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High-Throughput Linguistic Content Sentiment Analysis
The project has the following objectives:
1. To build a simulation for a generic social model, to represent how effective a toxic text sentiment
detection algorithm/model works within simulation
a. Building a simulation model
b. Testing the performance of the model using a dataset
c. Evaluation of the model
2. Optimizing existing toxic text detection algorithms/model to highly perform within the simulation
Faculty Supervisor:
Ketra Schmitt
Student:
Partner:
Scrawlr Development Inc.
Discipline:
Engineering
Sector:
Agriculture; Information and cultural industries; Professional, scientific and technical services
University:
Concordia University
Program:
Business Strategy Internship
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