About Attributable

Attributable is a negative analytics technology designed for online ecosystems at risk of content-based threats. Unlike other security technologies which monitor threats at the network level, Attributable focuses exclusively on negative user behavior, particularly online harassment and hate speech, disinformation and fraud.

Attributable is compliant with all national privacy legislation and employs secure tokenization to protect personally identifiable information.

Why moderate negative content?

Unlike healthy debate, online harassment, disinformation and other forms of negative user content pollute online discussion, driving away legitimate users, jeopardizing advertising revenue, and increasing the likelihood of severe financial penalties from national regulatory bodies seeking to stem toxic content using legislation.

Content-based threats also correlate with other types of misbehavior, including network intrusion. Failing to moderate user misbehavior is a signal to criminals and vandals that security is lax.

Repeat Offenders

As the name suggests, Attributable is a user-centric monitoring platform. Once negative user behavior is detected, threat profiles can be used to block specific users from polluting online conversations. Attributable accommodates blacklists, greylists and whitelists to prevent content abusers from repeatedly impacting legitimate users.

Compromised Accounts

Attributable uses content analysis and geolocation to help identify compromised user accounts, stopping identity theft before other users can be influenced by trusted contacts.

Custom KPIs, Triggers and Alerts

Attributable can accommodate any existing indicators or measurements, and reacts to thresholds that you set through the Attributable online dashboard. When user behavior trips a threshold, notifications can instantly alert you to potential risks, threats or outages.

Learn more about how Attributable can protect your specific ecosystem by scheduling a conversation with one of our content security experts.