Applied sentiment analysis on a real estate advertisement recommendation model
Regina Fang-Ying Lin, Jiesheng Wu, Kuo-Kun Tseng, Yuk Ming Tang, Lu Liu
Abstract
Recently, the data generated are exploding in the information age. In the post-COVID-19 era, some real estate contracts have been signed online, and online advertisement recommendation has become a new way to reduce the searching cost. Therefore, the model in which real estate online recommendations can be made suitable without user preferences has become a tricky problem. This study uses sentiment and economic data to predict real estate sales and then made an advertisement recommendation from the forecast results. The 2SA-RERec (Two Sentiment Analysis of Real Estate Recommendation) model is proposed, which shows the highest accuracy among the others.
Topics & Concepts
AdvertisingReal estateComputer scienceBusinessSentiment analysisWorld Wide WebArtificial intelligenceFinanceSentiment Analysis and Opinion MiningAdvanced Text Analysis TechniquesStock Market Forecasting Methods