Graduation Semester and Year
2019
Language
English
Document Type
Thesis
Degree Name
Master of Science in Computer Science
Department
Computer Science and Engineering
First Advisor
Chengkai Li
Abstract
We are in a digital era where claims made by people can attract attention and spread like wildfire. Misinformation and disinformation about important social and political issues can be intentional and motive can be malicious. Thus, we built a Twitter monitoring platform, namely, ClaimPortal. It assists its users by searching, checking, and providing analytics of factual claims made by politicians and influential people on Twitter. ClaimPortal empowers users with a search API which enables filtering conditions such as date range, tweets from/mentioning specific users, keyword based search, hashtags, check-worthiness scores, and types of claims. We explain the architecture of ClaimPortal and its back-end data collection and computation layer.
Keywords
Social media analytics, Fact-checking, Factual claim, Twitter politics
Disciplines
Computer Sciences | Physical Sciences and Mathematics
License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Recommended Citation
Majithia, Sarthak, "ClaimPortal: Building a Social Media Analytics System for Assisting Fact-Checking" (2019). Computer Science and Engineering Theses. 305.
https://mavmatrix.uta.edu/cse_theses/305
Comments
Degree granted by The University of Texas at Arlington