Invention Grant
- Patent Title: Identifying and quantifying sentiment and promotion bias in social and content networks
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Application No.: US17435299Application Date: 2019-04-19
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Publication No.: US12093970B2Publication Date: 2024-09-17
- Inventor: Jelena Tesic , Lucas Rusnak
- Applicant: Texas State University
- Applicant Address: US TX San Marcos
- Assignee: Texas State University
- Current Assignee: Texas State University
- Current Assignee Address: US TX San Marcos
- Agency: Shackelford, McKinley & Norton, LLP
- Agent Robert A. Voigt, Jr.
- International Application: PCT/US2019/028317 2019.04.19
- International Announcement: WO2020/214187A 2020.10.22
- Date entered country: 2021-08-31
- Main IPC: G06Q30/0202
- IPC: G06Q30/0202 ; G06N7/01 ; G06Q50/00

Abstract:
A method, system and computer program product for identifying and quantifying sentiment and promotion bias. A set of sentiment as a measure of a group opinion is received, where a sentiment is expressed as a weight associated with an edge between two vertices in a graph. Balanced graphs associated with spanning trees corresponding to multiple views of a signed graph are constructed using the set of sentiments. Scores are assigned for each of the multiple views of the signed graph to determine an influence one group has over another group while maintaining agreement. An inequitable ratio of the assigned scores over agreeable sets of vertices of the signed graph is obtained. Based on the inequitable ratio of the assigned scores over agreeable sets of vertices of the signed graph, a more accurate sentiment bias is identified and quantified in contrast to currently existing sentiment analysis tools.
Public/Granted literature
- US20220156767A1 IDENTIFYING AND QUANTIFYING SENTIMENT AND PROMOTION BIAS IN SOCIAL AND CONTENT NETWORKS Public/Granted day:2022-05-19
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