Method and system for scoring credibility of information sources
AssigneeOutside Intelligence, Inc.
InventorsVictor Fernandovich Comas LIJACHEV, Daniel Ryan ADAMSON
Life of this patent
Estimating the term…
Abstract
A method for classifying information sources and content based on credibility, reliability, or trust. A content item describing an event is retrieved from an information provider and parsed for links. Each link is evaluated and attributed a sentiment score. The same event is identified in a set of know sources and an event score is calculated based on the credibility of each of the known sources. Finally, the content item is ranked based on the event and sentiment scores.
Claims13
A computer-implemented method for establishing a credibility assessment engine for assessing the credibility of internet-based information sources, wherein each information source is a provider of content, the method comprising:
- obtaining, over the internet, a set of seed content items from one or more internet-based seed sources, each seed source being either a known good (KG) source or known bad (KB) source, and a set of content items that are not seed content items from one or more internet-based information sources that are not seed sources;
- generating, from the KG sources, a set of trusted events deemed to have occurred and, from the KB sources, a set of untrusted events deemed not to have occurred;
- for each of the trusted events:
- determining a trusted subset representing a subset of seed content items from KG sources that contain the trusted event;
- determining which of the information sources link to the trusted subset;
- generating trusted extracted text by extracting the text from each of the information sources that link to the trusted subset;
- and
- building a trusted corpus comprising the trusted extracted text;
- for each of the untrusted events:
- determining an untrusted subset representing a subset of seed content items from KB sources that contain the untrusted event;
- determining which of the information sources link to the untrusted subset;
- generating untrusted extracted text by extracting the text from each of the information sources that link to the untrusted subset;
- and
- building an untrusted corpus comprising the untrusted extracted text;
- assigning, by a content analysis module comprising a processor, a link sentiment to each link of each content item in the set of content items, the link sentiments based on a similarity measure of text in the content item to the corpus of trusted texts and the corpus of untrusted texts;
- storing each link sentiment to a database of the credibility assessment engine;
- assessing the credibility of each of the information sources by combining, by a scoring module comprising a processor, the link sentiments of content items obtained from the information source;
- and
- storing the credibilities of each of the information sources to the database.
Dependencies are inferred from the claim text.