JANUARY 19, 1 PM (UTC)
DURATION: 60 MINS

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.

By clicking on "Register for the event", you agree to the processing of the data you entered and you allow us to contact you for the purpose selected in the form. For further information, see our Data Privacy Policy.

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with textual NLP

Boost OSINT investigations

NLP: A CRUCIAL METHOD FOR THE OSINT ANALYST

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.

Social Links OSINT Analyst

IVAN KRAVTSOV

Part 1: NLP In Context

Senior Analyst at Interdiligence

Andrei Vladescu

This section will focus on textual NLP as a key technology in the corporate sector. Drawing from years of experience in this area, Andrei 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:

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:

Hate Speech Detection & Sentiment Analysis

Market Intelligence

Intent Classification

Urgency Detection

Opinion Polarization

- 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.