AI Based Sentiment Analysis for News Items
Cluster3 Project ID : 37-2015-3187
Summary of the technology
Project ID : 37-2015-3187
Description of the technology
Humanities, Web Technologies
Ongoing research; several methods have been completed
Patent currently in the examination phase.
Both inductive and deductive learning methods are used to differentiate between different topics, events and actions in the public and political domains. The technology differentiates between perspectives by which topics, events and actions are described, using contextual, sequential and spatial information
The technology enables the fast decomposition of a new domain at high resolution with minimal human intervention. It uses a proprietary variation of topic modeling for inductive learning of discourse, nlp parsing tools, and deep neural networks to produce an accurate analysis of the public domain that closely resembles the way human beings perceive it
Topics described by a specific media outlet and the relations between them. This network can reveal the way an outlet frames different topics using the context in which they are presented. In the example, the difference between the way FOX News and the BBC frames the BDS is seen. While both discuss the BDS in the context of the Israeli-Palestinian conflict, FOX also creates ties between BDS and anti-Semitism (in accordance with the Israeli government's strategy), while the BBC does not.
The technology can provide strategic solutions for key questions such as how to associate or disassociate actors with certain topics or values; how messages are accepted in different outlets; and what are the typical dynamic of topics to gain or lose media and public attention. The technology has relevance for anyone needing a continuously-updated sophisticated picture of political and public domains, with an ability to forecast public discourse, such as:
Professor Shaul. R. Shenhav:https://scholars.huji.ac.il/shaulshenhav/home