Information Source Credibility Scoring via Sentiment Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for assessing the credibility of information sources on the web are inadequate for determining the reliability of information and events, as they focus on spam detection rather than evaluating the underlying credibility of sources and the probability of information being truthful, leading to potential misuse in critical decision-making processes.
Innovation Solution
A computer-implemented method that extracts and parses content items for source links, attributes sentiment scores to each link, and scores information sources based on these scores to rank the credibility of events, using a transition matrix adjusted by sentiment scores and weighted coefficients to calculate cumulative event scores and rankings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If prior art link analysis algorithms (PageRank, TrustRank, HITS) are used to rank web pages, then web page ranking is improved, but the ability to assess the reliability of information and events is insufficient
Solution Approach 1:
The patent introduces an intermediary layer (sentiment analysis module and credibility scoring system) between the link analysis algorithms and the final information reliability assessment. This intermediary processes the raw link data through sentiment analysis and credibility scoring to produce reliable information assessments, resolving the contradiction between efficient ranking and reliable assessment.
Solution Approach 2:
The patent transforms the assessment parameters from simple link-based metrics to composite parameters that include sentiment scores, credibility ratings, and reliability probabilities. This parameter transformation enables the system to assess information reliability while maintaining the efficiency of link analysis algorithms.
2Speed
If general web-based searching is used to retrieve information, then information retrieval speed is improved, but the ability to distinguish credible from misleading information is insufficient
Solution Approach 1:
The patent applies preliminary action by pre-computing sentiment scores, credibility ratings, and reliability metrics for web pages before they are actually searched or accessed. This pre-processing enables fast retrieval with built-in credibility assessment, resolving the contradiction between retrieval speed and credibility discrimination precision.
Solution Approach 2:
The patent implements feedback mechanisms where credibility assessments and sentiment analysis results are continuously refined based on user interactions and verification outcomes. This feedback loop improves measurement precision over time while maintaining retrieval speed through cached assessment data.
Data Source
AI summary
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.