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Frequently Asked Questions

  • What is SocialTrase?
    SocialTrase is a cloud-based application that allows you to efficiently perform social media background checks allowed under the Fair Credit Reporting Act (FCRA). We analyze individual subjects' posts from the major social media platforms and also web and news posts for up to the past 7 years of history for FCRA uses and 10 years for non-FCRA uses. Every post and image from this history is run through our machine learning algorithm to identify potential risks such as toxic language, threat of violence, or explicit images. We then provide an overall score in addition to post insights that can be quickly reviewed in a background report.
  • Is Social Media Background Screening Legal?
    Many employers and institutions are interested in using social media to screen potential hires. The question is, is it legal to do so? The answer is yes, with some caveats. While it is legal to conduct social media background screenings, employers must be careful not to discriminate against potential hires based on their race, gender, religion, or other protected characteristics. Additionally, employers must obtain consent from the candidate before conducting any social media background screening. At Socialtrase, we can assist users with navigating this process by assisting them by pre-screening their social media background to ensure that their online presence aligns with their desired image and goals.
  • What social media platforms do you support?
    We currently support Facebook, Twitter, Instagram, LinkedIn, TikTok, and Reddit as well as web and news articles.
  • How do you score subjects?
    Our scoring algorithm takes into considers sentiment, risk triggers, and the proportion of flagged posts to the number of overall posts. The following is the score color key: Please note that the score is NOT an indicator of a user's risk to any organization if hired/enrolled. The score is used to represent the sentiment and flag composition of the user's posts and should only be used to understand how employers and institutions may compare two or more candidates uniformly and consistently. The user assumes responsibility for analyzing the subject's posts and ultimately making a risk determination based on their own criteria.
  • Can I run a background check on a subject multiple times?
    Yes, you can run a full screening as many times as you want. We also offer continuous screening, which allows you to automatically run screens at daily, weekly, monthly, semi-annual, and annual frequencies.
  • Do you analyze private posts?
    Absolutely not. We only analyze publicly available posts. These would be posts anyone can see without being logged into the social media platform or having to be "connected" to that individual as dictated by the platform. If a post has been flagged in the report it would mean that the post intentionally or unintentionally, has public access.
  • What types of information do you analyze?
    We analyze original posts, shares (retweets), replies, likes, comments, and images the subject has posted. We do not look at who they follow, or who follows them. Note, for some social media platforms likes are private, and therefore we do not analyze these posts.
  • How much history to you analyze?
    We will go back as far as 7 or 10 years of social media history for FCRA background checks and up to 10 years for non-FCRA background checks. Note: depending on the social media platform, there may be caps on the total number of posts Ferretly is able to access. Therefore, we may not be able to access all 7 years of history in certain instances where subject has a larger volume of posts. We analyze original posts, comments, reposts, replies, and likes if available on the social media platform.
  • How many social media profiles can I add per subject?
    You can add up to 12 profiles (two for each of Twitter, Instagram, LinkedIn, Facebook, Reddit, and TikTok).
  • Does this work for posts in foreign languages?
    While we support translations of posts with support for over 80 languages, currently, our machine learning algorithm only supports US English text. You can also enter keywords in any language. We will be adding new languages in the near future.
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