campaigns.

The core products accessible via the BotsArchive API include extensive social media bot data, advanced bot detection models, and historical records of bot activity. This allows developers and researchers to query for specific bot accounts, analyze their posting frequencies, network connections, and the types of content they amplify. For instance, a researcher could use the API to identify bot networks active during a specific political event, examining their engagement with particular hashtags or news articles. The data can be filtered by platform, time range, and bot confidence scores, providing granular control over the information retrieved.

BotsArchive is built to support data-intensive applications. Its API can be integrated into larger analytical pipelines, allowing organizations to enrich their existing social media monitoring tools or build custom dashboards for real-time threat intelligence. The developer experience is characterized by clear documentation and a straightforward authentication process using an API key, as detailed in the BotsArchive API documentation. This design helps users quickly implement queries and integrate the data into their projects, whether they are performing large-scale data pulls for academic studies or focused investigations into specific online phenomena. The API's data model is structured for efficient access to bot activity and associated metadata, facilitating queries that might involve millions of data points.

The platform's utility extends to identifying emerging bot trends and understanding their evolution over time. By providing historical data, BotsArchive enables longitudinal studies of bot behavior, which is crucial for understanding how automated influence operations adapt and change strategies. This deep historical context differentiates it from tools that only offer real-time detection, allowing for more robust and evidence-based conclusions on the long-term impact of bot activity on public discourse.

Key features

• Social Media Bot Data: Access a curated dataset of identified bot accounts across various social media platforms, including their profiles, activity logs, and associated metadata.
• Bot Detection Models: Utilize pre-trained machine learning models to identify potential bot accounts based on behavioral patterns, linguistic analysis, and network characteristics.
• Historical Bot Activity: Retrieve historical data on bot operations, allowing for analysis of trends, campaign timelines, and long-term behavioral shifts.
• Query Filtering and Granularity: Filter data by platform, date range, bot confidence scores, and specific keywords or hashtags to focus research.
• GDPR Compliance: Adheres to General Data Protection Regulation (GDPR) standards, ensuring data privacy and ethical handling of information.
• Developer-Friendly API: Features clear documentation, standard API key authentication, and a straightforward data model for ease of integration.

Pricing

BotsArchive offers a tiered pricing structure, including a free tier for initial exploration and various paid plans for increased usage and features. As of May 2026, the pricing is structured as follows:

For detailed and up-to-date pricing information, including annual discounts and specific feature breakdowns for each tier, please refer to the official BotsArchive pricing page.

Common integrations

BotsArchive's API can be integrated with various tools and platforms commonly used in data analysis, research, and social media monitoring. While there are no pre-built, named integrations listed, the API's standard RESTful design allows for custom integration with:

• Data Visualization Tools: Connect with platforms like Tableau, Power BI, or custom D3.js applications to visualize bot network structures and activity timelines.
• Programming Languages: Utilize client libraries in Python, R, Java, or JavaScript to programmatically fetch and process bot data within analytical scripts.
• Database Systems: Store and manage retrieved bot data in relational databases (e.g., PostgreSQL, MySQL) or NoSQL databases (e.g., MongoDB) for long-term storage and complex querying.
• Cloud Computing Platforms: Deploy applications leveraging the BotsArchive API on AWS, Google Cloud, or Azure, integrating with serverless functions or containerized services.
• Social Media Monitoring Platforms: Enhance existing monitoring solutions by incorporating BotsArchive's bot detection capabilities to filter out automated noise or identify malicious campaigns.
• Incident Response Systems: Integrate with security operations centers (SOC) tools or incident management platforms to flag and respond to coordinated bot attacks or misinformation propagation.

Alternatives

For users seeking alternatives to BotsArchive for social media bot detection and analysis, several other platforms offer similar or complementary functionalities:

• Botometer: A widely recognized tool developed by Indiana University, Botometer provides a score indicating the likelihood that a Twitter account is a bot.
• Truth Goggles: While not exclusively a bot detector, Truth Goggles focuses on fact-checking and identifying misinformation, which often involves analyzing the spread patterns that bots contribute to.
• Hoaxy: Another tool from Indiana University, Hoaxy visualizes the spread of claims and fact-checks on social media, helping to track the propagation of potentially false information, often amplified by bots.

Getting started

To begin using the BotsArchive API, you will first need to obtain an API key from your BotsArchive account. Once you have your key, you can make authenticated requests to the API endpoints. The following Python example demonstrates how to fetch a list of recent bot activity:

import requests
import json

API_KEY = "YOUR_BOTSARCHIVE_API_KEY"
BASE_URL = "https://api.botsarchive.com/v1"

headers = {
    "Authorization": f"Bearer {API_KEY}",
    "Content-Type": "application/json"
}

# Example: Get recent bot activity
endpoint = f"{BASE_URL}/bot-activity"
params = {
    "limit": 10, # Retrieve 10 most recent activities
    "platform": "twitter" # Filter by Twitter activity
}

try:
    response = requests.get(endpoint, headers=headers, params=params)
    response.raise_for_status() # Raise an exception for HTTP errors
    data = response.json()
    print(json.dumps(data, indent=2))

except requests.exceptions.RequestException as e:
    print(f"API request failed: {e}")
    if response is not None:
        print(f"Status Code: {response.status_code}")
        print(f"Response Body: {response.text}")

This Python code snippet illustrates a basic GET request to the /bot-activity endpoint. It includes setting the authorization header with your API key and specifying query parameters such as limit and platform to refine the results. The response is then printed in a human-readable JSON format. For more complex queries, such as filtering by specific bot IDs, time ranges, or integrating bot detection models, refer to the comprehensive BotsArchive developer documentation.