Publication Date
Spring 2023
Degree Type
Master's Project
Degree Name
Master of Science (MS)
Department
Computer Science
First Advisor
William Andreopoulos
Second Advisor
Katerina Potika
Third Advisor
Genya Ishigaki
Keywords
Annotation, image captioning, personalization, recommenda- tion system, twitter recommendation
Abstract
In the era of information explosion, the vast amount of data on social media platforms can overwhelm users. Not only does this information explosion contain irrelevant content, but also intentionally fabricated articles and images. As a result, personalized recommendation systems have become increasingly important to help users navigate and make sense of this data. We propose a novel technique to use users’ image preferences to recommend tweets. We extract vital information by analyzing images liked by users and use it to recommend tweets from Twitter. As many images online have no descriptive metadata associated with them, in this framework, we also provide an opportunity for the users to annotate the images they liked with the hashtags of the recommended tweets.
Recommended Citation
Kadam, Shashwat Avinash, "Personalized Tweet Recommendation Using Users’ Image Preferences" (2023). Master's Projects. 1217.
DOI: https://doi.org/10.31979/etd.q7pc-hsep
https://scholarworks.sjsu.edu/etd_projects/1217
