Boost OSINT Investigations With Textual NLP

Boost OSINT Investigations With Textual NLP

In an era of neural networks and big data, natural language processing is becoming ever more important across various sectors. In particular, the process of analyzing textual data in the public online space is proving vital in the competitive corporate sphere. NLP can help a business socially position itself, protect a brand reputation, and conduct reliable due diligence.

Join us on  Thursday, January 19, at 1pm UTC for the webinar Boost OSINT Investigations With Textual NLP. This event will cover both the theoretical and practical sides of how NLP can transform OSINT processes to deliver essential results across a range of cases. While we will be mainly focusing on the corporate sphere, this subject will also be relevant for law enforcement specialists.

WEBINAR AGENDA

We’re excited to be co-hosting this webinar with Andrei Vladescu, Senior Analyst from the consulting and due diligence company Interdiligence. Andrei will join Social Links OSINT Specialist, Ivan Kravstov to discuss the vast utility of NLP in working with open data, followed by a first-hand demonstration of this technology in action.

Part 1: NLP In Context

This section will focus on textual NLP as a key technology in the corporate sector. Drawing  from years of experience in this area, Andrey will share his insightful rationale behind how and why NLP technology is effective in understanding a business’ positioning within a community, protecting a corporate reputation, and conducting background investigations. In these contexts, he will discuss relevant NLP techniques including:

  • Hate Speech Detection & Sentiment Analysis
  • Market Intelligence
  • Intent Classification
  • Urgency Detection
  • Opinion Polarization

Part 2: SL Professional Text Analysis Methods

In this section, Ivan Kravstov will use built-in, automated features within SL Professional to provide practical demonstrations of the various techniques outlined by Andrei. This practical session will cover how to:

  • Evaluate textual sentiment in terms of manner, tone of voice, sarcasm, level of aggression, etc.
  • Identify if and where artificial alterations or other manipulations have been employed.
  • Aggregate the social attitude of a given group.
  • Break down a text into discrete object categories.
Share this post
You’ve successfully subscribed to Blog | Social Links | Data-driven investigations
Welcome back! You’ve successfully signed in.
Great! You’ve successfully signed up.
Success! Your email is updated.
Your link has expired
Success! Check your email for magic link to sign-in.