Modeling and Prediction for Movies

A personalized book recommendation system that combines collaborative filtering and popularity-based methods, featuring an interactive HTML/CSS frontend and a Flask backend.

This work will help online news companies to predict news popularity before publication ,the news popularity are often indicated by the amount of reads, likes or shares. For the web news stake holders, it’s very valuable if the recognition of the news articles are often accurately predicted before the publication.

This project uses the Coronavirus (COVID-19) Tweets dataset from Kaggle to build and optimize a machine learning model that predicts the influence, i.e. the number of retweets, of Tweets.

An exploratory analysis of Spotify song tracks to predict song popularity using various Machine Learning Models.

Find users who have accounts on both Twitter and Facebook, and identify cross-posts which mean two posts are actually containing the same information.

Framework that can be applied on top of any existing popularity estimation method to improve its accuracy.

Song Popularity Analysis Dashboard

including SH model, ML model, MRBF model, Altiman Model...

Sequential prediction learning framework and algorithm

Song Popularity Predictor

An implementation for our paper: Time sensitivity-based popularity prediction for online promotion on Twitter (Information Sciences, 2020). This is an extended Latent Factor Model that can predict popularity values of tweets on Twitter when they are published at various times. The data includes Twitter user profiles and tweet information (tweetI…

Code for "Did You “Read” the Next Episode? Using Textual Cues for Predicting Podcast Popularity" accepted at NLP4MusA Workshop at ISMIR 2020

Social media monitoring system for reddit, youtube and twitter using public API's. Includes popularity prediction graph calculated using upvotes, likes and retweets prediction models.

Predicting the number of views (i.e. popularity) of videos without time series data

关于视频流行度预测算法和缓存算法

Supervised classification project that predicts a song’s potential popularity based on attributes found in Spotify data to inform business strategies that can keep Spotify competitive in the current market.

PREP: Pre-training with Temporal Elapse Inference for Popularity Prediction

TKDE 2022. CCCL: Contrastive Cascade Graph Learning.

TPIC: A social media dataset for temporal popularity prediction