A Multimodal Analysis of Embedded Climate Change Media on Twitter

Project Title: A Multimodal Analysis of Embedded Climate Change Media on Twitter
Program:
CAREERS (323)

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Tags:
ai (271), AI/ML (802)

Status: Complete
Project Leader
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Project Leader:
Suhong Li

Email: sli@bryant.edu
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Student-facilitator(s):
Jacob Dauphinais (45038)

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Project Information
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Project Description:
This project seeks to analyze video and image elements of Twitter/X posts in their association to climate change. The focus is on data pipeline to create textual descriptions using Large Language Models. More specifically the objectives are:

-Develop a methodology for video and image processing using open-source LLMs
-Test multiple open-source LLMs for effectiveness in analyzing visual media
-Perform and use sentiment and topic analysis on extracted visual content
-View potential differences/similarities between text-focused and visual media focused climate change posts



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Student Facilitator Programming Skill Level: Some hands-on experience
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Project Institution: Bryant University 
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Anchor Institution: CR-University of Rhode Island
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Start as soon as possible.: No
Project Urgency: Already behind3Start date is flexible
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Launch Presentation: https://support.access-ci.org/system/files/webform/project/5273/Careers.project.launch_Jacob_S_Dauphinais.pptx
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Final Report
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