The Spam Checker in Text API is a powerful tool designed for text analysis. It detects and filters spam content within textual data, ensuring secure and spam-free communication environments for various applications.

The API uses advanced algorithms and machine learning techniques to analyze text, identifying patterns, keywords, and other indicators of spam. It assesses sender reputation and contextual factors, enabling accurate spam detection.

This API is valuable for applications requiring content moderation, such as social media platforms, messaging apps, email services, online forums, and customer support systems. It ensures user-generated content aligns with community guidelines and standards.

Yes, the Spam Checker in Text API offers real-time analysis, allowing businesses to respond promptly to emerging spam threats. Its efficiency and accuracy contribute to improved operational workflows and user experiences.

The API is language-agnostic and can analyze text in multiple languages. It does not restrict its functionality based on language or region, making it suitable for global applications.

The API returns a JSON object containing the analyzed text and its corresponding spam score. The spam score indicates the likelihood of the text being spam, allowing users to assess the content's legitimacy.

The key fields in the response data include "text," which contains the original input text, and "spam_score," which quantifies the spam likelihood on a scale, helping users determine the content's safety.

The response data is structured in JSON format, making it easy to parse. It typically includes fields like "text" for the input and "spam_score" for the analysis result, allowing for straightforward integration into applications.

The primary parameter for the Spam Checker in Text API is the "text" parameter, where users input the text they want to analyze. This allows for flexible and targeted spam detection based on specific content.

Users can utilize the returned data by interpreting the "spam_score" to filter or flag messages in their applications. For instance, a high spam score may trigger moderation actions, enhancing user safety and content quality.

The endpoint provides information on the analyzed text and its spam score. This includes insights into potential spam characteristics, enabling users to understand the nature of flagged content.

Data accuracy is maintained through advanced algorithms and machine learning techniques that continuously learn from new data. Regular updates and training improve the API's ability to identify spam effectively.

Typical use cases include moderating social media comments, filtering spam emails, enhancing chatbot responses, and ensuring the integrity of product reviews on e-commerce platforms, all aimed at improving user experience.

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To give you the opportunity to experience our APIs without any commitment, we offer a 7-day free trial that allows you to make up to 50 API calls at no cost. This trial can be used only once, so we recommend applying it to the API that interests you the most. While most of our APIs offer a free trial, some may not. The trial concludes after 7 days or once you've made 50 requests, whichever occurs first. If you reach the 50 request limit during the trial, you will need to "Start Your Paid Plan" to continue making requests. You can find the "Start Your Paid Plan" button in your profile under Subscription -> Choose the API you are subscribed to -> Pricing tab. Alternatively, if you don't cancel your subscription before the 7th day, your free trial will end, and your plan will automatically be billed, granting you access to all the API calls specified in your plan. Please keep this in mind to avoid unwanted charges.

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When you subscribe to an API free trial, you can make up to 50 API calls. If you wish to make additional API calls beyond this limit, the API will prompt you to perform an "Start Your Paid Plan." You can find the "Start Your Paid Plan" button in your profile under Subscription -> Choose the API you are subscribed to -> Pricing tab.

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