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Spam labeling: the role of recipient reactions

With the rise of spam calls, our phones have become battlegrounds, where legitimate calls vie for our attention amidst a deluge of unwanted interruptions. Hiya understands the importance of a call’s reputation and its ability to ensure a seamless telecommunications experience for all users.

The four aspects of call reputation

To combat improper spam labeling, the four facets of a call must be taken into account:

1. The phone number
2. The call
3. The recipient
4. The caller


Each aspect provides specific information to algorithms developed to determine the call’s legitimacy. Each plays a role in evaluating the desirability of a call; while the caller's identity and the associated phone number provide initial information, the call itself—its content, context, and quality—provides further insights.

The importance of recipient reactions

Recipient reactions form a vital component of a call’s reputation assessment and application of a “spam likely” label. Verifiable recipient data provides crucial insights into the desirability of a call. Call blocking, reporting, and high abandon rates are valuable indicators of unwanted calls. These reactions are not merely subjective opinions but verifiable data points that contribute to a comprehensive assessment of call reputation.

The collective recipient reactions play a significant role in identifying and labeling spam calls. When multiple users block, report, or exhibit high abandon rates for a specific number or caller, it indicates a pattern of undesirability.

How data informs analytics engines

A multifaceted analytical approach is required to ascertain the legitimacy of calls. For example, enterprises can utilize a branded call solution, like Hiya Connect, to enhance the authenticity of their calls. This allows greater algorithms to evaluate calls against registered information, providing users with greater confidence in answering legitimate calls.

The application of a spam label

It is important to note that spam labels are not applied based on a single report or block. Instead, analytics engines employ a dynamic threshold that adapts to changes in scammer tactics, call activity factors, and recipient reactions. The threshold for labeling a call as spam evolves based on patterns and trends identified in the data.

This system ensures that spam labels are only applied when there is sufficient verifiable recipient data to indicate the call as unwanted. This approach helps minimize false positives while maximizing the protection provided to users.

How Adaptive AI utilizes the core aspects of a call

Hiya Protect’s core technology, Adaptive AI system, is the industry's only self-learning spam protection system. Adaptive AI also leverages the four aspects of call reputation to respond to emerging threats and apply the right protection to each call, without the need for human retraining.

Hiya can show you why recipients report your calls as spam

Reputation relies on recipient reactions like blocks, high abandon rates, and user reports. Enterprises need to understand when and why their recipients block their calls by analyzing the four key aspects of a call: the number, the call, the recipient, and the caller. For more information on what to do if your business calls are being labeled as spam, be sure to check out our blog.

Author Alex Salkin